US20030208482A1 - Systems and methods of retrieving relevant information - Google Patents

Systems and methods of retrieving relevant information Download PDF

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US20030208482A1
US20030208482A1 US10/454,452 US45445203A US2003208482A1 US 20030208482 A1 US20030208482 A1 US 20030208482A1 US 45445203 A US45445203 A US 45445203A US 2003208482 A1 US2003208482 A1 US 2003208482A1
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pages
rank
weight
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Brian Kim
Sudong Chung
Anurag Dod
Michael Kim
Yeogirl Yun
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9538—Presentation of query results
    • Y—GENERAL 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
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/912—Applications of a database
    • Y10S707/917—Text
    • Y—GENERAL 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
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99935—Query augmenting and refining, e.g. inexact access
    • Y—GENERAL 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
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99937—Sorting

Definitions

  • the present invention relates to the Internet and the World Wide Web. More specifically, the present invention relates to a systems and methods for retrieving and ranking relevant information from the Internet and World Wide Web.
  • Web World Wide Web
  • pages Web pages
  • One study estimates there are more than two billion publicly available pages representing a growing fraction of the world's information.
  • millions of people cannot find specific information in an efficient manner.
  • the Internet is a communications infrastructure, which links computers throughout the world. It provides certain basic rules, termed protocols, by which computers can send data to each other.
  • IP Internet Protocol
  • TCP Transmission Control Protocol
  • IP governs how packets of information are sent over the Internet.
  • IP allows one computer to send a stream of data to another by breaking the data into packets, reassembling the packets at the receiving computer, and resending any missing packets. To do this they label each packet with a unique number and send it over the network.
  • the receiving computer uses its Internet software to put the data in order.
  • the data can be nearly anything: text, email, images, sounds, and software.
  • the Web is the innovation of Tim Berners-Lee. See Berners-Lee, Weaving the Web (1999). His fundamental innovation was to provide a universal accessible hypertext medium for sharing information on the Internet. He understood that to become valuable the Web required many publishers. Because information constantly changes, it requires that any authorized person must be able to publish, correct, and read that information without any central control. Thus, there is no central computer governing the Web, and no single network or organization that runs it.
  • To publish information a person only needs access to a Web server, a computer program that shares Web resources with other computers. The person operating the Web server defines who contributes, modifies and accesses the information. In turn, to access that information, a person only needs a client computer system, and a computer program, such as a browser, which can access the server to read, edit, and at times correct the information displayed.
  • Web pages or pages are identified by an address, termed a URL (Uniform Resource Locator).
  • URL Uniform Resource Locator
  • a page Once a page has a URL, it can be published on a Web server and found by a browser. For example, one URL is http://www.amazon.com/. The letters to the left of the double slashes tell the browser what protocol to use, here HTTP, to look up the page. The part to the right—www.amazon.com—identifies the Web server where the page exists.
  • HTTP a computer language, specifies which computer talks first and how to talk in turn.
  • HTTP supports hypertext, non-sequential text, which links the pages together. Hidden behind a hypertext word, phrase, symbol, or image is the destination page's URL, which tells the browser where to locate the page.
  • HTML Hypertext Markup Language
  • HTML Hypertext Markup Language
  • the Web is all information accessible to computers, where a URL identifies each unit of information.
  • the Web has no central index to the pages, such as that contained in a public library. Instead, the pages have addresses and are loosely organized by links to each other. Thus, the Web provides little structure to support retrieval of specific information. Instead, the Web creates a hypertext space in which any computer can link to any other computer.
  • any computer can display pages through a browser such as Microsoft Internet Explorer or Netscape Communicator once connected to the Internet. Upon request the browser will fetch the page, interpret the text and display the page on the screen.
  • the page may contain hypertext links, which are typically represented by text or an icon that is highlighted, underlined, and/or shown in a different color.
  • the text or icon is referred to as anchor text. To follow the link, the user will move the cursor over the anchor text and click the mouse.
  • Yahoo! provides phrase searching, and logical operators such as AND, OR, and NOT to specify which keywords must be present or absent in the pages, truncation of keywords, name searching, and field searching, e.g., in the title or URL.
  • Web search engines are an important means of information retrieval of the pages.
  • Search engines such as Google, FAST, AltaVista, Excite, HotBot, Infoseek, and Northern Light have fuller coverage of the Web.
  • Search engines In Searching the World Wide Web , Science 280, 98-100 (1998), Lawrence and Giles reported that the major search engines covered less than half of the 320 million pages. More recently, Google and FAST reported indexing over a billion pages.
  • search engines increase their coverage, they exacerbate an existing problem.
  • Search engines pull up all pages meeting the search criteria, which can overwhelm the searcher with thousands of irrelevant pages. Once they arrive, the searcher must review them one page at a time to find the relevant ones. Even if they could download many pages, average searchers are not always willing to take a look at more than a display of pages. Therefore it is important to present the most relevant pages to the searchers at the top of the list, say in first twenty results.
  • the major search engines have a ranking function that will rank higher those pages having certain keywords in certain locations such as the title, or the Meta tag, or at the beginning of a page. This does not, however, typically put the most relevant page at the top of the list; much less assess the importance of the page relative to other pages. Moreover, relying solely on the content of the page itself—including the Meta tags which do not appear when displayed—to rank the page can be a major problem to the search engine. A web author can repeat ‘hot” keywords many times, termed spamming, for example, in the title or Meta tags to raise the rank of a given page without adding value.
  • the Web includes hypertext, which links one page to another and provides significant information through the link structure.
  • the inbound links to a page help to assess the importance of the page. Because some of the inbound links originate from authors other than the one who wrote the page being considered, they tend to give a more objective measure of the quality or importance of the pages.
  • the author of the originating page endorses the destination page.
  • the present invention relates to systems and methods of information retrieval.
  • a search engine and a method produces relevant search results to keyword queries.
  • the search engine includes a crawler to gather the pages, indexer(s) to extract and index the URLs of pages with keywords into indexed data structure(s), and ranks hypertext pages based on intrinsic and extrinsic ranks of the pages based on content and connectivity analysis.
  • the page weights can be calculated based on an iterative numerical procedure including a method for accelerating the convergence of the scores.
  • the search engine can also rank pages based on scores of a multi-keyword query. The ranking scores can be based on using the entire set of hypertext pages and/or a subset based on topic or the like.
  • One embodiment of the present invention provides a general-purpose search engine a method to rank the pages without limitation to topic according to the quality of individual pages. This embodiment of the present invention enables the search engine to present the search results in such a way that the most relevant results appear on the top of the list.
  • FIG. 1 illustrates an embodiment of the architecture of the search engine
  • FIGS. 2 A- 2 C illustrate embodiments of the Web page database
  • FIG. 3 illustrates the extrinsic rank and the intrinsic rank of a Web page
  • FIG. 4 the architecture of the ranker of the search engine
  • FIG. 5 illustrates the page weight generator of the ranker
  • FIG. 6 illustrates the architecture of the mixer of the page weight generator.
  • the present invention relates to retrieving relevant pages from hypertext page collections.
  • a search engine for collecting, storing, indexing, and ranking Web pages in response to searcher queries.
  • the search engine can be used on many other collections of hypertext pages.
  • FIG. 1 illustrates one embodiment of a search engine 10 , which includes a crawler 12 to fetch pages from the Web 13 .
  • the search engine 10 is written in C++, runs on the Microsoft 2000 Server operating system, preferably in parallel using suitable Intel Pentium processors. It should be clear, however, that it is not essential to the invention that this hardware and operating system be used, and other hardware and operating systems can be used such as Solaris or Linux.
  • this hardware and operating system be used, and other hardware and operating systems can be used such as Solaris or Linux.
  • we run multiple instances of the crawler 12 to increase its capacity to crawl and re-crawl enormous hypertext document collections such as pages on the Web.
  • the crawler 12 stores the fetched pages in a Web page database 14 , which includes data structures optimized for fast access of the fetched pages as explained below in connection with FIGS. 2 A- 2 C.
  • the crawler 12 also sends the fetched pages to a link extractor 16 , which finds the outbound links in the pages and sends the source and destination URLs of the links to a URL management system (UMS) 18 .
  • the UMS 18 assigns an identification number to each URL and maintains a database of identification number and URL pairs preferably in a hash table.
  • the UMS 18 checks the URLs one by one, and if a new URL is found, it is sent to the crawler 12 to be written in the Web page database 14 preferably through a rate controller 20 .
  • the rate controller 20 buffers the URLs to be crawled, and sends the URLs to the crawler 12 only when the Web site providing the new page has not received a crawling request for a certain amount of time. This ensures a Web site does not get excessive crawling requests.
  • the search engine 10 provides an indexing function in the following manner.
  • the anchor text and link extractor 22 writes the source URL identification number, the destination URL identification number, and associated anchor text to the anchor text and link database 24 .
  • Anchor text is a section of text, an icon, or other element in a page that links to another page.
