New! View global litigation for patent families

US20020032740A1 - Data mining system - Google Patents

Data mining system Download PDF

Info

Publication number
US20020032740A1
US20020032740A1 US09918312 US91831201A US2002032740A1 US 20020032740 A1 US20020032740 A1 US 20020032740A1 US 09918312 US09918312 US 09918312 US 91831201 A US91831201 A US 91831201A US 2002032740 A1 US2002032740 A1 US 2002032740A1
Authority
US
Grant status
Application
Patent type
Prior art keywords
web
information
address
database
person
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US09918312
Inventor
Jonathan Stern
Jeremy Rothman-Shore
Kosmas Karadimitriou
Michel Decary
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zoom Information Inc
Original Assignee
Eliyon Tech Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor ; File system structures therefor
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • G06F17/30864Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor ; File system structures therefor
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • G06F17/30864Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/953Organization of data
    • Y10S707/959Network
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99931Database or file accessing
    • Y10S707/99933Query processing, i.e. searching
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99931Database or file accessing
    • Y10S707/99933Query processing, i.e. searching
    • Y10S707/99935Query augmenting and refining, e.g. inexact access
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99931Database or file accessing
    • Y10S707/99933Query processing, i.e. searching
    • Y10S707/99936Pattern matching access
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99931Database or file accessing
    • Y10S707/99937Sorting
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99943Generating database or data structure, e.g. via user interface
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99944Object-oriented database structure
    • Y10S707/99945Object-oriented database structure processing
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10STECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00Data processing: database and file management or data structures
    • Y10S707/99941Database schema or data structure
    • Y10S707/99948Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

A computer automated method and system mines from a global computer network, information about people and organizations. The system includes automated crawling means, a distributor controlling the crawling means processing, an extractor storing extracted information of interest in a database, an integrator and post-processor. The integrater resolves duplicate information and combines related information in the database. The post-processor analyzes the database contents and generates (by deduction) missing information. Also disclosed is a method and means for generating a business email address of a person named in the database, from the respective organization named in the database for the subject person.