  • the indexer 26 extracts the anchor text from the anchor text and link database 24 and parses the keywords from the Web page database 14 and generates an indexed database 28 .
  • the indexer 26 stores each keyword and its associated list of URL identification numbers for fast retrieval.
  • the search engine 10 ranks the pages in the following manner.
  • the ranker 30 reads the link structure from the anchor text and link database 24 , calculates the page weight, reads the indexed words from the indexed database 28 , and calculates the rank value for each keyword and page pair.
  • the ranker 30 stores the page weight and the rank values in the indexed database 28 .
  • the ranker 30 also builds a ranked database 32 as a subset of the indexed database 28 for a single keyword query.
  • the ranker 30 measures the relevancy of each page by examining its content, its page weight, the weight of the links to the page, and the weight of the linking pages.
  • the words, the font size, and the position of the words define the content of the page. For example, the ranker 30 compares the font size of each word relative to other words in the page to determine how important is the word.
  • the position of the word in the page also may matter. For example, if the word is in the title, it may be desirable to give it more weight than if the word appears at the bottom of the page.
  • Page weight is the probability of visitors viewing the page.
  • the ranker 30 determines the intrinsic rank of the page by multiplying the content score by the page weight.
  • the ranker 30 measures the weight of the links to the page by examining the text associated with the link such as the anchor text. For example, the ranker 30 gives more credit to a link from a page with the keyword in its anchor text. The ranker 30 determines the extrinsic rank of the page by multiplying the link weight by the page weight.
  • a query server 34 When a query server 34 receives a query from a searcher 36 , it collects the relevant pages from the ranked database 32 and indexed database 28 . Given the huge size of these databases, the pages are stored across multiple instances of search nodes. Each search node in the query server 34 collects a fixed number of the most relevant results from the databases it manages and returns them to query server 34 . The query server 34 then sorts and ranks the results from these different nodes and presents the most relevant results, typically ten, at a time.
  • FIGS. 2 A- 2 C illustrate that the data structures of the Web page database 14 typically need to accommodate different size pages.
  • pages 1-4 and 6 show that most compressed pages are roughly the same size, that is, not exceeding, for example, 6K bytes, while page 5 represents that some are larger.
  • the data structure stores pages adjacent to each other in a record tile to save storage space, and provides an index file containing the starting address of each page. This requires the Web page database 14 engage in two steps for retrieving a page.
  • the preferred data structure leverages the fact that many of the compressed pages are below a threshold, e.g., 6K bytes, and stores those pages in a fixed record large enough to contain 85% of the pages.
  • the Web page database 14 stores as much of the page as possible in the fixed record and the rest in a record file. Thus, the Web page database 14 requires just one step to retrieve 85% of the pages, greatly reducing access time.
  • a known compression technique such as the Microsoft Foundational Class (MFC) zlib library can compress the pages by 4to 1 or 3 to 1.
  • FIG. 3 illustrates how the ranker 30 determines the relevancy of a page by a combination of the intrinsic rank and extrinsic rank. Suppose we want to rank the relevancy of page a to a search query with keyword K.
  • the overall rank of page a can be then calculated by combining the intrinsic rank and extrinsic rank in the following formula:
  • IR(K;a) Intrinsic rank of page a for keyword K.
  • ER(K;a) Extrinsic rank of page a for keyword K.
  • Intrinsic rank is the measure of the importance of a page for a given keyword as claimed by the author of the page. Importance can be measured by examining the content of the page, e.g., the appearance of the keyword in the title or headings or body of the text, but this may be misleading. Some websites exaggerate the importance of their pages by repeating “hot” keywords endlessly without adding any value to the content of the page. We respect the author's claim as much as the page is worth. If the page is highly respected and frequently cited, we value author's claims more, and if otherwise, less. One solution is to use the page weight:
  • C(K;a) represents the content score of page a for keyword K and PW(a) represents the page weight for page a.
  • the content score can be calculated in many ways. One embodiment is as follows:
  • T(K;a) 1 if keyword K is found in the title of the page a and 0 otherwise.
  • P(K;a) represents the frequency of the keyword K in the plain text of page a.
  • P(K;a) is a constant, which prevents spamming.
  • plain text we mean text in the page excluding the title.
  • Parameters t, p and u represent the relative importance of the title, the plain text, and the URL field.
  • Page weight of a page is defined as the probability for a user—who travels on the Web endlessly in a random but well-defined manner—to visit the page. If a page has high probability to be visited by the user, the page is more likely to be a well-known page and to have many links from other pages.
  • the page weight reservoir has a bi-directional link to each page in the collection.
  • the page weight reservoir acts as a sink for pages having no outbound links (terminal pages) and a source for pages having no inbound links.
  • the page weight reservoir also solves the problem of pages pointing only to each other producing a loop, which would trap the user, and ensures the conservation of total page weight in the collection of pages.
  • the user complies with certain rules in moving from page to page. First, at each step, the user chooses an outbound link randomly and follows it to other pages. Second, if the user comes to the page weight reservoir, the user immediately chooses an outbound link randomly to the other pages. Consequently, each move from page to page is independent from prior history and it only depends on the current page.
  • LW(a ⁇ b) denote the link weight, that is, the probability of choosing a particular outbound hyperlink to page b out of all outbound links originating from page a.
  • the probability that the user visits page a at step n after visiting page b through the link b ⁇ a is LW(b ⁇ a) ⁇ P n ⁇ 1 (b), where P n ⁇ 1 (b) denotes the probability that the user visits page b at step n ⁇ 1.
  • the page weight is the probability for a user to visit a page, it can also represent the importance of each page.
  • a highly popular site, such as the Yahoo! home page is more likely to have higher page weight than less popular and obscure pages.
  • Link weight is the probability for the user to choose a particular outbound hyperlink out of all outbound links originating from a page.
  • Link weight also represents the importance of the link.
  • all link weights from a given page a can have a uniform value corresponding to 1/N out (a), where N out (a) is the total number of links outbound from page a, including the extra link to the page weight reservoir. Therefore, N out (a) is greater than or equal to one for every page and there is no terminal page in the collection.
  • not every outbound link is equally important. Thus, we give each link a different weight depending on several factors such as the offset of the link (i.e., position on the page) and the size of the paragraph where the link is located.
  • a link readily visible upon the loading of a page can have a higher link weight than one visible only after scrolling down.
  • the search engine can also assign different weights for external links—links that point to pages in other domain—and internal links—links that point to pages in the same domain. Many times the internal links serve as navigational tools rather than leading to new subjects represented by the anchor texts.
  • the sum of all link weights from a page equals one: ⁇ b ⁇ ⁇ LW ⁇ ( a -> b ) - 1
  • a W(K;b ⁇ a) is the anchor weight. It represents the weight given to anchor text found in page b linking to page a for a given keyword K.
  • the equation multiplies the anchor weight of a link by the weight of the originating page and sums each product for all fetched pages.
  • the anchor weight can be set in many different ways.
  • the anchor text for a given link is useful for setting the anchor weight.
  • a W(K;b ⁇ a) LW(b ⁇ a) if the keyword is in the anchor text and zero if not.
  • related headings, text in the vicinity of the anchor, and other anchor text on the same page can be used to set the anchor weight.
  • the ranker 30 calculates the rank of pages for multi-keyword queries in the following manner. For simplicity, let's consider two keyword query, K 1 ,K 2 .
  • the multi-keyword rank value is as follows:
  • IR ( K 1 ,K 2 ;a ) C ( K 1 ,K 2 ;a ) ⁇ PW ( a ).
  • C(K 1 ,K 2 ;a) is the multi-keyword content score defined as
  • PX(K 1 ,K 2 ;a) is the proximity value between two keywords, K 1 and K 2 in page a.
  • the proximity value has the maximum value of one when K 2 immediately follows K 1 and decreases to a minimum value as the distance between two keywords grows.
  • the proximity value decreases to its minimum, such as 0.1, when two keywords are separated by more than 10 words, and K 1 ⁇ circumflex over ( ) ⁇ K 2 represents the Boolean AND operation of the two keywords.
  • page c represents all pages, which contains link to page a with the identical anchor text, UA.
  • the partial extrinsic rank is very useful for a multi-keyword query.
  • UA(K) denotes the identical anchor text containing keyword K.
  • UA(K 1 ,K 2 ) is the identical anchor text containing both keywords K 1 and K 2 .
  • PX(K 1 ,K 2 ;UA(K 1 , K 2 )) is the proximity value of the keywords K 1 and K 2 within the identical anchor text UA(K 1 ,K 2 ).
  • the indexed database 28 contains a field to store the partial extrinsic rank for each identical anchor text and stores all offset for each keyword in the anchor text. Therefore, to calculate the extrinsic rank for multi-word query, we can find the entry for K 1 and K 2 in indexed database 28 .
  • the ranker 30 can obtain the proximity value and it collects the product of partial extrinsic rank and proximity value.