Description

    RELATED APPLICATIONS
  • [0001]
    This application claims the benefit of U.S. Provisional application Ser. No. 60/221,750, filed on Jul. 31, 2000, the entire teachings of which are incorporated herein by reference. This application also relates to U.S. patent application Ser. No. 09/704,080, filed Nov. 1, 2000; U.S. patent application Ser. No. 09/703,907, filed Nov. 1, 2000; U.S. patent application Ser. No. 09/768,869 filed Jan. 24, 2001; U.S. patent application Ser. No. 09/821,908 filed Mar. 30, 2001; and U.S. patent application Ser. No. _____, filed Jul. 20, 2001, entitled “Computer Method and Apparatus for Extracting Data from Web Pages”, Attorney Docket No. 2937.1000-005, all by the Assignee of the present invention and herein incorporated by reference.
  • BACKGROUND OF THE INVENTION
  • [0002]
    Generally speaking a global computer network, e.g., the Internet, is formed of a plurality of computers coupled to a communication line for communicating with each other. Each computer is referred to as a network node. Some nodes serve as information bearing sites while other nodes provide connectivity between end users and the information bearing sites.
  • [0003]
    The explosive growth of the Internet makes it an essential component of every business, organization and institution strategy, and leads to massive amounts of information being placed in the public domain for people to read and explore. The type of information available ranges from information about companies and their products, services, activities, people and partners, to information about conferences, seminars, and exhibitions, to news sites, to information about universities, schools, colleges, museums and hospitals, to information about government organizations, their purpose, activities and people. The Internet became the venue of choice for every organization for providing pertinent, detailed and timely information about themselves, their cause, services and activities.
  • [0004]
    The Internet essentially is nothing more than the network infrastructure that connects geographically dispersed computer systems. Every such computer system may contain publicly available (shareable) data that are available to users connected to this network. However, until the early 1990's there was no uniform way or standard conventions for accessing this data. The users had to use a variety of techniques to connect to remote computers (e.g. telnet, ftp, etc) using passwords that were usually site-specific, and they had to know the exact directory and file name that contained the information they were looking for.
  • [0005]
    The World Wide Web (WWW or simply Web) was created in an effort to simplify and facilitate access to publicly available information from computer systems connected to the Internet. A set of conventions and standards were developed that enabled users to access every Web site (computer system connected to the Web) in the same uniform way, without the need to use special passwords or techniques. In addition, Web browsers became available that let users navigate easily through Web sites by simply clicking hyperlinks (words or sentences connected to some Web resource).
  • [0006]
    Today the Web contains more than one billion pages that are interconnected with each other and reside in computers all over the world (thus the term “World Wide Web”). The sheer size and explosive growth of the Web has created the need for tools and methods that can automatically search, index, access, extract and recombine information and knowledge that is publicly available from Web resources.
  • [0007]
    The following definitions are used herein.
  • Web Domain
  • [0008]
    Web domain is an Internet address that provides connection to a Web server (a computer system connected to the Internet that allows remote access to some of its contents). URL
  • [0009]
    URL stands for Uniform Resource Locator. Generally, URLs have three parts: the first part describes the protocol used to access the content pointed to by the URL, the second contains the directory in which the content is located, and the third contains the file that stores the content:
  • [0010]
    <protocol>: <domain><directory><file>
  • [0011]
    For example:
  • [0012]
    http://www.corex.com/bios.html
  • [0013]
    http://www.cardscan.com/index.html
  • [0014]
    http://ft.cnn.com/archives/may99/pr37.html
  • [0015]
    ftp://shiva.lin.com/soft/words.zip
  • [0016]
    Commonly, the <protocol>part may be missing. In that case, modem Web browsers access the URL as if the http:// prefix was used. In addition, the <file>part may be missing. In that case, the convention calls for the file “index.html” to be fetched.
  • [0017]
    For example, the following are legal variations of the previous example URLs:
  • [0018]
    www.corex.com/bios.html
  • [0019]
    www.cardscan.com
  • [0020]
    fn.cnn.com/archives/may99/pr37.html
  • [0021]
    ftp://shiva.lin.com/soft/words.zip
  • Web Page
  • [0022]
    Web page is the content associated with a URL. In its simplest form, this content is static text, which is stored into a text file indicated by the URL. However, very often the content contains multi-media elements (e.g. imnages, audio, video, etc) as well as non-static text or other elements (e.g. news tickers, frames, scripts, streaming graphics, etc). Very often, more than one files form a Web page, however, there is only one file that is associated with the URL and which initiates or guides the Web page generation.
  • Web Browser
  • [0023]
    Web browser is a software program that allows users to access the content stored in Web sites. Modem Web browsers can also create content “on the fly”, according to instructions received from a Web site. This concept is commonly referred to as “dynamic page generation”. In addition, browsers can commonly send information back to the Web site, thus enabling two-way communication of the user and the Web site.
  • [0024]
    As our society's infrastructure becomes increasingly dependent on computers and information systems, electronic media and computer networks progressively replace traditional means of storing and disseminating information. There are several reasons for this trend, including cost of physical vs. computer storage, relatively easy protection of digital information from natural disasters and wear, almost instantaneous transmission of digital data to multiple recipients, and, perhaps most importantly, unprecedented capabilities for indexing, search and retrieval of digital information with very little human intervention.
  • [0025]
    Decades of active research in the Computer Science field of Information Retrieval have yield several algorithms and techniques for efficiently searching and retrieving information from structured databases. However, the world's largest information repository, the Web, contains mostly unstructured information, in the form of Web pages, text documents, or multimedia files. There are no standards on the content, format, or style of information published in the Web, except perhaps, the requirement that it should be understandable by human readers. Therefore the power of structured database queries that can readily connect, combine and filter information to present exactly what the user wants is not available in the Web.
  • [0026]
    Trying to alleviate this situation, search engines that index millions of Web pages based on keywords have been developed. Some of these search engines have a user-friendly front end that accepts natural languages queries. In general, these queries are analyzed to extract the keywords the user is possibly looking for, and then a simple keyword-based search is performed through the engine's indexes. However, this essentially corresponds to querying one field only in a database and it lacks the multi-field queries that are typical on any database system. The result is that Web queries cannot become very specific; therefore they tend to return thousands of results of which only a few may be relevant. Furthermore, the “results” returned are not specific data, similar to what database queries typically return; instead, they are lists of Web pages, which may or may not contain the requested answer.
  • [0027]
    In order to leverage the information retrieval power and search sophistication of database systems, the information needs to be structured, so that it can be stored in database format. Since the Web contains mostly unstructured information, methods and techniques are needed to extract data and discover patterns in the Web in order to transform the unstructured information into structured data.
  • [0028]
    The Web is a vast repository of information and data that grows continuously. Information traditionally published in other media (e.g. manuals, brochures, magazines, books, newspapers, etc.) is now increasingly published either exclusively on the Web, or in two versions, one of which is distributed through the Web. In addition, older information and content from traditional media is now routinely transferred into electronic format to be made available in the Web, e.g. old books from libraries, journals from professional associations, etc. As a result, the Web becomes gradually the primary source of information in our society, with other sources (e.g. books, journals, etc) assuming a secondary role.
  • [0029]
    As the Web becomes the world's largest information repository, many types of public information about people become accessible through the Web. For example, club and association memberships, employment information, even biographical information can be found in organization Web sites, company Web sites, or news Web sites. Furthermore, many individuals create personal Web sites where they publish themselves all kinds of personal information not available from any other source (e.g. resume, hobbies, interests, “personal news”, etc).
  • [0030]
    In addition, people often use public forums to exchange e-mails, participate in discussions, ask questions, or provide answers. E-mail discussions from these forums are routinely stored in archives that are publicly available through the Web; these archives are great sources of information about people's interests, expertise, hobbies, professional affiliations, etc.
  • [0031]
    Employment and biographical information is an invaluable asset for employment agencies and hiring managers who constantly search for qualified professionals to fill job openings. Data about people's interests, hobbies and shopping preferences are priceless for market research and target advertisement campaigns. Finally, any current information about people (e.g. current employment, contact information, etc) is of great interest to individuals who want to search for or reestablish contact with old friends, acquaintances or colleagues.
  • [0032]
    As organizations increase their Web presence through their own Web sites or press releases that are published on-line, most public information about organizations become accessible through the Web. Any type of organization information that a few years ago would only be published in brochures, news articles, trade show presentations, or direct mail to customers and consumers, now is also routinely published to the organization's Web site where it is readily accessible by anyone with an Internet connection and a Web browser. The information that organizations typically publish in their Web sites include the following:
  • [0033]
    Organization name
  • [0034]
    Organization description
  • [0035]
    Products
  • [0036]
    Management team
  • [0037]
    Contact information
  • [0038]
    Organization press releases
  • [0039]
    Product reviews, awards, etc
  • [0040]
    Organization location(s)
  • [0041]
    . . . etc . . .
  • SUMMARY OF THE INVENTION
  • [0042]
    Information about people is fairly prevalent on the Internet and almost every Web site contains some mentions about people. For example: many sites put up by companies (company Web sites) include information about their management team, their Public Relations person and in some cases their entire staff. Hospitals, universities and other academic institution sites tend to list their entire faculty and senior staff along with credentials and areas of specialty. News sites, magazines, newspapers, newsletters and other news and information sources contain articles and news about people. Even if the subject of the article is not about a person the article invariably will contain quotes from people with basic information about the organization they work for and their position or title in the organization. For example, an article about the explosive growth of the Web might contain a quote like: “‘Browser technology is now the foundation of our next generation software.’ said William H. Gates, founder and Chairman of Microsoft Corporation in Redmond Wash., a leading software company.”
  • [0043]
    All of this data is publicly available in the Web. However, since it is not organized in any standard fashion, it is extremely difficult for someone to find answers to questions such as: “What are the names of all Marketing Directors of high-tech companies in the New England area?” The purpose of the present invention is to extract this kind of public data about people from the Web and organize it into a database, so that simple database queries can answer such questions.
  • [0044]
    In addition to people information, this invention also extracts from the Web organization information. Many people are working in positions that directly relate to the organization's core activities. Hence their skills, knowledge and specialty likely match the activity of the workplace. Gathering information about the organization adds another dimension to the biographical information collected and maintained about people.
  • [0045]
    An organization's Web site contains a lot of information about the organization, its business, products, mission, people, location, partners and more. As with people, the described invention can only collect and organize information that exist on the site itself, hence the level, accuracy and amount of collected information will vary from organization to organization. In general, one can expect to find some or all of the following information.
  • [0046]
    The full name of the organization and commonly used aliases of it
  • [0047]
    The address of the organization headquarters and other offices and subsidiaries.
  • [0048]
    The location of the organization is of great significance since it generally points to the location of its people and therefore augments the record of the people associated with the organization.
  • [0049]
    Contact information including phone, fax and certain general email addresses such as sales@corpx.com
  • [0050]
    Organization description
  • [0051]
    Organization mission
  • [0052]
    Products and services
  • [0053]
    Common noun phrases. Noun phrases that appear often on an organization Web site are significant sources of information identifying the main keywords describing the organization and hence the people who are associated with it. Noun phrases such as “signal processing”, “public relations”, “intellectual property” or “early childhood” can dramatically narrow a search for people in a specific profession.
  • [0054]
    Creating a database about people and organizations could, of course, be done manually. Since this data is publicly available, human employees could scan the Web and other sources and populate a database with the data. However, there are significant drawbacks in this manual approach:
  • [0055]
    a) it is too expensive. Tens or hundreds of workers would be needed to scan and extract data even for a small fraction of the Web.
  • [0056]
    b) it is too slow. Scanning and extracting data from one Web site may require many man-hours of work—even working on a single Web page may require several minutes of work.
  • [0057]
    c) it is error prone. Human errors are unavoidable, both in finding the data and in transferring them to the database.
  • [0058]
    In contrast to the manual approach, the purpose of the present invention is to develop an automated approach for the data extraction and collection. The benefits over the manual approach are obvious:
  • [0059]
    a) automation is cheap. Computers can work 24 hours a day, 7 days a week. A single personal computer can replace tens of human workers in this data extraction task.
  • [0060]
    b) computers are fast. In general, using the method described in this invention, 5 minutes of computer time in a low-cost computer can produce the same data as several man-hours of manual work.
  • [0061]
    c) very high accuracy can be achieved. Even though programming errors are unavoidable, these errors can usually be found and corrected fairly easily, so that the accuracy of the system increases over time.
  • [0062]
    In a preferred embodiment, a computer automated system and method mines, from a global computer network, information on people and organizations. The invention system (and method functions/operations) includes:
  • [0063]
    a plurality of automated crawlers for transversing sites of a global computer network and retrieving pages that contain information of interest;
  • [0064]
    a distributor coupled to the crawlers for controlling crawler processing;
  • [0065]
    an extractor responsive to the crawler retrieved pages and extracting information about people and organizations therefrom, the extracted information being stored in a database;
  • [0066]
    an integrator coupled to the database for resolving duplicate information and combining related information in the database; and
  • [0067]
    a post processor coupled to the database for analyzing contents of the database and generating missing information therefrom.
  • [0068]
    Preferably the database stores information about different people in different respective records. Given two records of potentially the same person, the integrator combines the two records if: (a) name of the person is the same in the two records, and (b) either affiliated organization name or respective title is the same in the two records. The integrator may also consider person name - title combination matches in light of the statistical rarity of the title and person's name.
  • [0069]
    In accordance with one aspect of the present invention, the post-processor generates an email address (e.g. business/non-personal email address) of a subject person named in the database with respect to organization named in the database for the subject person. The email address is generated by the post-processor:
  • [0070]
    obtaining a working e-mail address to the respective organization, the working e-mail address not being the e-mail address of the subject person;
  • [0071]
    deducing from the working e-mail address, format of e-mail addresses to the respective organization;
  • [0072]
    using the deduced information, constructing potential (i.e. candidate) e-mail addresses for the subject person; and
  • [0073]
    verifying each constructed potential e-mail address by testing each, such that at least one verified constructed potential e-mail address provides a business e-mail address of the subject person.
  • [0074]
    The post-processor also may utilize predefined common email address formats to construct potential business/non-personal email addresses of the subject person.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0075]
    The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention.
  • [0076]
    [0076]FIG. 1 is a block diagram of a preferred embodiment of the present invention.
  • [0077]
    [0077]FIG. 2 is a schematic illustration of a global computer network in which the invention system of FIG. 1 operates.
  • [0078]
    [0078]FIG. 3 is a flow diagram of email address interpolation by a post-processor of the embodiment of FIG. 1.
  • [0079]
    [0079]FIG. 4 is a flow diagram of duplicate record detection for merger by an integrator of the embodiment of FIG. 1.
  • DETAILED DESCRIPTION OF THE INVENTION
  • [0080]
    As illustrated in FIG. 1, the main components of the invention system 40 are the following:
  • [0081]
    a) The “Crawler” 11: a software robot that visits and traverses Web sites in search of Web pages that contain information of interest
  • [0082]
    b) The “Distributor” 47: a software system that controls several Crawler processes
  • [0083]
    c) The “Extractor” 41: a software module that processes Web pages returned by the Crawler 11 to extract the information about people and companies (organizations).
  • [0084]
    d) The “Loader” 43: a software program that loads the data found by the Extractor into the database.
  • [0085]
    e) The database 45: the place where all the information are stored.
  • [0086]
    f) The “Integrator” 49: a software module that resolves duplicates, and combines related information in the database.
  • [0087]
    g) The “Post-Processor 51” which enhances the data, in particular analyzes the data and adds missing pieces of information, such as email addresses.
  • [0088]
    It is understood that each component 11, 47, 41, 43, 45, 49, 51 is implemented in hardware, software or a combination thereof and is executed by digital processing means (e.g., a computer) 27. A single computer or a series of computers processing in parallel, distributed or other fashion is suitable. For example as illustrated in FIG. 2, computer 27 executes invention system 40 in working memory. Computer 27 is coupled across communication lines 23 to a global network 21 of computers 25. Each node 25, 27 on the network 21 has a respective architecture (e.g., local area network, wide area network, client server, etc.) which may use routers, high speed connections, and the like to couple to global network 21. Some nodes may serve as service providers or host servers to a multiplicity of end users, and so forth.
  • [0089]
    Returning to FIG. 1, the Crawler 11 is a software robot that systematically visits and traverses Web sites in order to identify and collect Web pages that contain information of interest to the users. Such a robot for extracting information about people and organizations is described in detail in U.S. patent application Ser. No. 09/821,908 filed Mar. 30, 2001 entitled “Computer Method and Apparatus for Collecting People and Organization Information from Web Sites” by Jonathan Stem, Kosmas Karadimitriou, Jeremy W. Rothman-Shore and Michel Decary.
  • [0090]
    In order for the Crawler 11 to be effective in collecting Web pages with useful content, it must be able to perform the following functions:
  • [0091]
    a) identify the type of the site visited (e.g. company Web site, University Web site, personal Web site, etc.)
  • [0092]
    b) identify the name of the copyright owner of the site (i.e. the individual or organization that is responsible for the content published in the Web site)
  • [0093]
    c) identify the type of content that individual Web pages contain (e.g. contact information, list of people, multimedia content, etc.)
  • [0094]
    d) identify early in the process of traversing the Web site its expected structure (e.g. organization and type of Web pages and site link structure)
  • [0095]
    e) “prune” the site tree in order to avoid visiting parts that are not expected to produce much useful information.
  • [0096]
    Each of these is addressed in the related applications.
  • [0097]
    All of these functions are essential so that the Crawler 11 can harvest the most useful and content-rich Web pages from a Web site by visiting as few pages as possible. In other words, the Crawler 11 traverses the site in such a way so that it visits many pages with high information content, and few pages with little or no useful information. Note that the term “useful information” is relevant to what is considered useful by the system users. So, for example, users that use the system to collect information about a chemical process may consider “useful” any Web page with content that relates directly or indirectly to chemistry. On the other hand, users that want to collect information about company locations may consider useful any page that contains at least one address.
  • [0098]
    All of the data collected by the crawler 11 (web site type, copyright owner, list of interesting pages, etc.) are passed to the other components of the system so that they may use this data in their own analyses.
  • [0099]
    In general, the automated system 40 described by this invention needs to be as efficient as possible because of the sheer size of Web. One of the measures of efficiency is the number of Web sites visited and traversed per hour. The Web currently contains many million Web sites (estimates in January 2000 set this number to over 10 million Web sites and they keep increasing exponentially). A system that can visit and extract information from an average of 10 Web sites per hour will need at least 1 million hours to cover the entire Web, that is, about 100 years! On the other hand, a system that can visit 1,000 Web sites per hour (100 times more efficient) will need about 1 year to cover the entire Web, whereas a system capable of visiting 10,000 Web sites per hour can cover the entire Web in less than 2 months. These estimates are tabulated in the next table:
    Time Needed to Cover the
    System throughput Entire Web
    10 Web sites/hour 100 years
    100 Web sites/hour 10 years
    1,000 Web sites/hour 1 year
    10,000 Web sites/hour less than 2 months
  • [0100]
    The term “system throughput” is used to refer to the number of Web sites visited and processed per hour. The system throughput is related to the average time that the invention system 40 needs to visit and process (extract information) from one Web site: Systemthroughput = 1 Average time per Website
    Figure US20020032740A1-20020314-M00001
  • [0101]
    In general, the average time per Web site is the sum of the times needed by each system module to perform its functions, that is:
  • Average time per Web site=TCrawler+TExtractor+TLoader+TIntegrator
  • [0102]
    where
  • [0103]
    TCrawler is the time required by the Crawler 11 to crawl one Web site,
  • [0104]
    TExtractor is the time required by the Extractor 41 to extract data from the contents of one Web site,
  • [0105]
    TLoader is the time required by the Loader 43 to load in the database 45 the data extracted by the Extractor 41 from one Web site, and
  • [0106]
    TIntegrator is the time required by the Integrator 49 to post-process and clean up the data related to one Web site.
  • [0107]
    However, by arranging these modules in a pipeline fashion we can process multiple Web sites simultaneously, that is, while the Crawler 11 is crawling one Web site, the Loader 43 is loading the data from another Web site, and the Integrator 49 is processing the data from yet another Web site. In that case, the average time per Web site becomes equal to the maximum time among all components, that is:
  • Average time per Web site=Maximum of (Tcrawler, TExtactor, TLoader, TIntegrator)
  • [0108]
    In any modern computer system, processing data and performing database transactions is much faster than accessing the Web. Even when high-speed Internet connections are used, the time to access and download Web pages is bounded by the speed of the Web servers where the pages reside, by the network “path” that is used to transfer the data, and by the Internet “status” when this communication take place. So in general, accessing the Web is by far the slowest operation that the invention system 40 must perform, therefore the average time per Web site is practically equal to the time required by the Crawler 11 to visit and traverse one Web site:
  • Average time per Web site=TCrawler
  • [0109]
    and the system throughput becomes: System throughput = 1 T Crawler
    Figure US20020032740A1-20020314-M00002
  • [0110]
    This means that in order to increase the system 40 efficiency and be able to traverse the entire Web in a reasonable amount of time, one needs to decrease the average time required to crawl one Web site. However, as noted above, this cannot be achieved by simply using more powerful computers or better Internet connections, because this time is bounded by external factors (responsiveness of external Web servers, Internet status, etc). In other words, no matter how efficiently one builds the Crawler 11 or how fast an Internet connection one uses, the average time that is needed to crawl one Web site cannot be reduced arbitrarily. Thus, the only way to achieve the desired system throughput is to use multiple Crawlers 11. In fact, even when using a relatively slow crawler that visits only 100 sites per hour and it would take by itself 10 years to cover the entire Web, when employing 100 such Crawlers 11 one can cover the entire Web in less than 2 months.
  • [0111]
    This discussion has demonstrated so far that the only way to achieve reasonable system throughput is to use several (in the order of hundreds) Crawler 11 processes simultaneously. In this case, controlling and administrating manually all these processes becomes a challenge, to say the least. Therefore a separate software module is needed that automates this process. This module is the Distributor 47.
  • [0112]
    Because the Distributor 47 is integrated with the Crawler 11, it is able to adjust the schedule of which websites to visit by leveraging the information that the Crawler 11 extracted during previous visits. Because the crawler 11 is automatically determining the site type, the Distributor 47 is able to give higher priority to some sites and lower priority to others. For example, if the crawler 11 found a site with a daily news feed, the Distributor 47 may adjust the schedule to visit this website on a daily basis. At the same time, if the crawler 11 finds a website that is uninteresting because it does not contain data relevant to what is being extracted, such as someone's personal website, the Distributor 47 adjusts the schedule to visit the website only every six months or longer.
  • [0113]
    To summarize, several Crawler 11 processes are needed by the system 40 in order to increase its efficiency, and an automated method must be employed to manage all these processes. The Distributor 47 offers exactly this functionality: it is a software module whose main function is to control and distribute work to multiple Crawlers 11. The Distributor 47 uses a database 14 to keep track of all the Web sites that must be visited, and the visiting schedule for each one (some Web sites must be visited more frequently than others, depending on how often their contents change). In addition, the Distributor 47 prioritizes the Web sites according to their relative importance for the users, and it manages the Crawlers 11 so that the most important sites are visited first. The Distributor 40 is responsible to start multiple Crawler 11 processes, and keep their number as high as possible, without hurting the overall system performance. It also monitors the status of the running Crawler processes and stops or kills any processes that exhibit unwanted behavior (e.g. a process that takes too long, uses too much memory or disk space, etc).
  • [0114]
    Every Crawler 11 returns and saves in local storage 48 a set of Web pages 12 that potentially contain useful information. These Web pages 12 are then processed by a software module that can extract data from HTML code or plain text, the Extractor 41.
  • [0115]
    The Extractor 41 uses linguistic methods to parse and “understand” text so that it identifies and extracts useful information. The users of the system 40 define what they consider to be “useful” information, and customize accordingly the Extractor 41. Note that the Extractor 41 itself is a very generic and flexible tool, that has the ability to read and parse correctly text written in any language, according to the syntax and grammar rules of that language. However, it needs customization in order to work with a specific language (e.g. English, French, German, etc.) and furthermore, it needs to be “trained” in order to recognize what the users consider useful information.
  • [0116]
    Customizing the Extractor 41 for a specific language means that one provides it with a set of syntax and grammar rules so that it correctly identifies subject, verb and object in a sentence, it recognizes the time that the sentence refers to (past, present or future), it recognizes the beginning and end of sentences, etc. Training the Extractor 41 for recognizing “useful” information means that one provides it with rules and dictionaries of specific terms so that it recognizes keywords and using the rules it decides when something is useful or not. In general, this training may be automated in a significant level, by using examples of “useful” and “useless” text and let the Extractor 41 determine statistically what are the terms that may be considered as keywords of useful information, and also what are good rules (or tests) that may be used during the data extraction process. There are various methods and techniques that the Extractor 41 may use for its internal decision making and pattern recognition, for example, template-based pattern recognition (see U.S. patent application Ser. No. 09/585,320 filed on Jun. 2, 2000 for a “Method and Apparatus for Deriving Information from Written Text”), Bayesian Networks for decision making (see U.S. patent application Ser. No. 09/704,080, filed Nov. 1, 2000 entitled “Computer Method and Apparatus for Determining Content Owner of a Web Site”; U.S. patent application Ser. No. 09/703,907, filed Nov. 1, 2000 entitled “Computer Method and Apparatus for Determining Site Type of a Web Site; U.S. patent application Ser. No. 09/768,869 filed Jan. 24, 2001 entitled “Computer Method and Apparatus for Determining Content Types of Web Pages”), Neural Networks for data classification, Genetic Algorithms for selection of “good” rules and keywords, etc.
  • [0117]
    Where the Extractor 41 is part of the same system 40 as the Crawler 11, it uses the list of interesting pages 12 (stored at 48 in FIG. 1) as input to process on. Also, it uses the website type and determined copyright owner to assist interpretation of the data. For example, if the website is a Company website, Extractor 41 concludes people whose names are found on a management team page on the website work for the company identified as the copyright owner, even though such is not directly stated on the page.
  • [0118]
    For a detailed description of a preferred Extractor 41 that is customized to extract information about people from the Web see U.S. patent application Ser. No. ________ ,filed Jul. 20, 2001 entitled “Computer Method and Apparatus for Extracting Data from Web Pages”, Attorney Docket No. 2937.1000-005. That Extractor 41 uses various methods and techniques described in U.S. patent application Ser. No. 09/585,320 filed on Jun. 2, 2000 for a “Method and Apparatus for Deriving Information from Written Text”.
  • [0119]
    For mining information about people and organizations, the Extractor 41 extracts the following data:
  • [0120]
    a) Names of People
  • [0121]
    b) Positions that these people hold or have held, including title, organization name, organization location, state and end dates, and whether the person still holds the position
  • [0122]
    c) Educational degrees these people have received
  • [0123]
    d) Certifications that these people have received (e.g. CPA, RN, LCSW, . . . )
  • [0124]
    e) An email address for the person, if available
  • [0125]
    f) A description of the copyright owner, if it is a company website
  • [0126]
    g) An address for the copyright owner, if it is a company website
  • [0127]
    h) Subsidiaries, partners and competitors for the copyright owner, if it is a company website
  • [0128]
    i) Number of employees
  • [0129]
    j) Relevant date for each piece of information—some documents are old, even if they are recently published. If a document is dated, the date must be collected and attached to all information found on it.
  • [0130]
    In the preferred embodiment, Extractor 41 places the foregoing extracted data into working records 16 (for information on people), 17 (for information on organizations).
  • [0131]
    After the Extractor 41 has processed the Web pages returned by a Crawler 11 and it has extracted the useful information, it passes the extracted information (records 16, 17) to the Loader 43, which is the software module responsible for storing the information in the database 45. One of Loader's 43 responsibilities is to make sure that the information is internally consistent, for example, with no duplicate or conflicting data (i.e., no duplicate records 16, 17). The Loader 43 also implements data filtering rules that have been given by the system users in order to avoid cluttering the database with “garbage” data. For example, in a system built to collect people information, the Extractor 41 may return any information it finds connected to a person's name. However, the Loader 43 may employ filters to discard any information referring to fictional characters or historical figures, e.g. Donald Duck or Alexander the Great, and load in the database 45 only what appears to be current information about real (and alive) people.
  • [0132]
    Note that some of this filtering may also be performed as post-processing by the Integrator 49, however, by doing the filtering prior to loading the information/records 16, 17 into the database 45, one avoids cluttering the system with obviously useless data. Also some filtering rules may be employed by the Extractor 41, however, the Extractor 41 preferably does not communicate directly with the database 45, and some of the filtering may require database access.
  • [0133]
    Another major responsibility of the Loader 43 is to merge information found by the Extractor 41 from separate Web pages in the same Web site. In general, the Extractor 41 works in a page-by-page mode, extracting any information it finds in each individual page. Very often though, the same information may be found repeatedly in more than one Web page from the Web site, e.g. every press release potentially contains the company address. The Extractor 41 itself may keep track of what information it has found as it progressively process all the Web pages from a Web site, however, that would require a lot of “bookkeeping” from the Extractor 41. A simpler way is to let the Extractor 41 extract all the useful information it finds, and then let the Loader 43 decide what is duplicate information or merge pieces of partial information. For example, the first and last name of an employee may be found in one Web page, whereas another Web page contains only his last name and his title. The Loader 43 recognizes that these two pieces of information actually complement one another, and that they may be safely merged into one piece that contains the first name, last name, and title of the person.
  • [0134]
    The Loader 43 also uses the data collected by the Crawler 11 and the Extractor 41 to tie disparate pieces of information together at the database level. For example, if the Crawler 11 finds that the owner of a website is company “A”, and the Extractor 41 finds an address for company “A” and a person working for company “A”, the loader 43 combines this information when storing it in the database 45 to show that this person works for company A at the found address.
  • [0135]
    The Loader 43 also assigns a date to all of the information that it loads. A press release is often maintained on an organization's Web site for years, but the information can quickly go out of date. For example, if the CEO of a company is replaced, all of the older press releases will still refer to that person as working at the company. In any kind of news article or press release, the date of the information must be captured.
  • [0136]
    Each record 16, 17 carries two dates: the date that the information was extracted, and the original date of the document if such a date can be found. If a page does not contain a date and it is a management team page, it can generally be assumed to be current.
  • [0137]
    The modification date of a document on the Internet cannot be used to date the information in the article, since this can change for technical reasons, such as using a new layout for a Web site, a page can be dynamically generated, etc.
  • [0138]
    A preferred embodiment of Loader 43 is described in the related U.S. patent application Ser. No. ______, filed Jul. 20, 2001, entitled “Computer Method and Apparatus for Extracting Data from Web Pages”, Attorney Docket No. 2937.1000-005, cited above.
  • [0139]
    The database 45 used by the system 40 must be a modem high-end database that can handle large quantities of data and a high number of transactions. The amount of data collected by the system 40 can potentially tax the capacity and capabilities of any database system, therefore particular attention must be paid to the specifications and maintenance of the database 45. Of course, this also depends on the user requirements and the type of information that the system is designed to collect; for example, a system that collects information about “the health industry” probably requires higher capacity database than another system that collects information about “zebras”. In addition, a system that offers a Web interface through which anybody in the world may access the data requires a much more powerful database than another system which is not expected to have more than 10 users at a time browsing through the data.
  • [0140]
    Another part of the invention 40 system is the Integrator 49, the software module that periodically operates on the data in the database 45 trying to identify duplicate data, aliases, and merge or remove any incomplete or low-quality data. In essence, the Integrator 49 finds and exploits any data connections that may exist in the database 45.
  • [0141]
    When performing Web data mining, there are basically three types of “data connections” or associations:
  • [0142]
    a) Data connections within a Web page
  • [0143]
    An example of this type of data connection is a Web page that contains the biography of a person. This page may start with the sentence “When Mr. Jonathan Stern, CEO of Corex Technologies Corp., decided to . . . ” From this sentence, the following data can be extracted:
  • [0144]
    “Mr. Jonathan Stern, CEO, Corex Technologies Corp., present”
  • [0145]
    Later on the same page, another sentence may contain: “Prior to Corex, Jonathan was the CEO of Rosh Intelligent Systems where he . . . ” From this sentence, the following data can be extracted:
  • [0146]
    “Jonathan, CEO, Rosh Intelligent Systems, past”
  • [0147]
    It is obvious to a human reader that these two pieces of data are interconnected, referring to the same person. This is a very common type of data interconnections in text that was meant to be read by humans. It assumes that as the reader proceeds through the text he/she keeps a mental “trace” or “memory” of the information already given so that there is no need to repeat continuously in every sentence “Mr. Jonathan Stern, CEO, Corex Technologies Corp”.
  • [0148]
    In the system 40 described in the current invention, this level of data interconnections are handled and resolved at the Extractor 41 level.
  • [0149]
    b) Data connections within a Web site
  • [0150]
    Another type of data connection may exist in the Web site level. Very often, a Web site is focused on providing information about a specific “subject”. For example, company Web sites usually provide information related to the company, whereas a Web site maintained by the “Johnny Cash Fan Club” probably contains information that is focused exclusively to the singer Johnny Cash. A Web site with such a strong focus tends to assume that human readers are familiar with the central subject of the site and so the site often provides incomplete information in its Web pages. For example, a company Web site may provide the company address in some Web page without including the company name, since it is assumed that a human reader already knows the company name.
  • [0151]
    As it has been described in the previous sections, these type of data connections are handled in the system by the Loader 43.
  • [0152]
    c) Data connections among different Web sites
  • [0153]
    Finally, the third type of data connections refers to data collected from different Web sites. For example, in a system built to collect company information, the products of “RND Corporation” may be found in the RND Corporation's Web site, the stock ticker for this company may be found in the Fidelity Investments Web site, a brief description about the company may be found in a press release from the PRNewsWire Web site, whereas reviews about the company's flagship product may be found in a trade publication's Web site.
  • [0154]
    In the current system 40, the Integrator module 49 identifies and handles this type of data connections. As the database 45 is populated with new data and older data are “refreshed” by revisiting Web sites, new interconnections of this type are continuously introduced. For every new piece of information, the Integrator 49 “scans” the database to find other pieces of information that potentially share a connection. FIG. 4 illustrates the Integrator 49 process.
  • [0155]
    Combining people information from different sources is performed only if a reasonable match is found on two separate pieces of data between two records 16. One of the pieces of data needs to be the name of the person (step 121 ), since two people with different names are almost never the same people. However, name matching alone is not good enough, since many different people in world share the same name. Thus, supporting evidence needs to be found.
  • [0156]
    At step 123, if the two records 16 of people with the same name are found working for the same company (organization), either currently or in the past, the records 16 are assumed to be of the same person and therefore combined (at 140). This is almost always safe for smaller companies. For very large companies, it is possible that there are two people with the same name working there. However, the chances that both of these people are mentioned on the web and found by the system 40 reduce the chances that this situation will actually be encountered. Thus, while this process potentially may introduce a small amount of erroneous combinations, the vast majority will be correct.
  • [0157]
    If a match on company names is not found at step 123, titles are used (at step 125) to determine whether subject records 16 of people information should be combined. In this case, if two records 16 of people with the same name are found to have the same title, it is possible to combine the subject records 16. This cannot be done blindly, since it is entirely possible that there are two people named “John Smith” with the title of “Product Manager” in the world. So after step 125 detecting same title, step 127 determines statisical rarity of the title indication shared by the two subject records 16. The database 45 itself may be used to determine statistics of the frequency of titles. Titles that appear very common, such as “Product Manager”, would not be combined on, but a relatively rare title, such as “Patent Clerk”, would be combined on (at 140), since the chances of two people with the same name and that particular title are very low. Thus, while this will also generate some erroneous combinations, the vast majority will still be correct.
  • [0158]
    Statistics on names may also be used when combining on a name-title match (step 129). For example, if a relatively rare name, such as “Geoffrey Westerchest” was encountered for two separate records 16, the chances that they are the same person are higher, because there are fewer people out there with that name. Thus, how rare a title needs to be might be relaxed in that case. In other words, while it is quite possible that two different instances of “John Smith, Product Manager” are two different people, it is unlikely that two instances of “Geoffrey Westerchest, Product Manager” are different people. Thus, at step 140, Integrator 49 combines records 16 corresponding to these two Geoffreys, i.e., statistically rare name, but not so rare/uncommon title determined at step 129.
  • [0159]
    Now that the data is completely integrated, connected pieces of information can be used to interpolate missing data by post-processor 51 (FIG. 1). An example of this is using the email addresses of one or two people at an organization to compute email addresses for the other people in the organization.
  • [0160]
    Whenever a person is associated with an organization, post-processor 51 attempts to identify an email address for that person. Most sites will list an email address for at least one of the people in the organization, or at the very least a generic email for the site (i.e. sales@corex.com) revealing the domain name used for sending emails, which in some cases might be different than the domain name of the site. As soon as a single email address is found, post-processor 51 deduces email addresses for the rest of the people at the organization as follows and illustrated in FIG. 3.
  • [0161]
    Most organizations have a standard format for their email addresses based on name of a person. From one found/extracted email address of a person at a given organization, post-processor 51 reverse engineers the organization's standard format for email addresses at step 101. At step 103, the preferred algorithm searches for substrings of the known/given person's name within the given email address. For example, if the name is Dexter Sealy, and his given email address is desealy~corex.com, the last name is completely contained within the email address, and the given email address starts with the first two letters of the corresponding person's (Dexter's) first name. So two patterns are identified (step 105 ): {first name: 1st 2characters} {last name}@corex.com and {first name: 1st 2characters} {last name: 1st 5 characters}@corex.com. From the identified patterns, step 107 forms and applies rules to database records 16 that indicate people at the given organization whose email addresses are missing from the records 16.
  • [0162]
    Accordingly, the people at the given organization whose records 16 do not indicate respective email addresses have these rules applied to their names, as indicated in the name fields of records 16. As a result, in the foregoing example, from the name Jeremy Rothman-Shore in a record 16 name field, the candidate or potential email addresses jerothm@corex.com, and jerothman-shore@corex.com are produced (output) at step 107 of post-processor 51.
  • [0163]
    In the event that there is no person's email address from which to reverse engineer the company standard email address format and interpolate (generate) email addresses for others at the given company/organization (at 113, FIG. 3), or the reverse engineering process fails (some people have emails that do not follow the organization standard email address format) after step 107, the post-processing routine 51 applies preferred rules 111 of the most common combinations for creating an email address. Such common combinations include:
  • [0164]
    {first}. {last}@{server name}
  • [0165]
    {last} {server name}
  • [0166]
    {first x letters of last name}@{server name}
  • [0167]
    {1 st letter of firstname}{lastname}@{server name}
  • [0168]
    {lastname}{1st letter of firstname}@{server name}
  • [0169]
    . . . etc . . .
  • [0170]
    In addition, most email servers will try to alias email addresses to someone in the organization and forward on the message, even if the message originally used an incorrect email address. For example, many email servers will accept an email address in the form of {first name}_{last name}@{server name} and send it to the appropriate person.
  • [0171]
    In order to verify the interpolated/generated email addresses, step 115 sends a test or email message using a candidate generated email address, out to the person from post processor 51/invention system 40. If the first tested candidate email address is incorrect, an unrecognized recipient reply will be sent back from the mail server to system 40 (host server 27). In such a case, post-processor 51 tries another candidate or an alternate variant of the email address at test step 115 until either a mail delivery acknowledgment is received or no error reply comes back. A unique code may be embedded in the subject field of each trial to simplify matching it with the delivery acknowledgment or error message.
  • [0172]
    While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.
  • [0173]
    For example, reference is made to the Internet and Web sites thereon. The present invention may be applied to other global computer networks and is not dependant on the web platform or HTTP protocol, and the like.
  • [0174]
    The terms “company” and “organization” are used to refer to a variety of entities and/or employers such as businesses, associations, societies, governmental bodies, clubs and the like. Hence association with anyone of these entities is generically termed “employment” or business/non-personal relations to and is intended to cover any affiliation, membership, or connection a person has with the corresponding entity. That is, the terms “employer” and “employed by” are to be given a more generic interpretation liken to non-personal/business affairs of a person. Similarly the term “business email address” is intended to distinguish from a personal, private, at-home email address of a person, but may correspond to any of the variety of entities noted above.