  • the ranker 30 associates a list of related words for selected broad topic keywords, such as “science” or “sports”. In this way we can also solve the problem of synonyms, such as finding the pages for “automobile” when querying with “car.”
  • the related words table can be as follows: Word Related words Automobile ⁇ auto, 1.0>, ⁇ car, 1.0>, ⁇ truck, 0.9>, . . . ⁇ Sports ⁇ football, 1.0>, ⁇ basketball, 0.9>, ⁇ tennis, 0.9>, . . . ⁇ . . . . .
  • the ranker 30 includes a link structure sorter 38 , which extracts records of the link structure from the anchor text and link database 24 , and sorts the records in the order of source URL identification number. The sorted records are written in the link database 40 .
  • the page weight generator 42 reads the link database 40 and calculates the page weight for the fetched pages and stores them in the page weight database 43 .
  • the intrinsic rank generator 44 reads the indexed database 28 to calculate the content score and multiplies it with the page weight read from the page weight database 43 to calculate the intrinsic rank for a given keyword and URL pair.
  • the intrinsic rank generator 44 reads one keyword at a time from the indexed database 28 .
  • the indexed database 28 stores a set of records where each record includes the URL identification number and bit fields to indicate the presence and proximity of a given keyword in the title, the anchor text of the inbound link, text related to the anchor text as described earlier, in the plain text, and/or in the URL of the page. Another bit field of the record can be set when the URL is the top-level of a given host.
  • the partial extrinsic rank generator 47 reads several input files: the anchor text and link database 24 , the indexed database 28 , and the page weight database 43 , and calculates the partial extrinsic rank values for each identical anchor text and URL pair. The resulting partial extrinsic rank is written back to the indexed database 28 to be used for extrinsic rank for single and multi-word query.
  • the extrinsic rank generator 45 collects the partial extrinsic rank for each keyword and URL pair. In the case of a multi-keyword query, the extrinsic rank generator 45 collects all partial extrinsic ranks for identical anchor text containing the keywords.
  • Intrinsic and extrinsic rank values are sent to the merger module 46 to be combined into the final rank.
  • the merger module 46 updates the rank of each URL in the indexed database 28 .
  • the merger module 46 collects the top-ranked URLs (e.g., top 400 URLs) and writes them in the ranked database 32 in descending order.
  • FIG. 5 illustrates the page weight generator 42 of the ranker 30 .
  • the function 50 initializes the page weight vector X to a constant such as 1.
  • the connectivity graph G 48 representing the link structure of all of the fetched pages, is constructed from the link database 40 .
  • the function 52 takes the connectivity graph G 48 and the new input page weight vector X 54 and computes the output page weight vector Y.
  • the function 56 tests for convergence. If the output page weight vector Y is satisfactorily close to the input page weight vector X within a predetermined tolerance, typically in the order of 10 ⁇ 6 then the iteration stops and the final page weight vector is written to the page weight database 43 .
  • the function 56 passes the input and output page weight vectors, X and Y, to the mixer module 58 , which mixes them to generate the new input page weight vector X 54 , and the iterative process repeats until the convergence is reached.
  • the extended Anderson Mixing method calculates the page weights iteratively as described in V. Eyert, A Comparative Study on Methods for Convergence Acceleration of Iterative Vector Sequence , J. Comp. Phys. 124, 271-285 (1996), which disclosure is incorporated by reference.
  • the system teaches itself to construct the next input vector in the most efficient way.
  • the mixing scheme can achieve the same accuracy in about seven iterations for what appears to take others more than 200 iterations.
  • X is a N ⁇ 1 column matrix representing the page weights for all N fetched pages.
  • N ⁇ N square matrix G represents the connectivity graph.
  • the off-diagonal elements of G represent the link connectivity between the pages.
  • the diagonal elements of the matrix G are all equal to zero.
  • the solution vector X is an eigenvector of the matrix G with the eigenvalue one. In principle, the solution vector X can be obtained from solving this matrix equation exactly. In dealing with the World Wide Web, however, the number of total pages N is very large—order of hundred of millions or billions—and solving this matrix equation exactly is impractical in terms of computer memory and CPU time. Thus, we employ the iterative method.
  • FIG. 6 illustrates one embodiment of a mixer module 58 .
  • the function 56 passes the input page weight vector X 57 and output page weight vector Y 59 to the mixer module 58 when convergence is not achieved.
  • R is the residual vector of current iteration and R j is the residual vector of j-th previous iteration.
  • M is the history level and is typically 3 or 4.
  • the coefficients b j are determined by the requirement that they yield that particular linear combination, which minimizes the magnitude of the general residual vector, ⁇ Q
  • ⁇ is a constant parameter and the value of 0.5 works usually well.
  • the mixer module 58 saves the current residual vector R 60 to the residual vector database 68 to be used for next iteration. If there are already M residual vectors in the database 68 , we discard the oldest residual vector.
  • the present invention provides a method for assigning the ranking scores for multi-keyword query.
  • ⁇ 1 ⁇ 0 +(1 ⁇ 0 ) e ⁇ i/ ⁇
  • n represents the number of keywords in the query.
  • the constant parameters ⁇ 0 and ⁇ has typical values of 0.5 and 1, respectively.
  • the present invention provides a method for calculating ranking scores by dividing the entire hypertext pages into distinct number of groups.
  • the page weight can be refined further by classifying pages into several distinct groups such as “Art”, “Education”, “Reference”, etc. Once the pages are classified, the page weights can be calculated in the same manner described above within these groups. The page weight will be more relevant for the given topic.
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Cited By (86)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020129014A1 (en) * 2001-01-10 2002-09-12 Kim Brian S. Systems and methods of retrieving relevant information
US20020138487A1 (en) * 2001-03-22 2002-09-26 Dov Weiss Method and system for mapping and searching the internet and displaying the results in a visual form
US20030149727A1 (en) * 2002-02-07 2003-08-07 Enow, Inc. Real time relevancy determination system and a method for calculating relevancy of real time information
US20040220963A1 (en) * 2003-05-01 2004-11-04 Microsoft Corporation Object clustering using inter-layer links
US20040267721A1 (en) * 2003-06-27 2004-12-30 Dmitriy Meyerzon Normalizing document metadata using directory services
US20050004943A1 (en) * 2003-04-24 2005-01-06 Chang William I. Search engine and method with improved relevancy, scope, and timeliness
US20050027685A1 (en) * 2003-03-28 2005-02-03 Kamvar Sepandar D. Adaptive computation of ranking
US20050033742A1 (en) * 2003-03-28 2005-02-10 Kamvar Sepandar D. Methods for ranking nodes in large directed graphs
US20050080786A1 (en) * 2003-10-14 2005-04-14 Fish Edmund J. System and method for customizing search results based on searcher's actual geographic location
US20050106539A1 (en) * 2003-11-17 2005-05-19 International Business Machines Corporation Self-configuring keyword derivation
US20050120292A1 (en) * 2003-11-28 2005-06-02 Fuji Xerox Co., Ltd. Device, method, and computer program product for generating information of link structure of documents
US20050138007A1 (en) * 2003-12-22 2005-06-23 International Business Machines Corporation Document enhancement method
US20050165757A1 (en) * 2000-10-25 2005-07-28 Broder Andrei Z. Method and apparatus for ranking web page search results
US20050222989A1 (en) * 2003-09-30 2005-10-06 Taher Haveliwala Results based personalization of advertisements in a search engine
EP1587009A2 (en) * 2004-04-15 2005-10-19 Microsoft Corporation Content propagation for enhanced document retrieval
US20050234879A1 (en) * 2004-04-15 2005-10-20 Hua-Jun Zeng Term suggestion for multi-sense query
US20050234953A1 (en) * 2004-04-15 2005-10-20 Microsoft Corporation Verifying relevance between keywords and Web site contents
US20050246623A1 (en) * 2004-04-29 2005-11-03 Microsoft Corporation Method and system for identifying image relatedness using link and page layout analysis
US20060026496A1 (en) * 2004-07-28 2006-02-02 Sachindra Joshi Methods, apparatus and computer programs for characterizing web resources
US20060040248A1 (en) * 2004-08-23 2006-02-23 Aaron Jeffrey A Electronic profile based education service
EP1643383A1 (en) 2004-09-30 2006-04-05 Microsoft Corporation System and method for incorporating anchor text into ranking of search results
US20060074960A1 (en) * 2004-09-20 2006-04-06 Goldschmidt Marc A Providing data integrity for data streams
US20060074910A1 (en) * 2004-09-17 2006-04-06 Become, Inc. Systems and methods of retrieving topic specific information
FR2878348A1 (fr) * 2004-11-23 2006-05-26 Thomas Henry Serveur informatique permettant a un utilisateur de gerer une pluralite de documents aux formats heterogenes
WO2006062421A2 (en) * 2004-12-10 2006-06-15 S.L.I. Systems, Inc. Information display method and system
US20060143197A1 (en) * 2004-12-23 2006-06-29 Become, Inc. Method for assigning relative quality scores to a collection of linked documents
WO2006085778A2 (en) * 2005-02-11 2006-08-17 Eurekster, Inc Information prioritisation system and method
US20060200461A1 (en) * 2005-03-01 2006-09-07 Lucas Marshall D Process for identifying weighted contextural relationships between unrelated documents
US20060230036A1 (en) * 2005-03-31 2006-10-12 Kei Tateno Information processing apparatus, information processing method and program
US20070016579A1 (en) * 2004-12-23 2007-01-18 Become, Inc. Method for assigning quality scores to documents in a linked database
US20070061315A1 (en) * 2005-09-15 2007-03-15 Microsoft Corporation Determination of useful convergence of static rank
US20070136318A1 (en) * 2005-12-08 2007-06-14 International Business Machines Corporation Document-based information and uniform resource locator (URL) management
US7260573B1 (en) * 2004-05-17 2007-08-21 Google Inc. Personalizing anchor text scores in a search engine
US20070198603A1 (en) * 2006-02-08 2007-08-23 Konstantinos Tsioutsiouliklis Using exceptional changes in webgraph snapshots over time for internet entity marking
US20070244883A1 (en) * 2006-04-14 2007-10-18 Websidestory, Inc. Analytics Based Generation of Ordered Lists, Search Engine Fee Data, and Sitemaps
US7289985B2 (en) 2004-04-15 2007-10-30 Microsoft Corporation Enhanced document retrieval
US20080016071A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using Connections Between Users, Tags and Documents to Rank Documents in an Enterprise Search System
US20080016072A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Enterprise-Based Tag System
US20080016053A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Administration Console to Select Rank Factors
US20080016061A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using a Core Data Structure to Calculate Document Ranks
US20080016098A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using Tags in an Enterprise Search System
US20080016052A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using Connections Between Users and Documents to Rank Documents in an Enterprise Search System
WO2008010158A1 (en) 2006-07-17 2008-01-24 Koninklijke Philips Electronics N.V. Determining an ambient parameter set
US20080071797A1 (en) * 2006-09-15 2008-03-20 Thornton Nathaniel L System and method to calculate average link growth on search engines for a keyword
US20080082481A1 (en) * 2006-10-03 2008-04-03 Yahoo! Inc. System and method for characterizing a web page using multiple anchor sets of web pages
US7366705B2 (en) 2004-04-15 2008-04-29 Microsoft Corporation Clustering based text classification
US20080104113A1 (en) * 2006-10-26 2008-05-01 Microsoft Corporation Uniform resource locator scoring for targeted web crawling
US7398461B1 (en) * 2002-01-24 2008-07-08 Overture Services, Inc. Method for ranking web page search results
US20080195631A1 (en) * 2007-02-13 2008-08-14 Yahoo! Inc. System and method for determining web page quality using collective inference based on local and global information
US20080229828A1 (en) * 2007-03-20 2008-09-25 Microsoft Corporation Establishing reputation factors for publishing entities
US7440941B1 (en) * 2002-09-17 2008-10-21 Yahoo! Inc. Suggesting an alternative to the spelling of a search query
US20090012937A1 (en) * 2007-07-03 2009-01-08 Sungkyunkwan University Foundation For Corporate Collaboration Apparatus, method and recorded medium for collecting user preference information by using tag information
US20090013033A1 (en) * 2007-07-06 2009-01-08 Yahoo! Inc. Identifying excessively reciprocal links among web entities
CN100456296C (zh) * 2006-06-28 2009-01-28 腾讯科技（深圳）有限公司 一种多媒体文件搜索引擎的排序方法
US20090063471A1 (en) * 2007-08-29 2009-03-05 Partnet, Inc. Systems and methods for providing a confidence-based ranking algorithm
US7502773B1 (en) * 2003-12-31 2009-03-10 Microsoft Corporation System and method facilitating page indexing employing reference information
US7565630B1 (en) 2004-06-15 2009-07-21 Google Inc. Customization of search results for search queries received from third party sites
US20090307056A1 (en) * 2008-06-09 2009-12-10 Optiweber, Inc. Collecting and scoring online references
US7672927B1 (en) 2004-02-27 2010-03-02 Yahoo! Inc. Suggesting an alternative to the spelling of a search query
US7689585B2 (en) 2004-04-15 2010-03-30 Microsoft Corporation Reinforced clustering of multi-type data objects for search term suggestion
US7716198B2 (en) 2004-12-21 2010-05-11 Microsoft Corporation Ranking search results using feature extraction
US7716223B2 (en) 2004-03-29 2010-05-11 Google Inc. Variable personalization of search results in a search engine
US20100162093A1 (en) * 2008-12-18 2010-06-24 Google Inc. Identifying comments to show in connection with a document
US7761448B2 (en) 2004-09-30 2010-07-20 Microsoft Corporation System and method for ranking search results using click distance
US7792833B2 (en) 2005-03-03 2010-09-07 Microsoft Corporation Ranking search results using language types
US7827181B2 (en) 2004-09-30 2010-11-02 Microsoft Corporation Click distance determination
US20100293057A1 (en) * 2003-09-30 2010-11-18 Haveliwala Taher H Targeted advertisements based on user profiles and page profile
US7840569B2 (en) 2007-10-18 2010-11-23 Microsoft Corporation Enterprise relevancy ranking using a neural network
US20120023091A1 (en) * 2006-10-12 2012-01-26 Vanessa Fox System and Method for Enabling Website Owner to Manage Crawl Rate in a Website Indexing System
US8417686B2 (en) 2005-05-31 2013-04-09 Google Inc. Web crawler scheduler that utilizes sitemaps from websites
US8433703B1 (en) * 2003-12-22 2013-04-30 Google Inc. Recording user actions
US8452746B2 (en) 2005-08-10 2013-05-28 Google Inc. Detecting spam search results for context processed search queries
US8495483B1 (en) * 2002-03-13 2013-07-23 Google Inc. Using text surrounding hypertext links when indexing and generating page summaries
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
US8594994B1 (en) * 2003-08-21 2013-11-26 Google Inc. Cross-lingual indexing and information retrieval
US8738635B2 (en) 2010-06-01 2014-05-27 Microsoft Corporation Detection of junk in search result ranking
US8756210B1 (en) 2005-08-10 2014-06-17 Google Inc. Aggregating context data for programmable search engines
US8812493B2 (en) 2008-04-11 2014-08-19 Microsoft Corporation Search results ranking using editing distance and document information
US8843486B2 (en) 2004-09-27 2014-09-23 Microsoft Corporation System and method for scoping searches using index keys
US20140344288A1 (en) * 2013-05-14 2014-11-20 Google Inc. Presenting Related Content in a Stream of Content
US9031937B2 (en) 2005-08-10 2015-05-12 Google Inc. Programmable search engine
US9348912B2 (en) 2007-10-18 2016-05-24 Microsoft Technology Licensing, Llc Document length as a static relevance feature for ranking search results
US9495462B2 (en) 2012-01-27 2016-11-15 Microsoft Technology Licensing, Llc Re-ranking search results
CN107798068A (zh) * 2017-09-26 2018-03-13 浙江极赢信息技术有限公司 一种失信用户数据的处理方法、系统及相关装置
US11803918B2 (en) 2015-07-07 2023-10-31 Oracle International Corporation System and method for identifying experts on arbitrary topics in an enterprise social network
USRE49927E1 (en) 2021-02-16 2024-04-16 Brightedge Technologies, Inc. Identifying and evaluating online references

Families Citing this family (146)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6185585B1 (en) * 1997-12-16 2001-02-06 Corporate Media Partners System and method for distribution and navigation of internet content
US6665837B1 (en) * 1998-08-10 2003-12-16 Overture Services, Inc. Method for identifying related pages in a hyperlinked database
US6714929B1 (en) 2001-04-13 2004-03-30 Auguri Corporation Weighted preference data search system and method
US7581167B2 (en) * 2001-05-17 2009-08-25 Hewlett-Packard Development Company, L.P. Method and system for automated simulation of dynamic URL-based Web application
US7272594B1 (en) 2001-05-31 2007-09-18 Autonomy Corporation Ltd. Method and apparatus to link to a related document