Claims (23)

    What is claimed is:
  1. 1. A method for generating business e-mail address of a person comprising the steps of:
    providing a database storing information regarding people, the database including for each person at least name of the person and the name of respective employer for which the person is currently employed; and
    using digital processor means coupled to the database, automatically generating e-mail address of a subject person named in the database, the e-mail address being with respect to a respective organization named in the database for the subject person.
  2. 2. A method as claimed in claim 1 wherein the step of using digital processor means and automatically generating e-mail address includes:
    obtaining a working e-mail address to the respective organization, the working e-mail address not being the e-mail address of the subject person;
    deducing from the working e-mail address, format of e-mail addresses to the respective organization;
    using the deduced information, constructing potential e-mail addresses for the subject person; and
    verifying each constructed potential e-mail address by testing each, such that at least one verified constructed potential e-mail address provides a business e-mail address of the subject person.
  3. 3. A method as claimed in claim 2 further comprising the step of using predefined common email address formats, constructing potential email addresses for the subject person.
  4. 4. A method as claimed in claim 1 wherein the step of providing a database includes using crawler means, automatically extracting information regarding people and/or organizations from sites of a global computer network and storing the extracted information in the database, such that the database is formed by automated means.
  5. 5. A method as claimed in claim 4 wherein the step of using crawler means includes employing a multiplicity of crawlers under control of a distributor.
  6. 6. A system for generating business e-mail address of a person comprising:
    a database storing information regarding people, the database including for each person at least name of the person and the name of respective employer for which the person is currently employed; and
    digital processor means coupled to the database for automatically generating an e-mail address of a subject person named in the database, the e-mail address being with respect to a respective organization named in the database for the subject person.
  7. 7. A system as claimed in claim 6 wherein the digital processor means automatically generates the e-mail address by:
    obtaining a working e-mail address to the respective organization, the working e-mail address not being the e-mail address of the subject person;
    deducing from the working e-mail address, format of e-mail addresses to the respective organization;
    using the deduced information, constructing potential e-mail addresses for the subject person; and
    verifying each constructed potential e-mail address by testing each, such that at least one verified constructed potential e-mail address provides a business e-mail address of the subject person.
  8. 8. A system as claims in claim 7 wherein the digital processor means utilizes predefined common email address formats to further construct potential email addresses for the subject person.
  9. 9. A system as claimed in claim 6 wherein the database is computer generated from crawler means automatically extracting information regarding people and/or organizations from sites of a global computer network and storing the extracted information in the database, such that the database is formed by automated means.
  10. 10. A system as claimed in claim 9 wherein the crawler means includes plural crawlers under control of a distributor.
  11. 11. A computer automated system for mining from a global computer network information on people and organizations comprising:
    a plurality of automated crawlers for traversing sites of a global computer network and retrieving pages that contain information of interest;
    a distributor coupled to the crawlers for controlling crawler processing;
    an extractor responsive to the crawler retrieved pages and extracting information about people and organizations therefrom; the extracted information being stored in a database;
    an integrator coupled to the database for resolving duplicate information and combining related information in the database; and
    a post-processor coupled to the database for analyzing contents of the database and generating missing information therefrom.
  12. 12. A system as claimed in claim 11 wherein the database stores information about a person in a respective record, different records storing different person's information; and
    given two records of potentially a same person, the integrator combines the records if the person's name is the same in the two records and one of organization name and title is the same in the two records.
  13. 13. A system as claimed in claim 12 wherein the integrator further considers statistical rarity of title and person's name in determining whether to combine the two records.
  14. 14. A system as claimed in claim 11 wherein the post-processor generates an email address of a subject person named in the database, the email address being with respect to respective organization named in the database for the subject person.
  15. 15. A system as claimed in claim 14 wherein the postprocessor generates the email address for the subject person by:
    obtaining a working e-mail address to the respective organization, the working e-mail address not being the e-mail address of the subject person;
    deducing from the working e-mail address, format of e-mail addresses to the respective organization;
    using the deduced information, constructing potential e-mail addresses for the subject person; and
    verifying each constructed potential e-mail address by testing each, such that at least one verified constructed potential e-mail address provides a business e-mail address of the subject person.
  16. 16. A system as claims in claim 15 wherein the post-processor further utilized predefined common email address formats to construct potential email addresses for the subject person.
  17. 17. A method for mining, from a global computer network, information on people and organizations, comprising the computer implemented steps of:
    using a plurality of crawlers, traversing sites of a global computer network and retrieving pages that contain information of interest;
    controlling the crawlers with a distributor;
    extracting from the retrieved pages information about people and/or organizations;
    storing the extracted information in a database;
    resolving duplicate information stored in the database; and
    analyzing contents of the database and generating missing information for storage in the database.
  18. 18. A method as claimed in claim 17 wherein the step of resolving duplicates includes combining related information in the database.
  19. 19. A method as claimed in claim 17 wherein:
    the step of storing includes storing information about different people in different records of the database; and
    the step of resolving includes:
    (a) comparing name of a person indicated in one record with name of person indicated in a second record;
    (b) if the person name comparing results in a match, then determining whether one of organization name and title is the same in the one and second records, and
    (c) combining the one and second records when the determining of step (b) finds one of organization name and title to be the same in the one and second records.
  20. 20. A method as claimed in claim 19 further comprising the step of considering statistical rarity of title and person's name.
  21. 21. A method as claimed in claim 17 wherein the step of generating missing information includes generating an email address of a subject person with respect to a respective organization named in the database for the subject person.
  22. 22. A method as claimed in claim 21 wherein the step of generating an email address includes:
    obtaining a working e-mail address to the respective organization, the working e-mail address not being the e-mail address of the subject person;
    deducing from the working e-mail address, format of e-mail addresses to the respective organization;
    using the deduced information, constructing potential e-mail addresses for the subject person; and
    verifying each constructed potential e-mail address by testing each, such that at least one verified constructed potential e-mail address provides a business e-mail address of the subject person.
  23. 23. A method as claimed in claim 22, further comprising the step of using predefined common email address formats, constructing potential email addresses for the subject person.
US09918312 2000-07-31 2001-07-30 Data mining system Abandoned US20020032740A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US22175000 true 2000-07-31 2000-07-31
US09918312 US20020032740A1 (en) 2000-07-31 2001-07-30 Data mining system

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US09918312 US20020032740A1 (en) 2000-07-31 2001-07-30 Data mining system
PCT/US2001/024162 WO2002010989A3 (en) 2000-07-31 2001-07-30 Method for maintaining people and organization information
PCT/US2001/041515 WO2002010968A3 (en) 2000-07-31 2001-07-31 Data mining system
US11436370 US20070027672A1 (en) 2000-07-31 2006-05-18 Computer method and apparatus for extracting data from web pages

Publications (1)

Publication Number Publication Date
US20020032740A1 true true US20020032740A1 (en) 2002-03-14

Family

ID=22829204

Family Applications (7)

Application Number Title Priority Date Filing Date
US09704080 Active 2021-04-17 US6618717B1 (en) 2000-07-31 2000-11-01 Computer method and apparatus for determining content owner of a website
US09703907 Active 2021-07-09 US6778986B1 (en) 2000-07-31 2000-11-01 Computer method and apparatus for determining site type of a web site
US09768869 Active 2022-10-09 US7356761B2 (en) 2000-07-31 2001-01-24 Computer method and apparatus for determining content types of web pages
US09821908 Active 2023-08-04 US6983282B2 (en) 2000-07-31 2001-03-30 Computer method and apparatus for collecting people and organization information from Web sites
US09910169 Active 2024-04-19 US7065483B2 (en) 2000-07-31 2001-07-20 Computer method and apparatus for extracting data from web pages
US09917200 Active 2023-01-26 US7054886B2 (en) 2000-07-31 2001-07-27 Method for maintaining people and organization information
US09918312 Abandoned US20020032740A1 (en) 2000-07-31 2001-07-30 Data mining system

Family Applications Before (6)

Application Number Title Priority Date Filing Date
US09704080 Active 2021-04-17 US6618717B1 (en) 2000-07-31 2000-11-01 Computer method and apparatus for determining content owner of a website
US09703907 Active 2021-07-09 US6778986B1 (en) 2000-07-31 2000-11-01 Computer method and apparatus for determining site type of a web site
US09768869 Active 2022-10-09 US7356761B2 (en) 2000-07-31 2001-01-24 Computer method and apparatus for determining content types of web pages
US09821908 Active 2023-08-04 US6983282B2 (en) 2000-07-31 2001-03-30 Computer method and apparatus for collecting people and organization information from Web sites
US09910169 Active 2024-04-19 US7065483B2 (en) 2000-07-31 2001-07-20 Computer method and apparatus for extracting data from web pages
US09917200 Active 2023-01-26 US7054886B2 (en) 2000-07-31 2001-07-27 Method for maintaining people and organization information

Country Status (2)

Country Link
US (7) US6618717B1 (en)
WO (5) WO2002010957A3 (en)