US20020198962A1 (en) * 2001-06-21 2002-12-26 Horn Frederic A. Method, system, and computer program product for distributing a stored URL and web document set
US7139972B2 (en) * 2001-07-26 2006-11-21 International Business Machines Corporation Preemptive downloading of web pages with terms associated with user interest keywords
US7836057B1 (en) 2001-09-24 2010-11-16 Auguri Corporation Weighted preference inference system and method
JP4283466B2 (ja) * 2001-10-12 2009-06-24 富士通株式会社 リンク関係に基づく文書整理方法
US8527495B2 (en) * 2002-02-19 2013-09-03 International Business Machines Corporation Plug-in parsers for configuring search engine crawler
US7949648B2 (en) * 2002-02-26 2011-05-24 Soren Alain Mortensen Compiling and accessing subject-specific information from a computer network
EP1367505A1 (en) * 2002-05-30 2003-12-03 Thomson Licensing S.A. Method and device for creating semantic browsing options
US9280603B2 (en) 2002-09-17 2016-03-08 Yahoo! Inc. Generating descriptions of matching resources based on the kind, quality, and relevance of available sources of information about the matching resources
US7406458B1 (en) * 2002-09-17 2008-07-29 Yahoo! Inc. Generating descriptions of matching resources based on the kind, quality, and relevance of available sources of information about the matching resources
US20050091106A1 (en) * 2003-10-27 2005-04-28 Reller William M. Selecting ads for a web page based on keywords located on the web page
US7536713B1 (en) 2002-12-11 2009-05-19 Alan Bartholomew Knowledge broadcasting and classification system
US20040210560A1 (en) * 2003-04-16 2004-10-21 Shuster Gary Stephen Method and system for searching a wide area network
EP1629404A2 (en) * 2003-06-03 2006-03-01 Access Co., Ltd. Method for browsing contents using page storing file
US7428700B2 (en) * 2003-07-28 2008-09-23 Microsoft Corporation Vision-based document segmentation
US7346839B2 (en) * 2003-09-30 2008-03-18 Google Inc. Information retrieval based on historical data
US7281005B2 (en) * 2003-10-20 2007-10-09 Telenor Asa Backward and forward non-normalized link weight analysis method, system, and computer program product
US20050091224A1 (en) * 2003-10-22 2005-04-28 Fisher James A. Collaborative web based development interface
US8521725B1 (en) 2003-12-03 2013-08-27 Google Inc. Systems and methods for improved searching
US8296304B2 (en) 2004-01-26 2012-10-23 International Business Machines Corporation Method, system, and program for handling redirects in a search engine
US7499913B2 (en) 2004-01-26 2009-03-03 International Business Machines Corporation Method for handling anchor text
US7293005B2 (en) 2004-01-26 2007-11-06 International Business Machines Corporation Pipelined architecture for global analysis and index building
US7424467B2 (en) * 2004-01-26 2008-09-09 International Business Machines Corporation Architecture for an indexer with fixed width sort and variable width sort
GB2411014A (en) * 2004-02-11 2005-08-17 Autonomy Corp Ltd Automatic searching for relevant information
US7584221B2 (en) * 2004-03-18 2009-09-01 Microsoft Corporation Field weighting in text searching
US7681141B2 (en) * 2004-05-11 2010-03-16 Sony Computer Entertainment America Inc. Fast scrolling in a graphical user interface
US7716225B1 (en) 2004-06-17 2010-05-11 Google Inc. Ranking documents based on user behavior and/or feature data
US7493320B2 (en) 2004-08-16 2009-02-17 Telenor Asa Method, system, and computer program product for ranking of documents using link analysis, with remedies for sinks
JP2008513881A (ja) 2004-09-16 2008-05-01 テレノール アーアスアー パーソナルウェブのドキュメントを検索し、ドキュメント間でナビゲートし、ドキュメントをランク付けするための方法、システムおよびコンピュータプログラムプロダクト
US7461064B2 (en) 2004-09-24 2008-12-02 International Buiness Machines Corporation Method for searching documents for ranges of numeric values
US8620717B1 (en) 2004-11-04 2013-12-31 Auguri Corporation Analytical tool
US7991755B2 (en) * 2004-12-17 2011-08-02 International Business Machines Corporation Dynamically ranking nodes and labels in a hyperlinked database
US8099405B2 (en) * 2004-12-28 2012-01-17 Sap Ag Search engine social proxy
US20060149800A1 (en) * 2004-12-30 2006-07-06 Daniel Egnor Authoritative document identification
US20060161543A1 (en) * 2005-01-19 2006-07-20 Tiny Engine, Inc. Systems and methods for providing search results based on linguistic analysis
US9092523B2 (en) 2005-02-28 2015-07-28 Search Engine Technologies, Llc Methods of and systems for searching by incorporating user-entered information
US20060200460A1 (en) * 2005-03-03 2006-09-07 Microsoft Corporation System and method for ranking search results using file types
CN101523338B (zh) 2005-03-18 2016-10-19 搜索引擎科技有限责任公司 应用来自用户的反馈来改进搜索结果的搜索引擎
US20060235842A1 (en) * 2005-04-14 2006-10-19 International Business Machines Corporation Web page ranking for page query across public and private
US7516123B2 (en) * 2005-04-14 2009-04-07 International Business Machines Corporation Page rank for the semantic web query
US7693829B1 (en) * 2005-04-25 2010-04-06 Google Inc. Search engine with fill-the-blanks capability
US7822751B2 (en) * 2005-05-27 2010-10-26 Google Inc. Scoring local search results based on location prominence
US7933929B1 (en) 2005-06-27 2011-04-26 Google Inc. Network link for providing dynamic data layer in a geographic information system
US8417693B2 (en) 2005-07-14 2013-04-09 International Business Machines Corporation Enforcing native access control to indexed documents
US9715542B2 (en) * 2005-08-03 2017-07-25 Search Engine Technologies, Llc Systems for and methods of finding relevant documents by analyzing tags
US7599917B2 (en) * 2005-08-15 2009-10-06 Microsoft Corporation Ranking search results using biased click distance
US7933897B2 (en) 2005-10-12 2011-04-26 Google Inc. Entity display priority in a distributed geographic information system
GB2431742A (en) * 2005-10-27 2007-05-02 Hewlett Packard Development Co A method of retrieving data from a data repository
US8095565B2 (en) * 2005-12-05 2012-01-10 Microsoft Corporation Metadata driven user interface
US7502789B2 (en) * 2005-12-15 2009-03-10 Microsoft Corporation Identifying important news reports from news home pages
US7379932B2 (en) * 2005-12-21 2008-05-27 International Business Machines Corporation System and a method for focused re-crawling of Web sites
US20070150477A1 (en) * 2005-12-22 2007-06-28 International Business Machines Corporation Validating a uniform resource locator ('URL') in a document
US8122013B1 (en) 2006-01-27 2012-02-21 Google Inc. Title based local search ranking
US7624104B2 (en) * 2006-06-22 2009-11-24 Yahoo! Inc. User-sensitive pagerank
US7752195B1 (en) * 2006-08-18 2010-07-06 A9.Com, Inc. Universal query search results
US7949661B2 (en) * 2006-08-24 2011-05-24 Yahoo! Inc. System and method for identifying web communities from seed sets of web pages
US7693865B2 (en) * 2006-08-30 2010-04-06 Yahoo! Inc. Techniques for navigational query identification
WO2008046098A2 (en) * 2006-10-13 2008-04-17 Move, Inc. Multi-tiered cascading crawling system
TWI337712B (en) * 2006-10-30 2011-02-21 Inst Information Industry Systems and methods for measuring behavior characteristics, and machine readable medium thereof
US7434576B2 (en) * 2006-11-20 2008-10-14 Hwang Horng-Jann Cutting apparatus for cutting tiles
US7921092B2 (en) * 2006-12-04 2011-04-05 Yahoo! Inc. Topic-focused search result summaries
US20080147641A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell Method for prioritizing search results retrieved in response to a computerized search query
US20080147578A1 (en) * 2006-12-14 2008-06-19 Dean Leffingwell System for prioritizing search results retrieved in response to a computerized search query
US7844602B2 (en) * 2007-01-19 2010-11-30 Healthline Networks, Inc. Method and system for establishing document relevance
ITBG20070012A1 (it) * 2007-02-13 2008-08-14 Web Lion Sas Metodo di ricerca e selezione di siti web
US7580945B2 (en) * 2007-03-30 2009-08-25 Microsoft Corporation Look-ahead document ranking system
US8161040B2 (en) * 2007-04-30 2012-04-17 Piffany, Inc. Criteria-specific authority ranking
US8244737B2 (en) * 2007-06-18 2012-08-14 Microsoft Corporation Ranking documents based on a series of document graphs
US9392074B2 (en) * 2007-07-07 2016-07-12 Qualcomm Incorporated User profile generation architecture for mobile content-message targeting
US9497286B2 (en) 2007-07-07 2016-11-15 Qualcomm Incorporated Method and system for providing targeted information based on a user profile in a mobile environment
US20090048977A1 (en) * 2007-07-07 2009-02-19 Qualcomm Incorporated User profile generation architecture for targeted content distribution using external processes
US9203911B2 (en) * 2007-11-14 2015-12-01 Qualcomm Incorporated Method and system for using a cache miss state match indicator to determine user suitability of targeted content messages in a mobile environment
CN102017550A (zh) * 2007-11-14 2011-04-13 高通股份有限公司 用于确定地理用户简档以基于所述简档确定有目标的内容消息的适宜性的方法和系统
US20090132646A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in a local search system with static location markers
US7921108B2 (en) * 2007-11-16 2011-04-05 Iac Search & Media, Inc. User interface and method in a local search system with automatic expansion
US20090132927A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method for making additions to a map
US20090132484A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in a local search system having vertical context
US20090132572A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in a local search system with profile page
US20090132513A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. Correlation of data in a system and method for conducting a search
US20090132953A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in local search system with vertical search results and an interactive map
US20090132505A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. Transformation in a system and method for conducting a search
US20090132573A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in a local search system with search results restricted by drawn figure elements
US8145703B2 (en) * 2007-11-16 2012-03-27 Iac Search & Media, Inc. User interface and method in a local search system with related search results
US8090714B2 (en) * 2007-11-16 2012-01-03 Iac Search & Media, Inc. User interface and method in a local search system with location identification in a request
US20090132486A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in local search system with results that can be reproduced
US20090132485A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method in a local search system that calculates driving directions without losing search results
US20090132514A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. method and system for building text descriptions in a search database
US20090132512A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. Search system and method for conducting a local search
US7809721B2 (en) * 2007-11-16 2010-10-05 Iac Search & Media, Inc. Ranking of objects using semantic and nonsemantic features in a system and method for conducting a search
US20090132929A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. User interface and method for a boundary display on a map
US8732155B2 (en) 2007-11-16 2014-05-20 Iac Search & Media, Inc. Categorization in a system and method for conducting a search
US20090132643A1 (en) * 2007-11-16 2009-05-21 Iac Search & Media, Inc. Persistent local search interface and method
US8447751B2 (en) * 2007-11-18 2013-05-21 Efficient Systems, Llc Navigable website analysis engine
US8789108B2 (en) * 2007-11-20 2014-07-22 Samsung Electronics Co., Ltd. Personalized video system
US8078613B2 (en) * 2007-11-28 2011-12-13 Red Hat, Inc. Method for removing network effects from search engine results
WO2009148473A1 (en) * 2007-12-12 2009-12-10 21Ct, Inc. Method and system for abstracting information for use in link analysis
US20090157512A1 (en) * 2007-12-14 2009-06-18 Qualcomm Incorporated Near field communication transactions with user profile updates in a mobile environment
JP5194765B2 (ja) * 2007-12-18 2013-05-08 富士ゼロックス株式会社 情報分析装置、及び情報分析プログラム
US8255396B2 (en) * 2008-02-25 2012-08-28 Atigeo Llc Electronic profile development, storage, use, and systems therefor
US20090216563A1 (en) * 2008-02-25 2009-08-27 Michael Sandoval Electronic profile development, storage, use and systems for taking action based thereon
CA2716062C (en) * 2008-02-25 2014-05-06 Atigeo Llc Determining relevant information for domains of interest
JP5056523B2 (ja) * 2008-03-24 2012-10-24 富士通株式会社 表示制御装置、表示制御方法及び表示制御プログラム
US20090287693A1 (en) * 2008-05-15 2009-11-19 Mathieu Audet Method for building a search algorithm and method for linking documents with an object
US8346791B1 (en) 2008-05-16 2013-01-01 Google Inc. Search augmentation
KR100987330B1 (ko) * 2008-05-21 2010-10-13 성균관대학교산학협력단 사용자 웹 사용 정보에 기반한 멀티 컨셉 네트워크 생성시스템 및 방법
US8984398B2 (en) * 2008-08-28 2015-03-17 Yahoo! Inc. Generation of search result abstracts
US20100131563A1 (en) * 2008-11-25 2010-05-27 Hongfeng Yin System and methods for automatic clustering of ranked and categorized search objects
MX2011006340A (es) 2008-12-12 2011-10-28 Atigeo Llc Suministro de recomendaciones utilizando la informacion determinada para dominios de interés.
US20100174719A1 (en) * 2009-01-06 2010-07-08 Jorge Alegre Vilches System, method, and program product for personalization of an open network search engine
US7958109B2 (en) * 2009-02-06 2011-06-07 Yahoo! Inc. Intent driven search result rich abstracts
US8234259B2 (en) * 2009-05-08 2012-07-31 Raytheon Company Method and system for adjudicating text against a defined policy
US20100318533A1 (en) * 2009-06-10 2010-12-16 Yahoo! Inc. Enriched document representations using aggregated anchor text
US9213780B2 (en) * 2009-06-26 2015-12-15 Microsoft Technology Licensing Llc Cache and index refreshing strategies for variably dynamic items and accesses
US7716179B1 (en) * 2009-10-29 2010-05-11 Wowd, Inc. DHT-based distributed file system for simultaneous use by millions of frequently disconnected, world-wide users
US7716205B1 (en) * 2009-10-29 2010-05-11 Wowd, Inc. System for user driven ranking of web pages
US9996614B2 (en) * 2010-04-07 2018-06-12 Excalibur Ip, Llc Method and system for determining relevant text in a web page
US10083248B2 (en) 2010-04-07 2018-09-25 Excalibur Ip, Llc Method and system for topic-based browsing
US20110258187A1 (en) * 2010-04-14 2011-10-20 Raytheon Company Relevance-Based Open Source Intelligence (OSINT) Collection
WO2011140506A2 (en) 2010-05-06 2011-11-10 Atigeo Llc Systems, methods, and computer readable media for security in profile utilizing systems
US20110288931A1 (en) * 2010-05-20 2011-11-24 Google Inc. Microsite models
US20120005185A1 (en) * 2010-06-30 2012-01-05 Cbs Interactive Inc. System and method for locating data feeds
US9798800B2 (en) 2010-09-24 2017-10-24 International Business Machines Corporation Providing question and answers with deferred type evaluation using text with limited structure
US8346792B1 (en) 2010-11-09 2013-01-01 Google Inc. Query generation using structural similarity between documents
US8793706B2 (en) 2010-12-16 2014-07-29 Microsoft Corporation Metadata-based eventing supporting operations on data
US9436726B2 (en) 2011-06-23 2016-09-06 BCM International Regulatory Analytics LLC System, method and computer program product for a behavioral database providing quantitative analysis of cross border policy process and related search capabilities
CN103136297A (zh) * 2011-12-05 2013-06-05 英顺源（上海）科技有限公司 通过资料查找扩充相关字词的系统及其方法
CA2789909C (en) 2012-09-14 2019-09-10 Ibm Canada Limited - Ibm Canada Limitee Synchronizing http requests with respective html context
US9323767B2 (en) 2012-10-01 2016-04-26 Longsand Limited Performance and scalability in an intelligent data operating layer system
US10725645B2 (en) * 2013-05-20 2020-07-28 Rakuten, Inc. Information processing device for controlling display of web pages using main display area and sub display area
US9411786B2 (en) * 2013-07-08 2016-08-09 Adobe Systems Incorporated Method and apparatus for determining the relevancy of hyperlinks
WO2016070026A1 (en) * 2014-10-31 2016-05-06 Informite Inc. Systems and methods for keyword research and analysis
CN104778232B (zh) * 2015-03-31 2017-04-19 北京奇虎科技有限公司 一种基于长查询的搜索结果的优化方法和装置
US11379538B1 (en) 2016-05-19 2022-07-05 Artemis Intelligence Llc Systems and methods for automatically identifying unmet technical needs and/or technical problems
CN106528861A (zh) * 2016-11-30 2017-03-22 福建中金在线信息科技有限公司 一种添加内链的方法及装置
US11392651B1 (en) 2017-04-14 2022-07-19 Artemis Intelligence Llc Systems and methods for automatically identifying unmet technical needs and/or technical problems
CN107562966B (zh) * 2017-10-23 2020-10-30 郑州大学 用于网页链接检索排序的基于智能学习的优化系统及方法
US10523742B1 (en) * 2018-07-16 2019-12-31 Brandfolder, Inc. Intelligent content delivery networks
US11449407B2 (en) 2020-05-28 2022-09-20 Bank Of America Corporation System and method for monitoring computing platform parameters and dynamically generating and deploying monitoring packages
US11762924B2 (en) * 2020-06-30 2023-09-19 Microsoft Technology Licensing, Llc Web content reliability classification
US11762916B1 (en) 2020-08-17 2023-09-19 Artemis Intelligence Llc User interface for identifying unmet technical needs and/or technical problems
CN113806660A (zh) * 2021-09-17 2021-12-17 北京百度网讯科技有限公司 数据评估方法、训练方法、装置、电子设备以及存储介质
US20230259374A1 (en) * 2022-02-16 2023-08-17 International Business Machines Corporation Task-oriented user guidance

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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
US5855015A (en) * 1995-03-20 1998-12-29 Interval Research Corporation System and method for retrieval of hyperlinked information resources
US5895470A (en) * 1997-04-09 1999-04-20 Xerox Corporation System for categorizing documents in a linked collection of documents