Cited By (81)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020123985A1 (en) * 2001-02-06 2002-09-05 O'brien Christopher Data mining system, method and apparatus for industrial applications
WO2002075583A1 (en) * 2001-03-20 2002-09-26 Ispheres Corporation A learning automatic data extraction system
US20030005157A1 (en) * 1999-11-26 2003-01-02 Edmon Chung Network address server
US20030028889A1 (en) * 2001-08-03 2003-02-06 Mccoskey John S. Video and digital multimedia aggregator
US20030028896A1 (en) * 2001-08-03 2003-02-06 Swart William D. Video and digital multimedia aggregator remote content crawler
US20030028890A1 (en) * 2001-08-03 2003-02-06 Swart William D. Video and digital multimedia acquisition and delivery system and method
US20030078807A1 (en) * 2001-10-22 2003-04-24 Siemens Medical Solutions Health Services Corporation System for maintaining organization related information for use in supporting organization operation
US20030076342A1 (en) * 2001-10-22 2003-04-24 Siemens Medical Solutions Health Services Corporation User interface system for maintaining organization related information for use in supporting organization operation
US20030212675A1 (en) * 2002-05-08 2003-11-13 International Business Machines Corporation Knowledge-based data mining system
US20030212699A1 (en) * 2002-05-08 2003-11-13 International Business Machines Corporation Data store for knowledge-based data mining system
US20030212649A1 (en) * 2002-05-08 2003-11-13 International Business Machines Corporation Knowledge-based data mining system
US20030218631A1 (en) * 2002-05-21 2003-11-27 Malik Dale W. Caller initiated distinctive presence alerting and auto-response messaging
US20040015554A1 (en) * 2002-07-16 2004-01-22 Brian Wilson Active e-mail filter with challenge-response
US20040133561A1 (en) * 2002-10-02 2004-07-08 Burke Thomas R. System and method for identifying alternate contact information
US20040167886A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Production of role related information from free text sources utilizing thematic caseframes
US20040164961A1 (en) * 2003-02-21 2004-08-26 Debasis Bal Method, system and computer product for continuously monitoring data sources for an event of interest
US20040205342A1 (en) * 2003-01-09 2004-10-14 Roegner Michael W. Method and system for dynamically implementing an enterprise resource policy
US20040215610A1 (en) * 2003-04-22 2004-10-28 Lawson Software, Inc. System and method for extracting and applying business organization information
US20040230417A1 (en) * 2003-05-16 2004-11-18 Achim Kraiss Multi-language support for data mining models
US20040268388A1 (en) * 2003-06-25 2004-12-30 Roegner Michael W. Method and system for dynamically and specifically targeting marketing
US20050021551A1 (en) * 2003-05-29 2005-01-27 Locateplus Corporation Current mailing address identification and verification
US20050033633A1 (en) * 2003-08-04 2005-02-10 Lapasta Douglas G. System and method for evaluating job candidates
US20050097473A1 (en) * 2002-08-19 2005-05-05 Bellsouth Intellectual Property Corporation Redirection of user-initiated distinctive presence alert messages
US20050138129A1 (en) * 2003-12-23 2005-06-23 Maria Adamczyk Methods and systems of responsive messaging
US20050160014A1 (en) * 2004-01-15 2005-07-21 Cairo Inc. Techniques for identifying and comparing local retail prices
US20050198183A1 (en) * 2004-02-23 2005-09-08 Nokia Corporation Methods, apparatus and computer program products for dispatching and prioritizing communication of generic-recipient messages to recipients
US20060026114A1 (en) * 2004-07-28 2006-02-02 Ken Gregoire Data gathering and distribution system
US20060059123A1 (en) * 2004-08-31 2006-03-16 Udo Klein Fuzzy recipient and contact search for email workflow and groupware applications
US20060059122A1 (en) * 2004-08-31 2006-03-16 Udo Klein Applying search engine technology to HCM employee searches
US20060123000A1 (en) * 2004-12-03 2006-06-08 Jonathan Baxter Machine learning system for extracting structured records from web pages and other text sources
US20060167931A1 (en) * 2004-12-21 2006-07-27 Make Sense, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US20060212448A1 (en) * 2005-03-18 2006-09-21 Bogle Phillip L Method and apparatus for ranking candidates
US20060212305A1 (en) * 2005-03-18 2006-09-21 Jobster, Inc. Method and apparatus for ranking candidates using connection information provided by candidates
US20070005566A1 (en) * 2005-06-27 2007-01-04 Make Sence, Inc. Knowledge Correlation Search Engine
US20070078821A1 (en) * 2005-09-30 2007-04-05 Kabushiki Kaisha Toshiba System and method for managing history of plant data
US20070112777A1 (en) * 2005-11-08 2007-05-17 Yahoo! Inc. Identification and automatic propagation of geo-location associations to un-located documents
US20070143415A1 (en) * 2005-12-15 2007-06-21 Daigle Brian K Customizable presence icons for instant messaging
US20070156653A1 (en) * 2005-12-30 2007-07-05 Manish Garg Automated knowledge management system
US20080071796A1 (en) * 2006-09-11 2008-03-20 Ghuneim Mark D System and method for collecting and processing data
US20080071909A1 (en) * 2006-09-14 2008-03-20 Michael Young System and method for facilitating distribution of limited resources
US20080068150A1 (en) * 2006-09-13 2008-03-20 Bellsouth Intellectual Property Corporation Monitoring and entry system presence service
US20080077685A1 (en) * 2006-09-21 2008-03-27 Bellsouth Intellectual Property Corporation Dynamically configurable presence service
US20080077696A1 (en) * 2006-09-21 2008-03-27 Bellsouth Intellectual Property Corporation Personal presentity presence subsystem
US20080109411A1 (en) * 2006-10-24 2008-05-08 Michael Young Supply Chain Discovery Services
US20080140626A1 (en) * 2004-04-15 2008-06-12 Jeffery Wilson Method for enabling dynamic websites to be indexed within search engines
US20080147642A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell System for discovering data artifacts in an on-line data object
US20080147641A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method for prioritizing search results retrieved in response to a computerized search query
US20080147588A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method for discovering data artifacts in an on-line data object
US20080147631A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method and system for collecting and retrieving information from web sites
US20080147578A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell System for prioritizing search results retrieved in response to a computerized search query
US7395329B1 (en) 2002-05-13 2008-07-01 At&T Delaware Intellectual Property., Inc. Real-time notification of presence availability changes
US7543016B2 (en) 2003-07-31 2009-06-02 International Business Machines Corporation Method, system and program product for automatically assigning electronic addresses to users
US20090240662A1 (en) * 2008-03-18 2009-09-24 Morgan Christopher B Integration for intelligence data systems
US20110022675A1 (en) * 2008-03-10 2011-01-27 Afilias Limited Platform independent idn e-mail storage translation
US20110035443A1 (en) * 2009-08-04 2011-02-10 At&T Intellectual Property I, L.P. Aggregated Presence Over User Federated Devices
US20110125587A1 (en) * 2008-06-23 2011-05-26 Double Verify, Inc. Automated Monitoring and Verification of Internet Based Advertising
US7991762B1 (en) 2005-06-24 2011-08-02 Google Inc. Managing URLs
US8005870B1 (en) * 2001-06-19 2011-08-23 Microstrategy Incorporated System and method for syntax abstraction in query language generation
US20110225246A1 (en) * 2010-03-10 2011-09-15 Afilias Limited Alternate e-mail delivery
US20110282909A1 (en) * 2008-10-17 2011-11-17 Intuit Inc. Secregating anonymous access to dynamic content on a web server, with cached logons
US8068986B1 (en) 2007-04-27 2011-11-29 Majid Shahbazi Methods and apparatus related to sensor signal sniffing and/or analysis
US20110314109A1 (en) * 2008-03-10 2011-12-22 Afilias Limited Alternate e-mail address configuration
US8108389B2 (en) 2004-11-12 2012-01-31 Make Sence, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
FR2966949A1 (en) * 2010-11-02 2012-05-04 Beetween Method for automating creation of structured database, involves removing pages whose probability indicator is less than threshold value, and processing non-isolated pages to determine information that is not directly accessible
US8260619B1 (en) 2008-08-22 2012-09-04 Convergys Cmg Utah, Inc. Method and system for creating natural language understanding grammars
US20120265744A1 (en) * 2001-08-08 2012-10-18 Gary Charles Berkowitz Knowledge-based e-catalog procurement system and method
US8386459B1 (en) 2005-04-25 2013-02-26 Google Inc. Scheduling a recrawl
US20130212468A1 (en) * 2005-11-01 2013-08-15 At&T Intellectual Property Ii, L.P. Alert Driven Interactive Interface to a Website Mining System
US20130290828A1 (en) * 2012-04-30 2013-10-31 Clipboard Inc. Extracting a portion of a document, such as a web page
US8578410B2 (en) 2001-08-03 2013-11-05 Comcast Ip Holdings, I, Llc Video and digital multimedia aggregator content coding and formatting
US8666964B1 (en) * 2005-04-25 2014-03-04 Google Inc. Managing items in crawl schedule
US8898134B2 (en) 2005-06-27 2014-11-25 Make Sence, Inc. Method for ranking resources using node pool
US9021039B2 (en) 2002-07-16 2015-04-28 Sonicwall, Inc. Message challenge response
US9078014B2 (en) 2000-06-19 2015-07-07 Comcast Ip Holdings I, Llc Method and apparatus for targeting of interactive virtual objects
US9215198B2 (en) 2002-07-16 2015-12-15 Dell Software Inc. Efficient use of resources in message classification
US9213689B2 (en) 2005-11-14 2015-12-15 Make Sence, Inc. Techniques for creating computer generated notes
US9286294B2 (en) 1992-12-09 2016-03-15 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator content suggestion engine
US9330093B1 (en) * 2012-08-02 2016-05-03 Google Inc. Methods and systems for identifying user input data for matching content to user interests
US9330175B2 (en) 2004-11-12 2016-05-03 Make Sence, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US9342608B2 (en) 2013-08-01 2016-05-17 International Business Machines Corporation Clarification of submitted questions in a question and answer system
US9900297B2 (en) 2007-01-25 2018-02-20 Salesforce.Com, Inc. System, method and apparatus for selecting content from web sources and posting content to web logs