US6112203A (en) * 1998-04-09 2000-08-29 Altavista Company Method for ranking documents in a hyperlinked environment using connectivity and selective content analysis
US6282511B1 (en) * 1996-12-04 2001-08-28 At&T Voiced interface with hyperlinked information
US6285999B1 (en) * 1997-01-10 2001-09-04 The Board Of Trustees Of The Leland Stanford Junior University Method for node ranking in a linked database
US6334131B2 (en) * 1998-08-29 2001-12-25 International Business Machines Corporation Method for cataloging, filtering, and relevance ranking frame-based hierarchical information structures
US6356899B1 (en) * 1998-08-29 2002-03-12 International Business Machines Corporation Method for interactively creating an information database including preferred information elements, such as preferred-authority, world wide web pages
US6418433B1 (en) * 1999-01-28 2002-07-09 International Business Machines Corporation System and method for focussed web crawling

Family Cites Families (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5920859A (en) * 1997-02-05 1999-07-06 Idd Enterprises, L.P. Hypertext document retrieval system and method
US5745890A (en) * 1996-08-09 1998-04-28 Digital Equipment Corporation Sequential searching of a database index using constraints on word-location pairs
US6278992B1 (en) * 1997-03-19 2001-08-21 John Andrew Curtis Search engine using indexing method for storing and retrieving data
US5933822A (en) * 1997-07-22 1999-08-03 Microsoft Corporation Apparatus and methods for an information retrieval system that employs natural language processing of search results to improve overall precision
US6237011B1 (en) * 1997-10-08 2001-05-22 Caere Corporation Computer-based document management system
US6738678B1 (en) 1998-01-15 2004-05-18 Krishna Asur Bharat Method for ranking hyperlinked pages using content and connectivity analysis
US6922699B2 (en) * 1999-01-26 2005-07-26 Xerox Corporation System and method for quantitatively representing data objects in vector space
US6728752B1 (en) * 1999-01-26 2004-04-27 Xerox Corporation System and method for information browsing using multi-modal features
US6901402B1 (en) * 1999-06-18 2005-05-31 Microsoft Corporation System for improving the performance of information retrieval-type tasks by identifying the relations of constituents
US7181438B1 (en) * 1999-07-21 2007-02-20 Alberti Anemometer, Llc Database access system
US6516337B1 (en) * 1999-10-14 2003-02-04 Arcessa, Inc. Sending to a central indexing site meta data or signatures from objects on a computer network
US6785671B1 (en) * 1999-12-08 2004-08-31 Amazon.Com, Inc. System and method for locating web-based product offerings
US6546388B1 (en) * 2000-01-14 2003-04-08 International Business Machines Corporation Metadata search results ranking system
US6571240B1 (en) * 2000-02-02 2003-05-27 Chi Fai Ho Information processing for searching categorizing information in a document based on a categorization hierarchy and extracted phrases
US6862586B1 (en) * 2000-02-11 2005-03-01 International Business Machines Corporation Searching databases that identifying group documents forming high-dimensional torus geometric k-means clustering, ranking, summarizing based on vector triplets
US20020038299A1 (en) * 2000-03-20 2002-03-28 Uri Zernik Interface for presenting information
US6876997B1 (en) * 2000-05-22 2005-04-05 Overture Services, Inc. Method and apparatus for indentifying related searches in a database search system
US6636848B1 (en) * 2000-05-31 2003-10-21 International Business Machines Corporation Information search using knowledge agents
US6640218B1 (en) * 2000-06-02 2003-10-28 Lycos, Inc. Estimating the usefulness of an item in a collection of information
US7080073B1 (en) * 2000-08-18 2006-07-18 Firstrain, Inc. Method and apparatus for focused crawling
USH2111H1 (en) * 2000-08-28 2004-11-02 The United States Of America As Represented By The Secretary Of The Air Force Test and evaluation community network (TECNET)
US6560600B1 (en) * 2000-10-25 2003-05-06 Alta Vista Company Method and apparatus for ranking Web page search results
US7925967B2 (en) * 2000-11-21 2011-04-12 Aol Inc. Metadata quality improvement
US6618723B1 (en) * 2000-11-22 2003-09-09 Clear Direction, Inc. Interpersonal development communications system and directory
US7356530B2 (en) * 2001-01-10 2008-04-08 Looksmart, Ltd. Systems and methods of retrieving relevant information
US7299219B2 (en) * 2001-05-08 2007-11-20 The Johns Hopkins University High refresh-rate retrieval of freshly published content using distributed crawling
US20060235842A1 (en) * 2005-04-14 2006-10-19 International Business Machines Corporation Web page ranking for page query across public and private

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5855015A (en) * 1995-03-20 1998-12-29 Interval Research Corporation System and method for retrieval of hyperlinked information resources
US6282511B1 (en) * 1996-12-04 2001-08-28 At&T Voiced interface with hyperlinked information
US6285999B1 (en) * 1997-01-10 2001-09-04 The Board Of Trustees Of The Leland Stanford Junior University Method for node ranking in a linked database
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
US6112203A (en) * 1998-04-09 2000-08-29 Altavista Company Method for ranking documents in a hyperlinked environment using connectivity and selective content analysis
US6334131B2 (en) * 1998-08-29 2001-12-25 International Business Machines Corporation Method for cataloging, filtering, and relevance ranking frame-based hierarchical information structures
US6356899B1 (en) * 1998-08-29 2002-03-12 International Business Machines Corporation Method for interactively creating an information database including preferred information elements, such as preferred-authority, world wide web pages
US6418433B1 (en) * 1999-01-28 2002-07-09 International Business Machines Corporation System and method for focussed web crawling

Cited By (145)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050165757A1 (en) * 2000-10-25 2005-07-28 Broder Andrei Z. Method and apparatus for ranking web page search results
US8086601B2 (en) 2001-01-10 2011-12-27 Looksmart, Ltd. Systems and methods of retrieving relevant information
US20020129014A1 (en) * 2001-01-10 2002-09-12 Kim Brian S. Systems and methods of retrieving relevant information
US7356530B2 (en) * 2001-01-10 2008-04-08 Looksmart, Ltd. Systems and methods of retrieving relevant information
US20080147649A1 (en) * 2001-01-10 2008-06-19 Looksmart, Ltd. Systems and methods of retrieving relevant information
US20020138487A1 (en) * 2001-03-22 2002-09-26 Dov Weiss Method and system for mapping and searching the internet and displaying the results in a visual form
US7085753B2 (en) * 2001-03-22 2006-08-01 E-Nvent Usa Inc. Method and system for mapping and searching the Internet and displaying the results in a visual form
US7398461B1 (en) * 2002-01-24 2008-07-08 Overture Services, Inc. Method for ranking web page search results
US7324990B2 (en) * 2002-02-07 2008-01-29 The Relegence Corporation Real time relevancy determination system and a method for calculating relevancy of real time information
US20030149727A1 (en) * 2002-02-07 2003-08-07 Enow, Inc. Real time relevancy determination system and a method for calculating relevancy of real time information
US8495483B1 (en) * 2002-03-13 2013-07-23 Google Inc. Using text surrounding hypertext links when indexing and generating page summaries
US7440941B1 (en) * 2002-09-17 2008-10-21 Yahoo! Inc. Suggesting an alternative to the spelling of a search query
US7216123B2 (en) * 2003-03-28 2007-05-08 Board Of Trustees Of The Leland Stanford Junior University Methods for ranking nodes in large directed graphs
US7028029B2 (en) * 2003-03-28 2006-04-11 Google Inc. Adaptive computation of ranking
US20050033742A1 (en) * 2003-03-28 2005-02-10 Kamvar Sepandar D. Methods for ranking nodes in large directed graphs
US20050027685A1 (en) * 2003-03-28 2005-02-03 Kamvar Sepandar D. Adaptive computation of ranking
US20050004943A1 (en) * 2003-04-24 2005-01-06 Chang William I. Search engine and method with improved relevancy, scope, and timeliness
US20110173181A1 (en) * 2003-04-24 2011-07-14 Chang William I Search engine and method with improved relevancy, scope, and timeliness
US8645345B2 (en) 2003-04-24 2014-02-04 Affini, Inc. Search engine and method with improved relevancy, scope, and timeliness
US8886621B2 (en) 2003-04-24 2014-11-11 Affini, Inc. Search engine and method with improved relevancy, scope, and timeliness
US7917483B2 (en) * 2003-04-24 2011-03-29 Affini, Inc. Search engine and method with improved relevancy, scope, and timeliness
US7194466B2 (en) 2003-05-01 2007-03-20 Microsoft Corporation Object clustering using inter-layer links
US20040220963A1 (en) * 2003-05-01 2004-11-04 Microsoft Corporation Object clustering using inter-layer links