Families Citing this family (343)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8352400B2 (en) 1991-12-23 2013-01-08 Hoffberg Steven M Adaptive pattern recognition based controller apparatus and method and human-factored interface therefore
US7904187B2 (en) 1999-02-01 2011-03-08 Hoffberg Steven M Internet appliance system and method
JP3841233B2 (en) * 1996-12-18 2006-11-01 ソニー株式会社 Information processing apparatus and information processing method
WO2001018636A1 (en) * 1999-09-09 2001-03-15 American Express Travel Related Services Company, Inc. System and method for authenticating a web page
US9843447B1 (en) 1999-09-09 2017-12-12 Secure Axcess Llc Authenticating electronic content
US7203838B1 (en) 1999-09-09 2007-04-10 American Express Travel Related Services Company, Inc. System and method for authenticating a web page
KR100357098B1 (en) * 1999-11-12 2002-10-19 엘지전자 주식회사 apparatus and method for display of data information in data broadcasting reciever
US20010049707A1 (en) 2000-02-29 2001-12-06 Tran Bao Q. Systems and methods for generating intellectual property
EP1309927A2 (en) * 2000-03-27 2003-05-14 Documentum, Inc. Method and apparatus for generating metadata for a document
US6666377B1 (en) 2000-07-18 2003-12-23 Scott C. Harris Bar code data entry device
US20070027672A1 (en) * 2000-07-31 2007-02-01 Michel Decary Computer method and apparatus for extracting data from web pages
US6618717B1 (en) * 2000-07-31 2003-09-09 Eliyon Technologies Corporation Computer method and apparatus for determining content owner of a website
JP2002171232A (en) * 2000-08-01 2002-06-14 Matsushita Electric Ind Co Ltd Transmitting and receiving system and transmitter/ receiver
US6957224B1 (en) * 2000-09-11 2005-10-18 International Business Machines Corporation Efficient retrieval of uniform resource locators
US8122236B2 (en) 2001-10-24 2012-02-21 Aol Inc. Method of disseminating advertisements using an embedded media player page
EP1350392B1 (en) 2000-10-24 2009-01-14 Aol Llc Method of sizing an embedded media player page
FR2816157A1 (en) * 2000-10-31 2002-05-03 Thomson Multimedia Sa Method for processing video data distinees for viewing on screen and device embodying the METHOD
US8060816B1 (en) * 2000-10-31 2011-11-15 International Business Machines Corporation Methods and apparatus for intelligent crawling on the world wide web
DE10194867D2 (en) 2000-11-08 2003-11-20 Willytec Gmbh Technologiezentr (Dental) surface mapping and generation
US20040030683A1 (en) * 2000-11-21 2004-02-12 Evans Philip Clark System and process for mediated crawling
US20040064500A1 (en) * 2001-11-20 2004-04-01 Kolar Jennifer Lynn System and method for unified extraction of media objects
US20020103920A1 (en) 2000-11-21 2002-08-01 Berkun Ken Alan Interpretive stream metadata extraction
US7043473B1 (en) * 2000-11-22 2006-05-09 Widevine Technologies, Inc. Media tracking system and method
US8230323B2 (en) * 2000-12-06 2012-07-24 Sra International, Inc. Content distribution system and method
WO2002093334A3 (en) * 2001-04-06 2003-11-13 Symantec Corp Temporal access control for computer virus outbreaks
US7197506B2 (en) * 2001-04-06 2007-03-27 Renar Company, Llc Collection management system
US20020198859A1 (en) * 2001-06-22 2002-12-26 International Business Machines Corporation Method and system for providing web links
CN1167027C (en) * 2001-08-03 2004-09-15 富士通株式会社 Format file information extracting device and method
US20030061232A1 (en) * 2001-09-21 2003-03-27 Dun & Bradstreet Inc. Method and system for processing business data
US7788111B2 (en) * 2001-10-22 2010-08-31 Siemens Medical Solutions Usa, Inc. System for providing healthcare related information
US7437302B2 (en) * 2001-10-22 2008-10-14 Siemens Medical Solutions Usa, Inc. System for managing healthcare related information supporting operation of a healthcare enterprise
US20050010556A1 (en) * 2002-11-27 2005-01-13 Kathleen Phelan Method and apparatus for information retrieval
US7194464B2 (en) 2001-12-07 2007-03-20 Websense, Inc. System and method for adapting an internet filter
US7333966B2 (en) 2001-12-21 2008-02-19 Thomson Global Resources Systems, methods, and software for hyperlinking names
EP1466435A4 (en) 2002-01-08 2011-05-18 Seven Networks Inc Secure transport for mobile communication network
US7284195B2 (en) * 2002-01-31 2007-10-16 International Business Machines Corporation Structure and method for linking within a website
US7228335B2 (en) * 2002-02-19 2007-06-05 Goodcontacts Research Ltd. Method of automatically populating contact information fields for a new contract added to an electronic contact database
US6856679B2 (en) * 2002-05-01 2005-02-15 Sbc Services Inc. System and method to provide automated scripting for customer service representatives
US20040205484A1 (en) * 2002-05-01 2004-10-14 Pennington Stanford E. System and method for dynamically generating customized pages
US7367056B1 (en) 2002-06-04 2008-04-29 Symantec Corporation Countering malicious code infections to computer files that have been infected more than once
US7165068B2 (en) * 2002-06-12 2007-01-16 Zycus Infotech Pvt Ltd. System and method for electronic catalog classification using a hybrid of rule based and statistical method
US7496636B2 (en) * 2002-06-19 2009-02-24 International Business Machines Corporation Method and system for resolving Universal Resource Locators (URLs) from script code
US20060190561A1 (en) * 2002-06-19 2006-08-24 Watchfire Corporation Method and system for obtaining script related information for website crawling
US7228496B2 (en) * 2002-07-09 2007-06-05 Kabushiki Kaisha Toshiba Document editing method, document editing system, server apparatus, and document editing program
US7478121B1 (en) * 2002-07-31 2009-01-13 Opinionlab, Inc. Receiving and reporting page-specific user feedback concerning one or more particular web pages of a website
US7370285B1 (en) 2002-07-31 2008-05-06 Opinionlab, Inc. Receiving and reporting page-specific user feedback concerning one or more particular web pages of a website
US20040044734A1 (en) * 2002-08-27 2004-03-04 Mark Beck Enhanced services electronic mail
US7365221B2 (en) * 2002-09-26 2008-04-29 Panacos Pharmaceuticals, Inc. Monoacylated betulin and dihydrobetulin derivatives, preparation thereof and use thereof
US7337471B2 (en) * 2002-10-07 2008-02-26 Symantec Corporation Selective detection of malicious computer code
US7469419B2 (en) 2002-10-07 2008-12-23 Symantec Corporation Detection of malicious computer code
US7260847B2 (en) * 2002-10-24 2007-08-21 Symantec Corporation Antivirus scanning in a hard-linked environment
US7249187B2 (en) 2002-11-27 2007-07-24 Symantec Corporation Enforcement of compliance with network security policies
US7373664B2 (en) * 2002-12-16 2008-05-13 Symantec Corporation Proactive protection against e-mail worms and spam
US7293290B2 (en) 2003-02-06 2007-11-06 Symantec Corporation Dynamic detection of computer worms
US20040158546A1 (en) * 2003-02-06 2004-08-12 Sobel William E. Integrity checking for software downloaded from untrusted sources
US7246227B2 (en) * 2003-02-10 2007-07-17 Symantec Corporation Efficient scanning of stream based data
US7203959B2 (en) 2003-03-14 2007-04-10 Symantec Corporation Stream scanning through network proxy servers
US7546638B2 (en) 2003-03-18 2009-06-09 Symantec Corporation Automated identification and clean-up of malicious computer code
US20050188300A1 (en) * 2003-03-21 2005-08-25 Xerox Corporation Determination of member pages for a hyperlinked document with link and document analysis
US20040237037A1 (en) * 2003-03-21 2004-11-25 Xerox Corporation Determination of member pages for a hyperlinked document with recursive page-level link analysis
US7305612B2 (en) * 2003-03-31 2007-12-04 Siemens Corporate Research, Inc. Systems and methods for automatic form segmentation for raster-based passive electronic documents
JP2004303160A (en) * 2003-04-01 2004-10-28 Oki Electric Ind Co Ltd Information extracting device
US7680886B1 (en) 2003-04-09 2010-03-16 Symantec Corporation Suppressing spam using a machine learning based spam filter
US7650382B1 (en) 2003-04-24 2010-01-19 Symantec Corporation Detecting spam e-mail with backup e-mail server traps
US7739494B1 (en) 2003-04-25 2010-06-15 Symantec Corporation SSL validation and stripping using trustworthiness factors
US7366919B1 (en) 2003-04-25 2008-04-29 Symantec Corporation Use of geo-location data for spam detection
US7600001B1 (en) * 2003-05-01 2009-10-06 Vignette Corporation Method and computer system for unstructured data integration through a graphical interface
US7293063B1 (en) 2003-06-04 2007-11-06 Symantec Corporation System utilizing updated spam signatures for performing secondary signature-based analysis of a held e-mail to improve spam email detection
US7827487B1 (en) 2003-06-16 2010-11-02 Opinionlab, Inc. Soliciting user feedback regarding one or more web pages of a website without obscuring visual content
US8707312B1 (en) 2003-07-03 2014-04-22 Google Inc. Document reuse in a search engine crawler
US7725452B1 (en) * 2003-07-03 2010-05-25 Google Inc. Scheduler for search engine crawler
US20050027566A1 (en) * 2003-07-09 2005-02-03 Haskell Robert Emmons Terminology management system
US7739278B1 (en) 2003-08-22 2010-06-15 Symantec Corporation Source independent file attribute tracking
JP4174392B2 (en) * 2003-08-28 2008-10-29 Necシステムテクノロジー株式会社 Network unauthorized access preventing system, and network unauthorized access preventing apparatus
US20050060140A1 (en) * 2003-09-15 2005-03-17 Maddox Paul Christopher Using semantic feature structures for document comparisons
US20050076013A1 (en) * 2003-10-01 2005-04-07 Fuji Xerox Co., Ltd. Context-based contact information retrieval systems and methods
US7921159B1 (en) 2003-10-14 2011-04-05 Symantec Corporation Countering spam that uses disguised characters
WO2005050395A3 (en) * 2003-11-18 2005-08-18 Gh Llc Content communication system and methods
US20050149527A1 (en) * 2003-12-31 2005-07-07 Intellipoint International, Llc System and method for uniquely identifying persons
WO2005081116A1 (en) * 2004-01-05 2005-09-01 Yasuo Nishizawa Integrated intelligent seo transaction platform
US20050166137A1 (en) * 2004-01-26 2005-07-28 Bao Tran Systems and methods for analyzing documents
US7761923B2 (en) 2004-03-01 2010-07-20 Invensys Systems, Inc. Process control methods and apparatus for intrusion detection, protection and network hardening
US20050210008A1 (en) * 2004-03-18 2005-09-22 Bao Tran Systems and methods for analyzing documents over a network
US7130981B1 (en) 2004-04-06 2006-10-31 Symantec Corporation Signature driven cache extension for stream based scanning
US7418458B2 (en) * 2004-04-06 2008-08-26 Educational Testing Service Method for estimating examinee attribute parameters in a cognitive diagnosis model
US7519954B1 (en) * 2004-04-08 2009-04-14 Mcafee, Inc. System and method of operating system identification
CA2504118A1 (en) * 2004-04-09 2005-10-09 Opinionlab, Inc. Using software incorporated into a web page to collect page-specific user feedback concerning a document embedded in the web page
US7783476B2 (en) * 2004-05-05 2010-08-24 Microsoft Corporation Word extraction method and system for use in word-breaking using statistical information
US7861304B1 (en) 2004-05-07 2010-12-28 Symantec Corporation Pattern matching using embedded functions
US7373667B1 (en) 2004-05-14 2008-05-13 Symantec Corporation Protecting a computer coupled to a network from malicious code infections
US7484094B1 (en) 2004-05-14 2009-01-27 Symantec Corporation Opening computer files quickly and safely over a network
US8181112B2 (en) * 2004-05-21 2012-05-15 Oracle International Corporation Independent portlet rendering
US8719142B1 (en) 2004-06-16 2014-05-06 Gary Odom Seller categorization
JP4583218B2 (en) * 2004-07-05 2010-11-17 インターナショナル・ビジネス・マシーンズ・コーポレーションInternational Business Maschines Corporation Method of evaluating a target content, computer programs, system
US7996462B2 (en) * 2004-07-30 2011-08-09 Sap Ag Collaborative agent for a work environment
JP2006053745A (en) * 2004-08-11 2006-02-23 Saora Inc Data processing method, device and program
JP4350001B2 (en) * 2004-08-17 2009-10-21 富士通株式会社 Page information collection program, page information collection method, and page information collection apparatus
US7987172B1 (en) 2004-08-30 2011-07-26 Google Inc. Minimizing visibility of stale content in web searching including revising web crawl intervals of documents
US8244726B1 (en) 2004-08-31 2012-08-14 Bruce Matesso Computer-aided extraction of semantics from keywords to confirm match of buyer offers to seller bids
US20060047690A1 (en) * 2004-08-31 2006-03-02 Microsoft Corporation Integration of Flex and Yacc into a linguistic services platform for named entity recognition
US20060047691A1 (en) * 2004-08-31 2006-03-02 Microsoft Corporation Creating a document index from a flex- and Yacc-generated named entity recognizer
US20060047500A1 (en) * 2004-08-31 2006-03-02 Microsoft Corporation Named entity recognition using compiler methods
US7509680B1 (en) 2004-09-01 2009-03-24 Symantec Corporation Detecting computer worms as they arrive at local computers through open network shares
US7490244B1 (en) 2004-09-14 2009-02-10 Symantec Corporation Blocking e-mail propagation of suspected malicious computer code
US7555524B1 (en) 2004-09-16 2009-06-30 Symantec Corporation Bulk electronic message detection by header similarity analysis
US7620996B2 (en) * 2004-11-01 2009-11-17 Microsoft Corporation Dynamic summary module
US7546349B1 (en) 2004-11-01 2009-06-09 Symantec Corporation Automatic generation of disposable e-mail addresses
US8090776B2 (en) * 2004-11-01 2012-01-03 Microsoft Corporation Dynamic content change notification
US7565686B1 (en) 2004-11-08 2009-07-21 Symantec Corporation Preventing unauthorized loading of late binding code into a process
US7584194B2 (en) * 2004-11-22 2009-09-01 Truveo, Inc. Method and apparatus for an application crawler
CN101443751A (en) 2004-11-22 2009-05-27 特鲁维奥公司 Method and apparatus for an application crawler
US7370381B2 (en) * 2004-11-22 2008-05-13 Truveo, Inc. Method and apparatus for a ranking engine
US7634810B2 (en) * 2004-12-02 2009-12-15 Microsoft Corporation Phishing detection, prevention, and notification
US20060123478A1 (en) * 2004-12-02 2006-06-08 Microsoft Corporation Phishing detection, prevention, and notification
US7428491B2 (en) * 2004-12-10 2008-09-23 Microsoft Corporation Method and system for obtaining personal aliases through voice recognition
US7640590B1 (en) 2004-12-21 2009-12-29 Symantec Corporation Presentation of network source and executable characteristics
US20060168046A1 (en) * 2005-01-11 2006-07-27 Microsoft Corporaion Managing periodic electronic messages
WO2006081307A2 (en) * 2005-01-25 2006-08-03 Aureon Laboratories, Inc. Methods and systems for induction and use of probabilistic patterns to support decisions under uncertainty
DE102005016815A1 (en) * 2005-04-07 2006-10-12 Deutsche Telekom Ag A method of operating, in particular for creating a database
US20060229184A1 (en) * 2005-04-07 2006-10-12 Hewlett-Packard Development Company, L.P. Creaser
US8438633B1 (en) 2005-04-21 2013-05-07 Seven Networks, Inc. Flexible real-time inbox access
US8630996B2 (en) * 2005-05-05 2014-01-14 At&T Intellectual Property I, L.P. Identifying duplicate entries in a historical database
US20060265368A1 (en) * 2005-05-23 2006-11-23 Opinionlab, Inc. Measuring subjective user reaction concerning a particular document
JP4772378B2 (en) * 2005-05-26 2011-09-14 株式会社東芝 A method and apparatus for generating time-series data from a Web page
US7801881B1 (en) * 2005-05-31 2010-09-21 Google Inc. Sitemap generating client for web crawler
US7769742B1 (en) * 2005-05-31 2010-08-03 Google Inc. Web crawler scheduler that utilizes sitemaps from websites
US7725476B2 (en) 2005-06-14 2010-05-25 International Business Machines Corporation System and method for automated data retrieval based on data placed in clipboard memory
US8768911B2 (en) * 2005-06-15 2014-07-01 Geronimo Development System and method for indexing and displaying document text that has been subsequently quoted
US8805781B2 (en) * 2005-06-15 2014-08-12 Geronimo Development Document quotation indexing system and method
US20060287767A1 (en) * 2005-06-20 2006-12-21 Kraft Harold H Privacy Information Reporting Systems with Refined Information Presentation Model
WO2006136660A1 (en) 2005-06-21 2006-12-28 Seven Networks International Oy Maintaining an ip connection in a mobile network
GB0512744D0 (en) * 2005-06-22 2005-07-27 Blackspider Technologies Method and system for filtering electronic messages
US7895654B1 (en) 2005-06-27 2011-02-22 Symantec Corporation Efficient file scanning using secure listing of file modification times
US7975303B1 (en) 2005-06-27 2011-07-05 Symantec Corporation Efficient file scanning using input-output hints
US7652112B2 (en) * 2005-07-06 2010-01-26 E.I. Du Pont De Nemours And Company Polymeric extenders for surface effects
US7669119B1 (en) * 2005-07-20 2010-02-23 Alexa Internet Correlation-based information extraction from markup language documents
US8468126B2 (en) 2005-08-01 2013-06-18 Seven Networks, Inc. Publishing data in an information community
US7917468B2 (en) 2005-08-01 2011-03-29 Seven Networks, Inc. Linking of personal information management data
US8069166B2 (en) * 2005-08-01 2011-11-29 Seven Networks, Inc. Managing user-to-user contact with inferred presence information
US7565358B2 (en) 2005-08-08 2009-07-21 Google Inc. Agent rank
US7653617B2 (en) * 2005-08-29 2010-01-26 Google Inc. Mobile sitemaps
JPWO2007029348A1 (en) 2005-09-06 2009-03-12 コミュニティーエンジン株式会社 Data extraction system, a terminal device, a program of the terminal device, a server device, and a server apparatus program
US7672833B2 (en) * 2005-09-22 2010-03-02 Fair Isaac Corporation Method and apparatus for automatic entity disambiguation
WO2007038713A3 (en) * 2005-09-28 2008-02-14 Epacris Inc Search engine determining results based on probabilistic scoring of relevance
US7849093B2 (en) * 2005-10-14 2010-12-07 Microsoft Corporation Searches over a collection of items through classification and display of media galleries
US20070118607A1 (en) * 2005-11-22 2007-05-24 Niko Nelissen Method and System for forensic investigation of internet resources
US7949646B1 (en) 2005-12-23 2011-05-24 At&T Intellectual Property Ii, L.P. Method and apparatus for building sales tools by mining data from websites
US7831382B2 (en) * 2006-02-01 2010-11-09 TeleAtlas B.V. Method for differentiating duplicate or similarly named disjoint localities within a state or other principal geographic unit of interest
US7945533B2 (en) * 2006-03-01 2011-05-17 Oracle International Corp. Index replication using crawl modification information
US7475069B2 (en) * 2006-03-29 2009-01-06 International Business Machines Corporation System and method for prioritizing websites during a webcrawling process
US7860857B2 (en) * 2006-03-30 2010-12-28 Invensys Systems, Inc. Digital data processing apparatus and methods for improving plant performance
US9390422B2 (en) * 2006-03-30 2016-07-12 Geographic Solutions, Inc. System, method and computer program products for creating and maintaining a consolidated jobs database
US7735010B2 (en) 2006-04-05 2010-06-08 Lexisnexis, A Division Of Reed Elsevier Inc. Citation network viewer and method
US20070255675A1 (en) * 2006-04-26 2007-11-01 Jacquelyn Fuzell-Casey Auto-updating, web-accessible database to facilitate networking and resource management
US7603350B1 (en) 2006-05-09 2009-10-13 Google Inc. Search result ranking based on trust
US9507778B2 (en) 2006-05-19 2016-11-29 Yahoo! Inc. Summarization of media object collections
US20070294646A1 (en) * 2006-06-14 2007-12-20 Sybase, Inc. System and Method for Delivering Mobile RSS Content
US7769395B2 (en) 2006-06-20 2010-08-03 Seven Networks, Inc. Location-based operations and messaging
US8090658B2 (en) * 2006-06-23 2012-01-03 International Business Machines Corporation System and method of member unique names
US8332947B1 (en) 2006-06-27 2012-12-11 Symantec Corporation Security threat reporting in light of local security tools
US8239915B1 (en) 2006-06-30 2012-08-07 Symantec Corporation Endpoint management using trust rating data
US8615800B2 (en) 2006-07-10 2013-12-24 Websense, Inc. System and method for analyzing web content
US8020206B2 (en) 2006-07-10 2011-09-13 Websense, Inc. System and method of analyzing web content
US9633356B2 (en) 2006-07-20 2017-04-25 Aol Inc. Targeted advertising for playlists based upon search queries
US8775237B2 (en) 2006-08-02 2014-07-08 Opinionlab, Inc. System and method for measuring and reporting user reactions to advertisements on a web page
US9547648B2 (en) * 2006-08-03 2017-01-17 Excalibur Ip, Llc Electronic document information extraction
US8533226B1 (en) 2006-08-04 2013-09-10 Google Inc. System and method for verifying and revoking ownership rights with respect to a website in a website indexing system
US7930400B1 (en) 2006-08-04 2011-04-19 Google Inc. System and method for managing multiple domain names for a website in a website indexing system
US8190868B2 (en) 2006-08-07 2012-05-29 Webroot Inc. Malware management through kernel detection
US20080040352A1 (en) * 2006-08-08 2008-02-14 Kenneth Alexander Ellis Method for creating a disambiguation database
US7689682B1 (en) 2006-08-16 2010-03-30 Resource Consortium Limited Obtaining lists of nodes of a multi-dimensional network
US8930204B1 (en) 2006-08-16 2015-01-06 Resource Consortium Limited Determining lifestyle recommendations using aggregated personal information
US7809602B2 (en) * 2006-08-31 2010-10-05 Opinionlab, Inc. Computer-implemented system and method for measuring and reporting business intelligence based on comments collected from web page users using software associated with accessed web pages
GB0624667D0 (en) * 2006-09-07 2007-01-17 Fujin Technology Plc Structural analysis
US7685201B2 (en) * 2006-09-08 2010-03-23 Microsoft Corporation Person disambiguation using name entity extraction-based clustering
US8099415B2 (en) * 2006-09-08 2012-01-17 Simply Hired, Inc. Method and apparatus for assessing similarity between online job listings
DE502006009446D1 (en) * 2006-09-13 2011-06-16 Ivoclar Vivadent Ag Multicolored moldings
US8554638B2 (en) * 2006-09-29 2013-10-08 Microsoft Corporation Comparative shopping tool
US7599920B1 (en) 2006-10-12 2009-10-06 Google Inc. System and method for enabling website owners to manage crawl rate in a website indexing system
US8594702B2 (en) 2006-11-06 2013-11-26 Yahoo! Inc. Context server for associating information based on context
US9110903B2 (en) 2006-11-22 2015-08-18 Yahoo! Inc. Method, system and apparatus for using user profile electronic device data in media delivery
US8402356B2 (en) 2006-11-22 2013-03-19 Yahoo! Inc. Methods, systems and apparatus for delivery of media
US9654495B2 (en) 2006-12-01 2017-05-16 Websense, Llc System and method of analyzing web addresses
US20080133676A1 (en) * 2006-12-01 2008-06-05 John Choisser Method and system for providing email
US20080141110A1 (en) * 2006-12-07 2008-06-12 Picscout (Israel) Ltd. Hot-linked images and methods and an apparatus for adapting existing images for the same
DE102006061143A1 (en) * 2006-12-22 2008-07-24 Aepsilon Rechteverwaltungs Gmbh A method, computer readable medium and computer concerning the production of dental prostheses
DE102006061134A1 (en) * 2006-12-22 2008-06-26 Aepsilon Rechteverwaltungs Gmbh Procedures concerning the transport of dental prostheses
RU2313825C1 (en) * 2006-12-26 2007-12-27 Малышев Павел Михайлович Automated method for transformation of a series of computer codes adequate for information requested by user and automated complex for realization of the method
US8769099B2 (en) 2006-12-28 2014-07-01 Yahoo! Inc. Methods and systems for pre-caching information on a mobile computing device
US20080071886A1 (en) * 2006-12-29 2008-03-20 Wesley Scott Ashton Method and system for internet search
GB0700339D0 (en) 2007-01-09 2007-02-14 Surfcontrol On Demand Ltd A method and system for collecting addresses for remotely accessible information sources
US7860872B2 (en) * 2007-01-29 2010-12-28 Nikip Technology Ltd. Automated media analysis and document management system
US7693833B2 (en) * 2007-02-01 2010-04-06 John Nagle System and method for improving integrity of internet search
US7895515B1 (en) * 2007-02-28 2011-02-22 Trend Micro Inc Detecting indicators of misleading content in markup language coded documents using the formatting of the document
US20080235213A1 (en) * 2007-03-20 2008-09-25 Picscout (Israel) Ltd. Utilization of copyright media in second generation web content
US20080281827A1 (en) * 2007-05-10 2008-11-13 Microsoft Corporation Using structured database for webpage information extraction
GB0709527D0 (en) 2007-05-18 2007-06-27 Surfcontrol Plc Electronic messaging system, message processing apparatus and message processing method
US8805425B2 (en) 2007-06-01 2014-08-12 Seven Networks, Inc. Integrated messaging
US20090037412A1 (en) * 2007-07-02 2009-02-05 Kristina Butvydas Bard Qualitative search engine based on factors of consumer trust specification
US8321359B2 (en) * 2007-07-24 2012-11-27 Hiconversion, Inc. Method and apparatus for real-time website optimization
US20120166414A1 (en) * 2008-08-11 2012-06-28 Ultra Unilimited Corporation (dba Publish) Systems and methods for relevance scoring
WO2009032814A3 (en) * 2007-09-04 2009-05-07 Craig Mitnick System and method for collecting and organizing popular near real-time data in a virtual geographic grid
US20090070419A1 (en) * 2007-09-11 2009-03-12 International Business Machines Corporation Administering Feeds Of Presence Information Of One Or More Presentities
US20090070410A1 (en) * 2007-09-12 2009-03-12 International Business Machines Corporation Managing Presence Information Of A Presentity
CN101855632B (en) * 2007-11-08 2013-10-30 上海惠普有限公司 URL and anchor text analysis for focused crawling
US8069142B2 (en) 2007-12-06 2011-11-29 Yahoo! Inc. System and method for synchronizing data on a network
US8671154B2 (en) 2007-12-10 2014-03-11 Yahoo! Inc. System and method for contextual addressing of communications on a network
US8364181B2 (en) 2007-12-10 2013-01-29 Seven Networks, Inc. Electronic-mail filtering for mobile devices
US8307029B2 (en) 2007-12-10 2012-11-06 Yahoo! Inc. System and method for conditional delivery of messages
US9002828B2 (en) 2007-12-13 2015-04-07 Seven Networks, Inc. Predictive content delivery
US8166168B2 (en) 2007-12-17 2012-04-24 Yahoo! Inc. System and method for disambiguating non-unique identifiers using information obtained from disparate communication channels
US9706345B2 (en) 2008-01-04 2017-07-11 Excalibur Ip, Llc Interest mapping system
US9626685B2 (en) 2008-01-04 2017-04-18 Excalibur Ip, Llc Systems and methods of mapping attention
US8762285B2 (en) 2008-01-06 2014-06-24 Yahoo! Inc. System and method for message clustering
US8862657B2 (en) 2008-01-25 2014-10-14 Seven Networks, Inc. Policy based content service
US20090193338A1 (en) 2008-01-28 2009-07-30 Trevor Fiatal Reducing network and battery consumption during content delivery and playback
US8583639B2 (en) * 2008-02-19 2013-11-12 International Business Machines Corporation Method and system using machine learning to automatically discover home pages on the internet
US8554623B2 (en) 2008-03-03 2013-10-08 Yahoo! Inc. Method and apparatus for social network marketing with consumer referral
US8560390B2 (en) 2008-03-03 2013-10-15 Yahoo! Inc. Method and apparatus for social network marketing with brand referral
US8538811B2 (en) 2008-03-03 2013-09-17 Yahoo! Inc. Method and apparatus for social network marketing with advocate referral
US7865455B2 (en) * 2008-03-13 2011-01-04 Opinionlab, Inc. System and method for providing intelligent support
US8745133B2 (en) 2008-03-28 2014-06-03 Yahoo! Inc. System and method for optimizing the storage of data
US8589486B2 (en) * 2008-03-28 2013-11-19 Yahoo! Inc. System and method for addressing communications
US20100010993A1 (en) * 2008-03-31 2010-01-14 Hussey Jr Michael P Distributed personal information aggregator
US8271506B2 (en) 2008-03-31 2012-09-18 Yahoo! Inc. System and method for modeling relationships between entities
US20090287641A1 (en) * 2008-05-13 2009-11-19 Eric Rahm Method and system for crawling the world wide web
US8082248B2 (en) * 2008-05-29 2011-12-20 Rania Abouyounes Method and system for document classification based on document structure and written style
US8787947B2 (en) 2008-06-18 2014-07-22 Seven Networks, Inc. Application discovery on mobile devices
US8065310B2 (en) * 2008-06-25 2011-11-22 Microsoft Corporation Topics in relevance ranking model for web search
US8078158B2 (en) 2008-06-26 2011-12-13 Seven Networks, Inc. Provisioning applications for a mobile device
US8706406B2 (en) 2008-06-27 2014-04-22 Yahoo! Inc. System and method for determination and display of personalized distance
US8813107B2 (en) 2008-06-27 2014-08-19 Yahoo! Inc. System and method for location based media delivery
US8214346B2 (en) * 2008-06-27 2012-07-03 Cbs Interactive Inc. Personalization engine for classifying unstructured documents
US8452855B2 (en) 2008-06-27 2013-05-28 Yahoo! Inc. System and method for presentation of media related to a context
EP2318955A1 (en) 2008-06-30 2011-05-11 Websense, Inc. System and method for dynamic and real-time categorization of webpages
US8170974B2 (en) * 2008-07-07 2012-05-01 Yahoo! Inc. Forecasting association rules across user engagement levels
US8273182B2 (en) * 2008-07-15 2012-09-25 WLR Enterprises, LLC Devices and methods for cleaning and drying ice skate blades
US8286171B2 (en) 2008-07-21 2012-10-09 Workshare Technology, Inc. Methods and systems to fingerprint textual information using word runs
US8583668B2 (en) 2008-07-30 2013-11-12 Yahoo! Inc. System and method for context enhanced mapping
US20100049761A1 (en) * 2008-08-21 2010-02-25 Bijal Mehta Search engine method and system utilizing multiple contexts
US8386506B2 (en) 2008-08-21 2013-02-26 Yahoo! Inc. System and method for context enhanced messaging
US8555080B2 (en) * 2008-09-11 2013-10-08 Workshare Technology, Inc. Methods and systems for protect agents using distributed lightweight fingerprints
US8281027B2 (en) 2008-09-19 2012-10-02 Yahoo! Inc. System and method for distributing media related to a location
US9600484B2 (en) 2008-09-30 2017-03-21 Excalibur Ip, Llc System and method for reporting and analysis of media consumption data
US8108778B2 (en) 2008-09-30 2012-01-31 Yahoo! Inc. System and method for context enhanced mapping within a user interface
US8676782B2 (en) * 2008-10-08 2014-03-18 International Business Machines Corporation Information collection apparatus, search engine, information collection method, and program
US8984165B2 (en) * 2008-10-08 2015-03-17 Red Hat, Inc. Data transformation
US8909759B2 (en) 2008-10-10 2014-12-09 Seven Networks, Inc. Bandwidth measurement
FR2937449B1 (en) * 2008-10-17 2012-11-16 Philippe Laval Method and mel enrichment system
US8412709B1 (en) 2008-10-23 2013-04-02 Google Inc. Distributed information collection using pre-generated identifier
US9805123B2 (en) 2008-11-18 2017-10-31 Excalibur Ip, Llc System and method for data privacy in URL based context queries
US8024317B2 (en) 2008-11-18 2011-09-20 Yahoo! Inc. System and method for deriving income from URL based context queries
US8032508B2 (en) 2008-11-18 2011-10-04 Yahoo! Inc. System and method for URL based query for retrieving data related to a context
WO2010059747A3 (en) * 2008-11-18 2010-08-05 Workshare Technology, Inc. Methods and systems for exact data match filtering
US8060492B2 (en) 2008-11-18 2011-11-15 Yahoo! Inc. System and method for generation of URL based context queries
US8406456B2 (en) 2008-11-20 2013-03-26 Workshare Technology, Inc. Methods and systems for image fingerprinting
US9224172B2 (en) 2008-12-02 2015-12-29 Yahoo! Inc. Customizable content for distribution in social networks
US8055675B2 (en) 2008-12-05 2011-11-08 Yahoo! Inc. System and method for context based query augmentation
US8639493B2 (en) * 2008-12-18 2014-01-28 Intermountain Invention Management, Llc Probabilistic natural language processing using a likelihood vector
US8166016B2 (en) 2008-12-19 2012-04-24 Yahoo! Inc. System and method for automated service recommendations
US20100211533A1 (en) * 2009-02-18 2010-08-19 Microsoft Corporation Extracting structured data from web forums
US8150967B2 (en) 2009-03-24 2012-04-03 Yahoo! Inc. System and method for verified presence tracking
US20100250562A1 (en) 2009-03-24 2010-09-30 Mireo d.o.o. Recognition of addresses from the body of arbitrary text
US8793152B2 (en) * 2009-05-20 2014-07-29 Joseph Ruston Bishop Mining of distributed scientific data for enriched product/contact valuation
CA2763513A1 (en) 2009-05-26 2010-12-02 Roy Barkan Systems and methods for efficient detection of fingerprinted data and information
US8495151B2 (en) * 2009-06-05 2013-07-23 Chandra Bodapati Methods and systems for determining email addresses
US8463692B2 (en) * 2009-06-25 2013-06-11 Tradeking Group, Inc. Method and system to facilitate on-line trading
US8463652B2 (en) * 2009-06-25 2013-06-11 Tradeking Group, Inc. Method and system to facilitate on-line trading
US9841282B2 (en) 2009-07-27 2017-12-12 Visa U.S.A. Inc. Successive offer communications with an offer recipient
US8473847B2 (en) * 2009-07-27 2013-06-25 Workshare Technology, Inc. Methods and systems for comparing presentation slide decks
US8914342B2 (en) 2009-08-12 2014-12-16 Yahoo! Inc. Personal data platform
US8364611B2 (en) 2009-08-13 2013-01-29 Yahoo! Inc. System and method for precaching information on a mobile device
US9092424B2 (en) * 2009-09-30 2015-07-28 Microsoft Technology Licensing, Llc Webpage entity extraction through joint understanding of page structures and sentences
US8671089B2 (en) 2009-10-06 2014-03-11 Brightedge Technologies, Inc. Correlating web page visits and conversions with external references
US8595058B2 (en) * 2009-10-15 2013-11-26 Visa U.S.A. Systems and methods to match identifiers
US8332232B2 (en) * 2009-11-05 2012-12-11 Opinionlab, Inc. System and method for mobile interaction
US9576251B2 (en) * 2009-11-13 2017-02-21 Hewlett Packard Enterprise Development Lp Method and system for processing web activity data
US20110125733A1 (en) * 2009-11-25 2011-05-26 Fish Nathan J Quick access utility
US8606792B1 (en) 2010-02-08 2013-12-10 Google Inc. Scoring authors of posts
US8620849B2 (en) 2010-03-10 2013-12-31 Lockheed Martin Corporation Systems and methods for facilitating open source intelligence gathering
US9183560B2 (en) 2010-05-28 2015-11-10 Daniel H. Abelow Reality alternate
CN102279856B (en) * 2010-06-09 2013-10-02 阿里巴巴集团控股有限公司 Method and system for realizing website navigation
US20110314001A1 (en) * 2010-06-18 2011-12-22 Microsoft Corporation Performing query expansion based upon statistical analysis of structured data
US9043433B2 (en) 2010-07-26 2015-05-26 Seven Networks, Inc. Mobile network traffic coordination across multiple applications
US8838783B2 (en) 2010-07-26 2014-09-16 Seven Networks, Inc. Distributed caching for resource and mobile network traffic management
KR20130065710A (en) 2010-09-08 2013-06-19 에버노트 코포레이션 Site memory processing and clipping control
US9195774B2 (en) * 2010-09-17 2015-11-24 Kontera Technologies, Inc. Methods and systems for augmenting content displayed on a mobile device
CN102455997A (en) * 2010-10-27 2012-05-16 鸿富锦精密工业(深圳)有限公司 Component name extraction system and method
US20120110480A1 (en) * 2010-10-31 2012-05-03 Sap Portals Israel Ltd Method and apparatus for rendering a web page
US8484314B2 (en) 2010-11-01 2013-07-09 Seven Networks, Inc. Distributed caching in a wireless network of content delivered for a mobile application over a long-held request
WO2012060995A3 (en) 2010-11-01 2012-07-12 Michael Luna Distributed caching in a wireless network of content delivered for a mobile application over a long-held request
US8843153B2 (en) 2010-11-01 2014-09-23 Seven Networks, Inc. Mobile traffic categorization and policy for network use optimization while preserving user experience
US9171089B2 (en) * 2010-11-16 2015-10-27 John Nicholas and Kristin Gross Trust Message distribution system and method
WO2012071283A1 (en) 2010-11-22 2012-05-31 Michael Luna Aligning data transfer to optimize connections established for transmission over a wireless network
GB201309234D0 (en) 2010-11-22 2013-07-03 Seven Networks Inc Optimization of resource polling internvals to satisfy mobile device requests
GB2501416B (en) 2011-01-07 2018-03-21 Seven Networks Llc System and method for reduction of mobile network traffic used for domain name system (DNS) queries
US9898533B2 (en) 2011-02-24 2018-02-20 Microsoft Technology Licensing, Llc Augmenting search results
US20120246137A1 (en) * 2011-03-22 2012-09-27 Satish Sallakonda Visual profiles
EP2700019A4 (en) 2011-04-19 2015-01-28 Seven Networks Inc Social caching for device resource sharing and management
WO2012149434A3 (en) 2011-04-27 2013-01-24 Seven Networks, Inc. Detecting and preserving state for satisfying application requests in a distributed proxy and cache system
US8832228B2 (en) 2011-04-27 2014-09-09 Seven Networks, Inc. System and method for making requests on behalf of a mobile device based on atomic processes for mobile network traffic relief
US20120284036A1 (en) * 2011-05-03 2012-11-08 Ecomsystems, Inc. System and method for linking together an array of business programs
US8984004B2 (en) * 2011-05-09 2015-03-17 Smart-Foa Information collecting system
US9613340B2 (en) 2011-06-14 2017-04-04 Workshare Ltd. Method and system for shared document approval
US8706723B2 (en) * 2011-06-22 2014-04-22 Jostle Corporation Name-search system and method
US9239800B2 (en) 2011-07-27 2016-01-19 Seven Networks, Llc Automatic generation and distribution of policy information regarding malicious mobile traffic in a wireless network
US8650198B2 (en) 2011-08-15 2014-02-11 Lockheed Martin Corporation Systems and methods for facilitating the gathering of open source intelligence
JP5824974B2 (en) * 2011-08-31 2015-12-02 ブラザー工業株式会社 Image processing apparatus
CN103092855B (en) * 2011-10-31 2016-08-24 国际商业机器公司 Method and apparatus for detecting the address update
US9152730B2 (en) * 2011-11-10 2015-10-06 Evernote Corporation Extracting principal content from web pages
US8934414B2 (en) 2011-12-06 2015-01-13 Seven Networks, Inc. Cellular or WiFi mobile traffic optimization based on public or private network destination
US8868753B2 (en) 2011-12-06 2014-10-21 Seven Networks, Inc. System of redundantly clustered machines to provide failover mechanisms for mobile traffic management and network resource conservation
CN103150307B (en) * 2011-12-06 2016-02-10 株式会社理光 Find a name associated with keywords from the network method and apparatus
US9277443B2 (en) 2011-12-07 2016-03-01 Seven Networks, Llc Radio-awareness of mobile device for sending server-side control signals using a wireless network optimized transport protocol
GB2498064A (en) 2011-12-07 2013-07-03 Seven Networks Inc Distributed content caching mechanism using a network operator proxy
US20130159511A1 (en) 2011-12-14 2013-06-20 Seven Networks, Inc. System and method for generating a report to a network operator by distributing aggregation of data
EP2801236A4 (en) 2012-01-05 2015-10-21 Seven Networks Inc Detection and management of user interactions with foreground applications on a mobile device in distributed caching
CN103218719B (en) 2012-01-19 2016-12-07 阿里巴巴集团控股有限公司 E - Commerce website navigation method and system
WO2013116856A1 (en) 2012-02-02 2013-08-08 Seven Networks, Inc. Dynamic categorization of applications for network access in a mobile network
WO2013116852A1 (en) 2012-02-03 2013-08-08 Seven Networks, Inc. User as an end point for profiling and optimizing the delivery of content and data in a wireless network
US8812695B2 (en) 2012-04-09 2014-08-19 Seven Networks, Inc. Method and system for management of a virtual network connection without heartbeat messages
US8473293B1 (en) * 2012-04-17 2013-06-25 Google Inc. Dictionary filtering using market data
US8775631B2 (en) 2012-07-13 2014-07-08 Seven Networks, Inc. Dynamic bandwidth adjustment for browsing or streaming activity in a wireless network based on prediction of user behavior when interacting with mobile applications
GB201217563D0 (en) * 2012-10-01 2012-11-14 Wonga Technology Ltd Remote system interaction
US9161258B2 (en) 2012-10-24 2015-10-13 Seven Networks, Llc Optimized and selective management of policy deployment to mobile clients in a congested network to prevent further aggravation of network congestion
WO2014093456A3 (en) * 2012-12-11 2015-07-16 Compete, Inc. Direct page view measurement tag placement verification
US9031887B2 (en) 2012-12-18 2015-05-12 International Business Machines Corporation Determining a replacement document owner
US9307493B2 (en) 2012-12-20 2016-04-05 Seven Networks, Llc Systems and methods for application management of mobile device radio state promotion and demotion
FR3000253B1 (en) * 2012-12-21 2016-03-11 Aleph Networks content pages of the collection process and formation of a relational structure from the content
US9241314B2 (en) 2013-01-23 2016-01-19 Seven Networks, Llc Mobile device with application or context aware fast dormancy
US8874761B2 (en) 2013-01-25 2014-10-28 Seven Networks, Inc. Signaling optimization in a wireless network for traffic utilizing proprietary and non-proprietary protocols
US9002818B2 (en) 2013-01-31 2015-04-07 Hewlett-Packard Development Company, L.P. Calculating a content subset
US8750123B1 (en) 2013-03-11 2014-06-10 Seven Networks, Inc. Mobile device equipped with mobile network congestion recognition to make intelligent decisions regarding connecting to an operator network
US9170990B2 (en) 2013-03-14 2015-10-27 Workshare Limited Method and system for document retrieval with selective document comparison
US9477759B2 (en) * 2013-03-15 2016-10-25 Google Inc. Question answering using entity references in unstructured data
US9065765B2 (en) 2013-07-22 2015-06-23 Seven Networks, Inc. Proxy server associated with a mobile carrier for enhancing mobile traffic management in a mobile network
US8831969B1 (en) * 2013-10-02 2014-09-09 Linkedin Corporation System and method for determining users working for the same employers in a social network
US20150347489A1 (en) * 2014-03-31 2015-12-03 Scott David Sherwin Information retrieval system and method based on query and record metadata in combination with relevance between disparate items in classification systems
US20160119199A1 (en) * 2014-10-28 2016-04-28 AppDynamics, Inc. Reporting page composition data
CN105630802A (en) * 2014-10-30 2016-06-01 阿里巴巴集团控股有限公司 Webpage duplication removal method and apparatus
US20170024375A1 (en) * 2015-07-26 2017-01-26 Microsoft Technology Licensing, Llc Personal knowledge graph population from declarative user utterances
WO2017051420A1 (en) 2015-09-21 2017-03-30 Yissum Research Development Company Of The Hebrew University Of Jerusalem Ltd. Advanced computer implementation for crawling and/or detecting related electronically catalogued data using improved metadata processing
US20170091274A1 (en) * 2015-09-30 2017-03-30 Linkedin Corporation Organizational data enrichment

Citations (45)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5319777A (en) * 1990-10-16 1994-06-07 Sinper Corporation System and method for storing and retrieving information from a multidimensional array
US5418951A (en) * 1992-08-20 1995-05-23 The United States Of America As Represented By The Director Of National Security Agency Method of retrieving documents that concern the same topic
US5764906A (en) * 1995-11-07 1998-06-09 Netword Llc Universal electronic resource denotation, request and delivery system
US5764905A (en) * 1996-09-09 1998-06-09 Ncr Corporation Method, system and computer program product for synchronizing the flushing of parallel nodes database segments through shared disk tokens
US5813006A (en) * 1996-05-06 1998-09-22 Banyan Systems, Inc. On-line directory service with registration system
US5835905A (en) * 1997-04-09 1998-11-10 Xerox Corporation System for predicting documents relevant to focus documents by spreading activation through network representations of a linked collection of documents
US5895470A (en) * 1997-04-09 1999-04-20 Xerox Corporation System for categorizing documents in a linked collection of documents
US5918236A (en) * 1996-06-28 1999-06-29 Oracle Corporation Point of view gists and generic gists in a document browsing system
US5924090A (en) * 1997-05-01 1999-07-13 Northern Light Technology Llc Method and apparatus for searching a database of records
US5943670A (en) * 1997-11-21 1999-08-24 International Business Machines Corporation System and method for categorizing objects in combined categories
US6044375A (en) * 1998-04-30 2000-03-28 Hewlett-Packard Company Automatic extraction of metadata using a neural network
US6065016A (en) * 1996-08-06 2000-05-16 At&T Corporation Universal directory service
US6094653A (en) * 1996-12-25 2000-07-25 Nec Corporation Document classification method and apparatus therefor
US6112203A (en) * 1998-04-09 2000-08-29 Altavista Company Method for ranking documents in a hyperlinked environment using connectivity and selective content analysis
US6122647A (en) * 1998-05-19 2000-09-19 Perspecta, Inc. Dynamic generation of contextual links in hypertext documents
US6128613A (en) * 1997-06-26 2000-10-03 The Chinese University Of Hong Kong Method and apparatus for establishing topic word classes based on an entropy cost function to retrieve documents represented by the topic words
US6253198B1 (en) * 1999-05-11 2001-06-26 Search Mechanics, Inc. Process for maintaining ongoing registration for pages on a given search engine
US6260033B1 (en) * 1996-09-13 2001-07-10 Curtis M. Tatsuoka Method for remediation based on knowledge and/or functionality
US20010009017A1 (en) * 1998-01-15 2001-07-19 Alexandros Biliris Declarative message addressing
US6266664B1 (en) * 1997-10-01 2001-07-24 Rulespace, Inc. Method for scanning, analyzing and rating digital information content
US6269369B1 (en) * 1997-11-02 2001-07-31 Amazon.Com Holdings, Inc. Networked personal contact manager
US6301614B1 (en) * 1999-11-02 2001-10-09 Alta Vista Company System and method for efficient representation of data set addresses in a web crawler
US6336108B1 (en) * 1997-12-04 2002-01-01 Microsoft Corporation Speech recognition with mixtures of bayesian networks
US6349309B1 (en) * 1999-05-24 2002-02-19 International Business Machines Corporation System and method for detecting clusters of information with application to e-commerce
US6389436B1 (en) * 1997-12-15 2002-05-14 International Business Machines Corporation Enhanced hypertext categorization using hyperlinks
US6397205B1 (en) * 1998-11-24 2002-05-28 Duquesne University Of The Holy Ghost Document categorization and evaluation via cross-entrophy
US6415250B1 (en) * 1997-06-18 2002-07-02 Novell, Inc. System and method for identifying language using morphologically-based techniques
US6418432B1 (en) * 1996-04-10 2002-07-09 At&T Corporation System and method for finding information in a distributed information system using query learning and meta search
US6442555B1 (en) * 1999-10-26 2002-08-27 Hewlett-Packard Company Automatic categorization of documents using document signatures
US6463430B1 (en) * 2000-07-10 2002-10-08 Mohomine, Inc. Devices and methods for generating and managing a database
US6466940B1 (en) * 1997-02-21 2002-10-15 Dudley John Mills Building a database of CCG values of web pages from extracted attributes
US6519580B1 (en) * 2000-06-08 2003-02-11 International Business Machines Corporation Decision-tree-based symbolic rule induction system for text categorization
US6553364B1 (en) * 1997-11-03 2003-04-22 Yahoo! Inc. Information retrieval from hierarchical compound documents
US6556964B2 (en) * 1997-09-30 2003-04-29 Ihc Health Services Probabilistic system for natural language processing
US6618717B1 (en) * 2000-07-31 2003-09-09 Eliyon Technologies Corporation Computer method and apparatus for determining content owner of a website
US6621960B2 (en) * 2002-01-24 2003-09-16 Oplink Communications, Inc. Method of fabricating multiple superimposed fiber Bragg gratings
US6640224B1 (en) * 1997-12-15 2003-10-28 International Business Machines Corporation System and method for dynamic index-probe optimizations for high-dimensional similarity search
US6647396B2 (en) * 2000-12-28 2003-11-11 Trilogy Development Group, Inc. Classification based content management system
US6654768B2 (en) * 1998-10-01 2003-11-25 Onepin, Llc Method and apparatus for storing and retrieving business contact information in a computer system
US20030221163A1 (en) * 2002-02-22 2003-11-27 Nec Laboratories America, Inc. Using web structure for classifying and describing web pages
US20030225763A1 (en) * 2002-04-15 2003-12-04 Microsoft Corporation Self-improving system and method for classifying pages on the world wide web
US6665841B1 (en) * 1997-11-14 2003-12-16 Xerox Corporation Transmission of subsets of layout objects at different resolutions
US6668256B1 (en) * 2000-01-19 2003-12-23 Autonomy Corporation Ltd Algorithm for automatic selection of discriminant term combinations for document categorization
US6859797B1 (en) * 1999-03-09 2005-02-22 Sanyo France Calculatrices Electroniques, S.F.C.E. Process for the identification of a document
US20060288015A1 (en) * 2005-06-15 2006-12-21 Schirripa Steven R Electronic content classification

Family Cites Families (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4270182A (en) 1974-12-30 1981-05-26 Asija Satya P Automated information input, storage, and retrieval system
US5974455A (en) 1995-12-13 1999-10-26 Digital Equipment Corporation System for adding new entry to web page table upon receiving web page including link to another web page not having corresponding entry in web page table
WO1997025798A1 (en) 1996-01-11 1997-07-17 Mrj, Inc. System for controlling access and distribution of digital property
US6076088A (en) 1996-02-09 2000-06-13 Paik; Woojin Information extraction system and method using concept relation concept (CRC) triples
US5923850A (en) 1996-06-28 1999-07-13 Sun Microsystems, Inc. Historical asset information data storage schema
US6052693A (en) 1996-07-02 2000-04-18 Harlequin Group Plc System for assembling large databases through information extracted from text sources
JPH10320315A (en) 1997-05-14 1998-12-04 Nippon Telegr & Teleph Corp <Ntt> Electronic mail transmission management device and recording medium for recording program for executing electronic mail transmission management processing
US6055510A (en) 1997-10-24 2000-04-25 At&T Corp. Method for performing targeted marketing over a large computer network
US6336139B1 (en) 1998-06-03 2002-01-01 International Business Machines Corporation System, method and computer program product for event correlation in a distributed computing environment
US6192360B1 (en) 1998-06-23 2001-02-20 Microsoft Corporation Methods and apparatus for classifying text and for building a text classifier
EP1151401A4 (en) 1998-11-30 2002-03-06 Lexeme Corp A natural knowledge acquisition method
US6493703B1 (en) 1999-05-11 2002-12-10 Prophet Financial Systems System and method for implementing intelligent online community message board
US6601026B2 (en) 1999-09-17 2003-07-29 Discern Communications, Inc. Information retrieval by natural language querying
US6621930B1 (en) * 2000-08-09 2003-09-16 Elron Software, Inc. Automatic categorization of documents based on textual content
US6697793B2 (en) 2001-03-02 2004-02-24 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration System, method and apparatus for generating phrases from a database

Patent Citations (47)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5319777A (en) * 1990-10-16 1994-06-07 Sinper Corporation System and method for storing and retrieving information from a multidimensional array
US5418951A (en) * 1992-08-20 1995-05-23 The United States Of America As Represented By The Director Of National Security Agency Method of retrieving documents that concern the same topic
US5764906A (en) * 1995-11-07 1998-06-09 Netword Llc Universal electronic resource denotation, request and delivery system
US6418432B1 (en) * 1996-04-10 2002-07-09 At&T Corporation System and method for finding information in a distributed information system using query learning and meta search
US5813006A (en) * 1996-05-06 1998-09-22 Banyan Systems, Inc. On-line directory service with registration system
US5918236A (en) * 1996-06-28 1999-06-29 Oracle Corporation Point of view gists and generic gists in a document browsing system
US6065016A (en) * 1996-08-06 2000-05-16 At&T Corporation Universal directory service
US5764905A (en) * 1996-09-09 1998-06-09 Ncr Corporation Method, system and computer program product for synchronizing the flushing of parallel nodes database segments through shared disk tokens
US6260033B1 (en) * 1996-09-13 2001-07-10 Curtis M. Tatsuoka Method for remediation based on knowledge and/or functionality
US6094653A (en) * 1996-12-25 2000-07-25 Nec Corporation Document classification method and apparatus therefor
US6466940B1 (en) * 1997-02-21 2002-10-15 Dudley John Mills Building a database of CCG values of web pages from extracted attributes
US5895470A (en) * 1997-04-09 1999-04-20 Xerox Corporation System for categorizing documents in a linked collection of documents
US5835905A (en) * 1997-04-09 1998-11-10 Xerox Corporation System for predicting documents relevant to focus documents by spreading activation through network representations of a linked collection of documents
US5924090A (en) * 1997-05-01 1999-07-13 Northern Light Technology Llc Method and apparatus for searching a database of records
US6415250B1 (en) * 1997-06-18 2002-07-02 Novell, Inc. System and method for identifying language using morphologically-based techniques
US6128613A (en) * 1997-06-26 2000-10-03 The Chinese University Of Hong Kong Method and apparatus for establishing topic word classes based on an entropy cost function to retrieve documents represented by the topic words
US6556964B2 (en) * 1997-09-30 2003-04-29 Ihc Health Services Probabilistic system for natural language processing
US6675162B1 (en) * 1997-10-01 2004-01-06 Microsoft Corporation Method for scanning, analyzing and handling various kinds of digital information content
US6266664B1 (en) * 1997-10-01 2001-07-24 Rulespace, Inc. Method for scanning, analyzing and rating digital information content
US6269369B1 (en) * 1997-11-02 2001-07-31 Amazon.Com Holdings, Inc. Networked personal contact manager
US6553364B1 (en) * 1997-11-03 2003-04-22 Yahoo! Inc. Information retrieval from hierarchical compound documents
US6665841B1 (en) * 1997-11-14 2003-12-16 Xerox Corporation Transmission of subsets of layout objects at different resolutions
US5943670A (en) * 1997-11-21 1999-08-24 International Business Machines Corporation System and method for categorizing objects in combined categories
US6336108B1 (en) * 1997-12-04 2002-01-01 Microsoft Corporation Speech recognition with mixtures of bayesian networks
US6529891B1 (en) * 1997-12-04 2003-03-04 Microsoft Corporation Automatic determination of the number of clusters by mixtures of bayesian networks
US6389436B1 (en) * 1997-12-15 2002-05-14 International Business Machines Corporation Enhanced hypertext categorization using hyperlinks
US6640224B1 (en) * 1997-12-15 2003-10-28 International Business Machines Corporation System and method for dynamic index-probe optimizations for high-dimensional similarity search
US20010009017A1 (en) * 1998-01-15 2001-07-19 Alexandros Biliris Declarative message addressing
US6112203A (en) * 1998-04-09 2000-08-29 Altavista Company Method for ranking documents in a hyperlinked environment using connectivity and selective content analysis
US6044375A (en) * 1998-04-30 2000-03-28 Hewlett-Packard Company Automatic extraction of metadata using a neural network
US6122647A (en) * 1998-05-19 2000-09-19 Perspecta, Inc. Dynamic generation of contextual links in hypertext documents
US6654768B2 (en) * 1998-10-01 2003-11-25 Onepin, Llc Method and apparatus for storing and retrieving business contact information in a computer system
US6397205B1 (en) * 1998-11-24 2002-05-28 Duquesne University Of The Holy Ghost Document categorization and evaluation via cross-entrophy
US6859797B1 (en) * 1999-03-09 2005-02-22 Sanyo France Calculatrices Electroniques, S.F.C.E. Process for the identification of a document
US6253198B1 (en) * 1999-05-11 2001-06-26 Search Mechanics, Inc. Process for maintaining ongoing registration for pages on a given search engine
US6349309B1 (en) * 1999-05-24 2002-02-19 International Business Machines Corporation System and method for detecting clusters of information with application to e-commerce
US6442555B1 (en) * 1999-10-26 2002-08-27 Hewlett-Packard Company Automatic categorization of documents using document signatures
US6301614B1 (en) * 1999-11-02 2001-10-09 Alta Vista Company System and method for efficient representation of data set addresses in a web crawler
US6668256B1 (en) * 2000-01-19 2003-12-23 Autonomy Corporation Ltd Algorithm for automatic selection of discriminant term combinations for document categorization
US6519580B1 (en) * 2000-06-08 2003-02-11 International Business Machines Corporation Decision-tree-based symbolic rule induction system for text categorization
US6463430B1 (en) * 2000-07-10 2002-10-08 Mohomine, Inc. Devices and methods for generating and managing a database
US6618717B1 (en) * 2000-07-31 2003-09-09 Eliyon Technologies Corporation Computer method and apparatus for determining content owner of a website
US6647396B2 (en) * 2000-12-28 2003-11-11 Trilogy Development Group, Inc. Classification based content management system
US6621960B2 (en) * 2002-01-24 2003-09-16 Oplink Communications, Inc. Method of fabricating multiple superimposed fiber Bragg gratings
US20030221163A1 (en) * 2002-02-22 2003-11-27 Nec Laboratories America, Inc. Using web structure for classifying and describing web pages
US20030225763A1 (en) * 2002-04-15 2003-12-04 Microsoft Corporation Self-improving system and method for classifying pages on the world wide web
US20060288015A1 (en) * 2005-06-15 2006-12-21 Schirripa Steven R Electronic content classification

Cited By (168)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9286294B2 (en) 1992-12-09 2016-03-15 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator content suggestion engine
US20030046353A1 (en) * 1999-11-26 2003-03-06 Edmon Chung Electronic mail server
US20030005157A1 (en) * 1999-11-26 2003-01-02 Edmon Chung Network address server
US9078014B2 (en) 2000-06-19 2015-07-07 Comcast Ip Holdings I, Llc Method and apparatus for targeting of interactive virtual objects
US9813641B2 (en) 2000-06-19 2017-11-07 Comcast Ip Holdings I, Llc Method and apparatus for targeting of interactive virtual objects
US20020123985A1 (en) * 2001-02-06 2002-09-05 O'brien Christopher Data mining system, method and apparatus for industrial applications
US6662190B2 (en) 2001-03-20 2003-12-09 Ispheres Corporation Learning automatic data extraction system
WO2002075583A1 (en) * 2001-03-20 2002-09-26 Ispheres Corporation A learning automatic data extraction system
US8005870B1 (en) * 2001-06-19 2011-08-23 Microstrategy Incorporated System and method for syntax abstraction in query language generation
US8245259B2 (en) 2001-08-03 2012-08-14 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator
US8621521B2 (en) 2001-08-03 2013-12-31 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator
US20030028889A1 (en) * 2001-08-03 2003-02-06 Mccoskey John S. Video and digital multimedia aggregator
US20030028896A1 (en) * 2001-08-03 2003-02-06 Swart William D. Video and digital multimedia aggregator remote content crawler
US8578410B2 (en) 2001-08-03 2013-11-05 Comcast Ip Holdings, I, Llc Video and digital multimedia aggregator content coding and formatting
US20030028890A1 (en) * 2001-08-03 2003-02-06 Swart William D. Video and digital multimedia acquisition and delivery system and method
US7793326B2 (en) 2001-08-03 2010-09-07 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator
US8285701B2 (en) * 2001-08-03 2012-10-09 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator remote content crawler
US20120265744A1 (en) * 2001-08-08 2012-10-18 Gary Charles Berkowitz Knowledge-based e-catalog procurement system and method
US20030076342A1 (en) * 2001-10-22 2003-04-24 Siemens Medical Solutions Health Services Corporation User interface system for maintaining organization related information for use in supporting organization operation
US20060167863A1 (en) * 2001-10-22 2006-07-27 Cole Douglas J User interface system for maintaining organization related information for use in supporting organization operation
US20030078807A1 (en) * 2001-10-22 2003-04-24 Siemens Medical Solutions Health Services Corporation System for maintaining organization related information for use in supporting organization operation
US7051012B2 (en) 2001-10-22 2006-05-23 Siemens Medical Solutions Health Services Corporation User interface system for maintaining organization related information for use in supporting organization operation
US8214391B2 (en) 2002-05-08 2012-07-03 International Business Machines Corporation Knowledge-based data mining system
US20120259890A1 (en) * 2002-05-08 2012-10-11 International Business Machines Corporation Knowledge-based data mining system
US7010526B2 (en) * 2002-05-08 2006-03-07 International Business Machines Corporation Knowledge-based data mining system
US6993534B2 (en) 2002-05-08 2006-01-31 International Business Machines Corporation Data store for knowledge-based data mining system
US20030212699A1 (en) * 2002-05-08 2003-11-13 International Business Machines Corporation Data store for knowledge-based data mining system
US20030212649A1 (en) * 2002-05-08 2003-11-13 International Business Machines Corporation Knowledge-based data mining system
US20030212675A1 (en) * 2002-05-08 2003-11-13 International Business Machines Corporation Knowledge-based data mining system
US20080244026A1 (en) * 2002-05-13 2008-10-02 At&T Delaware Intellectual Property, Inc., Formerly Known As Bellsouth Intellectual Property Real-Time Notification of Presence Changes
US8606909B2 (en) 2002-05-13 2013-12-10 At&T Intellectual Property I, L.P. Real-time notification of presence availability
US8090821B2 (en) 2002-05-13 2012-01-03 At&T Intellectual Property I, L.P. Real-time notification of presence changes
US7395329B1 (en) 2002-05-13 2008-07-01 At&T Delaware Intellectual Property., Inc. Real-time notification of presence availability changes
US20030218631A1 (en) * 2002-05-21 2003-11-27 Malik Dale W. Caller initiated distinctive presence alerting and auto-response messaging
US20080184136A1 (en) * 2002-05-21 2008-07-31 At&T Delaware Intellectual Property Inc. Caller Initiated Distinctive Presence Alerting and Auto-Response Messaging
US9832145B2 (en) 2002-05-21 2017-11-28 At&T Intellectual Property I, L.P. Caller initiated distinctive presence alerting and auto-response messaging
US7353455B2 (en) 2002-05-21 2008-04-01 At&T Delaware Intellectual Property, Inc. Caller initiated distinctive presence alerting and auto-response messaging
US8707188B2 (en) 2002-05-21 2014-04-22 At&T Intellectual Property I, L.P. Caller initiated distinctive presence alerting and auto-response messaging
US9313158B2 (en) 2002-07-16 2016-04-12 Dell Software Inc. Message challenge response
US9021039B2 (en) 2002-07-16 2015-04-28 Sonicwall, Inc. Message challenge response
US9503406B2 (en) 2002-07-16 2016-11-22 Dell Software Inc. Active e-mail filter with challenge-response
US8990312B2 (en) 2002-07-16 2015-03-24 Sonicwall, Inc. Active e-mail filter with challenge-response
US20040015554A1 (en) * 2002-07-16 2004-01-22 Brian Wilson Active e-mail filter with challenge-response
US8924484B2 (en) * 2002-07-16 2014-12-30 Sonicwall, Inc. Active e-mail filter with challenge-response
US9215198B2 (en) 2002-07-16 2015-12-15 Dell Software Inc. Efficient use of resources in message classification
US9674126B2 (en) 2002-07-16 2017-06-06 Sonicwall Inc. Efficient use of resources in message classification
US20080168145A1 (en) * 2002-07-16 2008-07-10 Brian Wilson Active E-mail Filter with Challenge-Response
US7370278B2 (en) * 2002-08-19 2008-05-06 At&T Delaware Intellectual Property, Inc. Redirection of user-initiated distinctive presence alert messages
US20080209347A1 (en) * 2002-08-19 2008-08-28 At&T Delaware Intellectual Property, Inc., Formerly Known As Bellsouth Intellectual Property Redirection of a Message to an Alternate Address
US20050097473A1 (en) * 2002-08-19 2005-05-05 Bellsouth Intellectual Property Corporation Redirection of user-initiated distinctive presence alert messages
US8370756B2 (en) 2002-08-19 2013-02-05 At&T Intellectual Property I, L.P. Redirection of a message to an alternate address
US20040133561A1 (en) * 2002-10-02 2004-07-08 Burke Thomas R. System and method for identifying alternate contact information
US7254573B2 (en) 2002-10-02 2007-08-07 Burke Thomas R System and method for identifying alternate contact information in a database related to entity, query by identifying contact information of a different type than was in query which is related to the same entity
US20040215634A1 (en) * 2002-12-06 2004-10-28 Attensity Corporation Methods and products for merging codes and notes into an integrated relational database
US20040167884A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Methods and products for producing role related information from free text sources
US20040167908A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Integration of structured data with free text for data mining
US20040167885A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Data products of processes of extracting role related information from free text sources
US20040167887A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Integration of structured data with relational facts from free text for data mining
US20040167883A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Methods and systems for providing a service for producing structured data elements from free text sources
US20040167886A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Production of role related information from free text sources utilizing thematic caseframes
US20040167911A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Methods and products for integrating mixed format data including the extraction of relational facts from free text
US20050108256A1 (en) * 2002-12-06 2005-05-19 Attensity Corporation Visualization of integrated structured and unstructured data
US20040167910A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Integrated data products of processes of integrating mixed format data
US20040167870A1 (en) * 2002-12-06 2004-08-26 Attensity Corporation Systems and methods for providing a mixed data integration service
US20040205342A1 (en) * 2003-01-09 2004-10-14 Roegner Michael W. Method and system for dynamically implementing an enterprise resource policy
US9438559B1 (en) 2003-01-09 2016-09-06 Jericho Systems Corporation System for managing access to protected resources
US7779247B2 (en) 2003-01-09 2010-08-17 Jericho Systems Corporation Method and system for dynamically implementing an enterprise resource policy
US9432404B1 (en) 2003-01-09 2016-08-30 Jericho Systems Corporation System for managing access to protected resources
US8560836B2 (en) 2003-01-09 2013-10-15 Jericho Systems Corporation Method and system for dynamically implementing an enterprise resource policy
US20100161967A1 (en) * 2003-01-09 2010-06-24 Jericho Systems Corporation Method and system for dynamically implementing an enterprise resource policy
US20040164961A1 (en) * 2003-02-21 2004-08-26 Debasis Bal Method, system and computer product for continuously monitoring data sources for an event of interest
US20040215610A1 (en) * 2003-04-22 2004-10-28 Lawson Software, Inc. System and method for extracting and applying business organization information
WO2004102418A3 (en) * 2003-05-16 2005-02-10 Sap Ag Multi-language support for data mining models
US20040230417A1 (en) * 2003-05-16 2004-11-18 Achim Kraiss Multi-language support for data mining models
US7558726B2 (en) 2003-05-16 2009-07-07 Sap Ag Multi-language support for data mining models
WO2004102418A2 (en) * 2003-05-16 2004-11-25 Sap Aktiengesellschaft Multi-language support for data mining models
US20050021551A1 (en) * 2003-05-29 2005-01-27 Locateplus Corporation Current mailing address identification and verification
US8060504B2 (en) 2003-06-25 2011-11-15 Jericho Systems Corporation Method and system for selecting content items to be presented to a viewer
US8745046B2 (en) * 2003-06-25 2014-06-03 Jericho Systems Corporation Method and system for selecting content items to be presented to a viewer
US20100312741A1 (en) * 2003-06-25 2010-12-09 Roegner Michael W Method and system for selecting content items to be presented to a viewer
US7792828B2 (en) * 2003-06-25 2010-09-07 Jericho Systems Corporation Method and system for selecting content items to be presented to a viewer
US20040268388A1 (en) * 2003-06-25 2004-12-30 Roegner Michael W. Method and system for dynamically and specifically targeting marketing
US8438159B1 (en) 2003-06-25 2013-05-07 Jericho Systems, Inc. Method and system for selecting advertisements to be presented to a viewer
US7543016B2 (en) 2003-07-31 2009-06-02 International Business Machines Corporation Method, system and program product for automatically assigning electronic addresses to users
US8888496B1 (en) * 2003-08-04 2014-11-18 Skill Survey, Inc. System and method for evaluating job candidates
US20050033633A1 (en) * 2003-08-04 2005-02-10 Lapasta Douglas G. System and method for evaluating job candidates
US20050138129A1 (en) * 2003-12-23 2005-06-23 Maria Adamczyk Methods and systems of responsive messaging
US20050160014A1 (en) * 2004-01-15 2005-07-21 Cairo Inc. Techniques for identifying and comparing local retail prices
US9848086B2 (en) * 2004-02-23 2017-12-19 Nokia Technologies Oy Methods, apparatus and computer program products for dispatching and prioritizing communication of generic-recipient messages to recipients
US20050198183A1 (en) * 2004-02-23 2005-09-08 Nokia Corporation Methods, apparatus and computer program products for dispatching and prioritizing communication of generic-recipient messages to recipients
US20080140626A1 (en) * 2004-04-15 2008-06-12 Jeffery Wilson Method for enabling dynamic websites to be indexed within search engines
US7409393B2 (en) 2004-07-28 2008-08-05 Mybizintel Inc. Data gathering and distribution system
US20060026114A1 (en) * 2004-07-28 2006-02-02 Ken Gregoire Data gathering and distribution system
US20060059123A1 (en) * 2004-08-31 2006-03-16 Udo Klein Fuzzy recipient and contact search for email workflow and groupware applications
US7991787B2 (en) * 2004-08-31 2011-08-02 Sap Ag Applying search engine technology to HCM employee searches
US20060059122A1 (en) * 2004-08-31 2006-03-16 Udo Klein Applying search engine technology to HCM employee searches
US7596555B2 (en) * 2004-08-31 2009-09-29 Sap Ag Fuzzy recipient and contact search for email workflow and groupware applications
US9311601B2 (en) 2004-11-12 2016-04-12 Make Sence, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US8108389B2 (en) 2004-11-12 2012-01-31 Make Sence, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US9330175B2 (en) 2004-11-12 2016-05-03 Make Sence, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US20060123000A1 (en) * 2004-12-03 2006-06-08 Jonathan Baxter Machine learning system for extracting structured records from web pages and other text sources
US20060167931A1 (en) * 2004-12-21 2006-07-27 Make Sense, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US8126890B2 (en) * 2004-12-21 2012-02-28 Make Sence, Inc. Techniques for knowledge discovery by constructing knowledge correlations using concepts or terms
US20060212448A1 (en) * 2005-03-18 2006-09-21 Bogle Phillip L Method and apparatus for ranking candidates
US20060212305A1 (en) * 2005-03-18 2006-09-21 Jobster, Inc. Method and apparatus for ranking candidates using connection information provided by candidates
US8666964B1 (en) * 2005-04-25 2014-03-04 Google Inc. Managing items in crawl schedule
US8386459B1 (en) 2005-04-25 2013-02-26 Google Inc. Scheduling a recrawl
US8386460B1 (en) 2005-06-24 2013-02-26 Google Inc. Managing URLs
US7991762B1 (en) 2005-06-24 2011-08-02 Google Inc. Managing URLs
US20070005566A1 (en) * 2005-06-27 2007-01-04 Make Sence, Inc. Knowledge Correlation Search Engine
US8898134B2 (en) 2005-06-27 2014-11-25 Make Sence, Inc. Method for ranking resources using node pool
US8140559B2 (en) 2005-06-27 2012-03-20 Make Sence, Inc. Knowledge correlation search engine
US9477766B2 (en) 2005-06-27 2016-10-25 Make Sence, Inc. Method for ranking resources using node pool
US20070078821A1 (en) * 2005-09-30 2007-04-05 Kabushiki Kaisha Toshiba System and method for managing history of plant data
US9734259B2 (en) * 2005-11-01 2017-08-15 At&T Intellectual Property Ii, L.P. Alert driven interactive interface to a website mining system
US20130212468A1 (en) * 2005-11-01 2013-08-15 At&T Intellectual Property Ii, L.P. Alert Driven Interactive Interface to a Website Mining System
US20160026734A1 (en) * 2005-11-01 2016-01-28 At&T Intellectual Property Ii, L.P. Alert Driven Interactive Interface to a Website Mining System
US9176939B2 (en) * 2005-11-01 2015-11-03 At&T Intellectual Property Ii, L.P. Alert driven interactive interface to a website mining system
US20070112777A1 (en) * 2005-11-08 2007-05-17 Yahoo! Inc. Identification and automatic propagation of geo-location associations to un-located documents
US7792870B2 (en) * 2005-11-08 2010-09-07 Yahoo! Inc. Identification and automatic propagation of geo-location associations to un-located documents
US9213689B2 (en) 2005-11-14 2015-12-15 Make Sence, Inc. Techniques for creating computer generated notes
US20070143415A1 (en) * 2005-12-15 2007-06-21 Daigle Brian K Customizable presence icons for instant messaging
US20070156653A1 (en) * 2005-12-30 2007-07-05 Manish Garg Automated knowledge management system
US8682841B2 (en) 2006-09-11 2014-03-25 Willow Acqusition Corporation System and method for collecting and processing data
US9582611B2 (en) 2006-09-11 2017-02-28 Willow Acquisition Corporation System and method for collecting and processing data
US8271429B2 (en) * 2006-09-11 2012-09-18 Wiredset Llc System and method for collecting and processing data
US20080071796A1 (en) * 2006-09-11 2008-03-20 Ghuneim Mark D System and method for collecting and processing data
US7956739B2 (en) 2006-09-13 2011-06-07 At&T Intellectual Property I, L.P. Monitoring and entry system presence service
US20090267754A1 (en) * 2006-09-13 2009-10-29 At&T Intellectual Property I, L.P. Monitoring and Entry System Presence Service
US20080068150A1 (en) * 2006-09-13 2008-03-20 Bellsouth Intellectual Property Corporation Monitoring and entry system presence service
US7561041B2 (en) 2006-09-13 2009-07-14 At&T Intellectual Property I, L.P. Monitoring and entry system presence service
US20080071909A1 (en) * 2006-09-14 2008-03-20 Michael Young System and method for facilitating distribution of limited resources
US9344379B2 (en) 2006-09-14 2016-05-17 Afilias Limited System and method for facilitating distribution of limited resources
US20080077685A1 (en) * 2006-09-21 2008-03-27 Bellsouth Intellectual Property Corporation Dynamically configurable presence service
US8533306B2 (en) 2006-09-21 2013-09-10 At&T Intellectual Property I, L.P. Personal presentity presence subsystem
US20080077696A1 (en) * 2006-09-21 2008-03-27 Bellsouth Intellectual Property Corporation Personal presentity presence subsystem
US8316117B2 (en) 2006-09-21 2012-11-20 At&T Intellectual Property I, L.P. Personal presentity presence subsystem
US20080109411A1 (en) * 2006-10-24 2008-05-08 Michael Young Supply Chain Discovery Services
US20080147641A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method for prioritizing search results retrieved in response to a computerized search query
US20080147642A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell System for discovering data artifacts in an on-line data object
US20080147578A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell System for prioritizing search results retrieved in response to a computerized search query
US20080147631A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method and system for collecting and retrieving information from web sites
US20080147588A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method for discovering data artifacts in an on-line data object
US9900297B2 (en) 2007-01-25 2018-02-20 Salesforce.Com, Inc. System, method and apparatus for selecting content from web sources and posting content to web logs
US8068986B1 (en) 2007-04-27 2011-11-29 Majid Shahbazi Methods and apparatus related to sensor signal sniffing and/or analysis
US8335690B1 (en) 2007-08-23 2012-12-18 Convergys Customer Management Delaware Llc Method and system for creating natural language understanding grammars
US20110022675A1 (en) * 2008-03-10 2011-01-27 Afilias Limited Platform independent idn e-mail storage translation
US8756286B2 (en) * 2008-03-10 2014-06-17 Afilias Limited Alternate E-mail address configuration
US20110314109A1 (en) * 2008-03-10 2011-12-22 Afilias Limited Alternate e-mail address configuration
US20090240699A1 (en) * 2008-03-18 2009-09-24 Morgan Christopher B Integration for intelligence data systems
US20090240662A1 (en) * 2008-03-18 2009-09-24 Morgan Christopher B Integration for intelligence data systems
US8583482B2 (en) * 2008-06-23 2013-11-12 Double Verify Inc. Automated monitoring and verification of internet based advertising
US20140100970A1 (en) * 2008-06-23 2014-04-10 Double Verify Inc. Automated Monitoring and Verification of Internet Based Advertising
US20110125587A1 (en) * 2008-06-23 2011-05-26 Double Verify, Inc. Automated Monitoring and Verification of Internet Based Advertising
US20140100948A1 (en) * 2008-06-23 2014-04-10 Double Verify Inc. Automated Monitoring and Verification of Internet Based Advertising
US8260619B1 (en) 2008-08-22 2012-09-04 Convergys Cmg Utah, Inc. Method and system for creating natural language understanding grammars
US20110282909A1 (en) * 2008-10-17 2011-11-17 Intuit Inc. Secregating anonymous access to dynamic content on a web server, with cached logons
US9047387B2 (en) * 2008-10-17 2015-06-02 Intuit Inc. Secregating anonymous access to dynamic content on a web server, with cached logons
US20110035443A1 (en) * 2009-08-04 2011-02-10 At&T Intellectual Property I, L.P. Aggregated Presence Over User Federated Devices
US9258376B2 (en) 2009-08-04 2016-02-09 At&T Intellectual Property I, L.P. Aggregated presence over user federated devices
US20110225246A1 (en) * 2010-03-10 2011-09-15 Afilias Limited Alternate e-mail delivery
FR2966949A1 (en) * 2010-11-02 2012-05-04 Beetween Method for automating creation of structured database, involves removing pages whose probability indicator is less than threshold value, and processing non-isolated pages to determine information that is not directly accessible
US9753926B2 (en) * 2012-04-30 2017-09-05 Salesforce.Com, Inc. Extracting a portion of a document, such as a web page
US20130290828A1 (en) * 2012-04-30 2013-10-31 Clipboard Inc. Extracting a portion of a document, such as a web page
US9330093B1 (en) * 2012-08-02 2016-05-03 Google Inc. Methods and systems for identifying user input data for matching content to user interests
US9721205B2 (en) 2013-08-01 2017-08-01 International Business Machines Corporation Clarification of submitted questions in a question and answer system
US9342608B2 (en) 2013-08-01 2016-05-17 International Business Machines Corporation Clarification of submitted questions in a question and answer system
US9361386B2 (en) 2013-08-01 2016-06-07 International Business Machines Corporation Clarification of submitted questions in a question and answer system

Also Published As

Publication number Publication date Type
US6983282B2 (en) 2006-01-03 grant
WO2002010957A8 (en) 2002-07-25 application
WO2002010957A2 (en) 2002-02-07 application
WO2002010957A3 (en) 2003-04-10 application
WO2002010960A3 (en) 2003-07-17 application
WO2002010955A3 (en) 2003-08-07 application
US20020138525A1 (en) 2002-09-26 application
WO2002010956A3 (en) 2003-08-21 application
US6618717B1 (en) 2003-09-09 grant
US20020059251A1 (en) 2002-05-16 application
US20020091688A1 (en) 2002-07-11 application
US20020052928A1 (en) 2002-05-02 application
WO2002010982A2 (en) 2002-02-07 application
WO2002010960A2 (en) 2002-02-07 application
US7054886B2 (en) 2006-05-30 grant
US7356761B2 (en) 2008-04-08 grant
WO2002010956A2 (en) 2002-02-07 application
US7065483B2 (en) 2006-06-20 grant
US6778986B1 (en) 2004-08-17 grant
WO2002010982A3 (en) 2003-07-10 application
WO2002010955A2 (en) 2002-02-07 application

Similar Documents

Publication Publication Date Title
Chowdhury et al. Introduction to digital libraries
US6028601A (en) FAQ link creation between user&#39;s questions and answers
Meho et al. Modeling the information‐seeking behavior of social scientists: Ellis's study revisited
US7603350B1 (en) Search result ranking based on trust
US7657522B1 (en) System and method for providing information navigation and filtration
Jansen et al. Determining the informational, navigational, and transactional intent of Web queries
US7254573B2 (en) System and method for identifying alternate contact information in a database related to entity, query by identifying contact information of a different type than was in query which is related to the same entity
US7016889B2 (en) System and method for identifying useful content in a knowledge repository
US6915297B2 (en) Automatic knowledge management system
US6618717B1 (en) Computer method and apparatus for determining content owner of a website
US7720835B2 (en) Systems and methods for consumer-generated media reputation management
US6694307B2 (en) System for collecting specific information from several sources of unstructured digitized data
US8266148B2 (en) Method and system for business intelligence analytics on unstructured data
US20100114561A1 (en) Latent metonymical analysis and indexing (lmai)
US20060112081A1 (en) Storing searches in an e-mail folder
US20050119995A1 (en) Apparatus for and method of searching and organizing intellectual property information utilizing an IP thesaurus
US6681247B1 (en) Collaborator discovery method and system
Wagner Wiki: A technology for conversational knowledge management and group collaboration
Nasraoui et al. A web usage mining framework for mining evolving user profiles in dynamic web sites
US20060173957A1 (en) Apparatus and method for message-centric analysis and multi-aspect viewing using social networks
US7177904B1 (en) Techniques for sharing content information with members of a virtual user group in a network environment without compromising user privacy
US20020186240A1 (en) System and method for providing data for decision support
US6697807B2 (en) Method of and system for comparing database records to determine connections between parties over a network
Mattox et al. Enterprise expert and knowledge discovery.
Davison Recognizing nepotistic links on the web

Legal Events

Date Code Title Description
AS Assignment

Owner name: ELIYON TECHNOLOGIES CORPORATION, MASSACHUSETTS

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:STERN, JONATHAN;ROTHMAN-SHORE, JEREMY W.;KARADIMITRIOU, KOSMAS;AND OTHERS;REEL/FRAME:014917/0152

Effective date: 20040722

AS Assignment

Owner name: ZOOM INFORMATION INC., MASSACHUSETTS

Free format text: CHANGE OF NAME;ASSIGNOR:ELIYON TECHNOLOGIES CORPORATION;REEL/FRAME:016182/0815

Effective date: 20041126