US7228301B2 (en) 2003-06-27 2007-06-05 Microsoft Corporation Method for normalizing document metadata to improve search results using an alias relationship directory service
US20040267721A1 (en) * 2003-06-27 2004-12-30 Dmitriy Meyerzon Normalizing document metadata using directory services
US9477656B1 (en) 2003-08-21 2016-10-25 Google Inc. Cross-lingual indexing and information retrieval
US8594994B1 (en) * 2003-08-21 2013-11-26 Google Inc. Cross-lingual indexing and information retrieval
US8321278B2 (en) 2003-09-30 2012-11-27 Google Inc. Targeted advertisements based on user profiles and page profile
US20100293057A1 (en) * 2003-09-30 2010-11-18 Haveliwala Taher H Targeted advertisements based on user profiles and page profile
US20050222989A1 (en) * 2003-09-30 2005-10-06 Taher Haveliwala Results based personalization of advertisements in a search engine
US20050080786A1 (en) * 2003-10-14 2005-04-14 Fish Edmund J. System and method for customizing search results based on searcher's actual geographic location
US20050106539A1 (en) * 2003-11-17 2005-05-19 International Business Machines Corporation Self-configuring keyword derivation
US7401287B2 (en) * 2003-11-28 2008-07-15 Fuji Xerox Co., Ltd. Device, method, and computer program product for generating information of link structure of documents
US20050120292A1 (en) * 2003-11-28 2005-06-02 Fuji Xerox Co., Ltd. Device, method, and computer program product for generating information of link structure of documents
US20050138007A1 (en) * 2003-12-22 2005-06-23 International Business Machines Corporation Document enhancement method
US8433703B1 (en) * 2003-12-22 2013-04-30 Google Inc. Recording user actions
US8825637B1 (en) 2003-12-22 2014-09-02 Google Inc. Recording user actions
US7502773B1 (en) * 2003-12-31 2009-03-10 Microsoft Corporation System and method facilitating page indexing employing reference information
US7672927B1 (en) 2004-02-27 2010-03-02 Yahoo! Inc. Suggesting an alternative to the spelling of a search query
US8180776B2 (en) 2004-03-29 2012-05-15 Google Inc. Variable personalization of search results in a search engine
US7716223B2 (en) 2004-03-29 2010-05-11 Google Inc. Variable personalization of search results in a search engine
US8874567B2 (en) 2004-03-29 2014-10-28 Google Inc. Variable personalization of search results in a search engine
US20100169297A1 (en) * 2004-03-29 2010-07-01 Google Inc. Variable Personalization of Search Results in a Search Engine
US9058364B2 (en) 2004-03-29 2015-06-16 Google Inc. Variable personalization of search results in a search engine
US7305389B2 (en) 2004-04-15 2007-12-04 Microsoft Corporation Content propagation for enhanced document retrieval
KR101114023B1 (ko) * 2004-04-15 2014-02-26 마이크로소프트 코포레이션 확장형 문서 검색을 위한 콘텐츠 전파
US7428529B2 (en) * 2004-04-15 2008-09-23 Microsoft Corporation Term suggestion for multi-sense query
US7366705B2 (en) 2004-04-15 2008-04-29 Microsoft Corporation Clustering based text classification
EP1587009A2 (en) * 2004-04-15 2005-10-19 Microsoft Corporation Content propagation for enhanced document retrieval
US20050234879A1 (en) * 2004-04-15 2005-10-20 Hua-Jun Zeng Term suggestion for multi-sense query
US7289985B2 (en) 2004-04-15 2007-10-30 Microsoft Corporation Enhanced document retrieval
US7260568B2 (en) 2004-04-15 2007-08-21 Microsoft Corporation Verifying relevance between keywords and web site contents
US20050234953A1 (en) * 2004-04-15 2005-10-20 Microsoft Corporation Verifying relevance between keywords and Web site contents
EP1587009A3 (en) * 2004-04-15 2006-08-16 Microsoft Corporation Content propagation for enhanced document retrieval
US7689585B2 (en) 2004-04-15 2010-03-30 Microsoft Corporation Reinforced clustering of multi-type data objects for search term suggestion
US20080065627A1 (en) * 2004-04-29 2008-03-13 Microsoft Corporation Method and system for identifying image relatedness using link and page layout analysis
US20050246623A1 (en) * 2004-04-29 2005-11-03 Microsoft Corporation Method and system for identifying image relatedness using link and page layout analysis
US7293007B2 (en) * 2004-04-29 2007-11-06 Microsoft Corporation Method and system for identifying image relatedness using link and page layout analysis
US7260573B1 (en) * 2004-05-17 2007-08-21 Google Inc. Personalizing anchor text scores in a search engine
US7565630B1 (en) 2004-06-15 2009-07-21 Google Inc. Customization of search results for search queries received from third party sites
US9192684B1 (en) 2004-06-15 2015-11-24 Google Inc. Customization of search results for search queries received from third party sites
US20060026496A1 (en) * 2004-07-28 2006-02-02 Sachindra Joshi Methods, apparatus and computer programs for characterizing web resources
US7516397B2 (en) * 2004-07-28 2009-04-07 International Business Machines Corporation Methods, apparatus and computer programs for characterizing web resources
US20060040248A1 (en) * 2004-08-23 2006-02-23 Aaron Jeffrey A Electronic profile based education service
US8597030B2 (en) * 2004-08-23 2013-12-03 At&T Intellectual Property I, L.P. Electronic profile based education service
US20060074910A1 (en) * 2004-09-17 2006-04-06 Become, Inc. Systems and methods of retrieving topic specific information
US20060074960A1 (en) * 2004-09-20 2006-04-06 Goldschmidt Marc A Providing data integrity for data streams
US8843486B2 (en) 2004-09-27 2014-09-23 Microsoft Corporation System and method for scoping searches using index keys
US8082246B2 (en) 2004-09-30 2011-12-20 Microsoft Corporation System and method for ranking search results using click distance
US7739277B2 (en) 2004-09-30 2010-06-15 Microsoft Corporation System and method for incorporating anchor text into ranking search results
US7761448B2 (en) 2004-09-30 2010-07-20 Microsoft Corporation System and method for ranking search results using click distance
US7827181B2 (en) 2004-09-30 2010-11-02 Microsoft Corporation Click distance determination
EP1643383A1 (en) 2004-09-30 2006-04-05 Microsoft Corporation System and method for incorporating anchor text into ranking of search results
FR2878348A1 (fr) * 2004-11-23 2006-05-26 Thomas Henry Serveur informatique permettant a un utilisateur de gerer une pluralite de documents aux formats heterogenes
WO2006062421A3 (en) * 2004-12-10 2006-07-13 S L I Systems Inc Information display method and system
WO2006062421A2 (en) * 2004-12-10 2006-06-15 S.L.I. Systems, Inc. Information display method and system
US7716198B2 (en) 2004-12-21 2010-05-11 Microsoft Corporation Ranking search results using feature extraction
US20070016579A1 (en) * 2004-12-23 2007-01-18 Become, Inc. Method for assigning quality scores to documents in a linked database
US7797344B2 (en) 2004-12-23 2010-09-14 Become, Inc. Method for assigning relative quality scores to a collection of linked documents
US7668822B2 (en) 2004-12-23 2010-02-23 Become, Inc. Method for assigning quality scores to documents in a linked database
US20060143197A1 (en) * 2004-12-23 2006-06-29 Become, Inc. Method for assigning relative quality scores to a collection of linked documents
WO2006085778A3 (en) * 2005-02-11 2006-11-02 Eurekster Inc Information prioritisation system and method
WO2006085778A2 (en) * 2005-02-11 2006-08-17 Eurekster, Inc Information prioritisation system and method
US20060195443A1 (en) * 2005-02-11 2006-08-31 Franklin Gary L Information prioritisation system and method
US20090171951A1 (en) * 2005-03-01 2009-07-02 Lucas Marshall D Process for identifying weighted contextural relationships between unrelated documents
US20060200461A1 (en) * 2005-03-01 2006-09-07 Lucas Marshall D Process for identifying weighted contextural relationships between unrelated documents
US7792833B2 (en) 2005-03-03 2010-09-07 Microsoft Corporation Ranking search results using language types
US20060230036A1 (en) * 2005-03-31 2006-10-12 Kei Tateno Information processing apparatus, information processing method and program
US8417686B2 (en) 2005-05-31 2013-04-09 Google Inc. Web crawler scheduler that utilizes sitemaps from websites
US9002819B2 (en) 2005-05-31 2015-04-07 Google Inc. Web crawler scheduler that utilizes sitemaps from websites
US8756210B1 (en) 2005-08-10 2014-06-17 Google Inc. Aggregating context data for programmable search engines
US8452746B2 (en) 2005-08-10 2013-05-28 Google Inc. Detecting spam search results for context processed search queries
US9031937B2 (en) 2005-08-10 2015-05-12 Google Inc. Programmable search engine
US20070061315A1 (en) * 2005-09-15 2007-03-15 Microsoft Corporation Determination of useful convergence of static rank
US7596556B2 (en) * 2005-09-15 2009-09-29 Microsoft Corporation Determination of useful convergence of static rank
US8307275B2 (en) * 2005-12-08 2012-11-06 International Business Machines Corporation Document-based information and uniform resource locator (URL) management
US20070136318A1 (en) * 2005-12-08 2007-06-14 International Business Machines Corporation Document-based information and uniform resource locator (URL) management
US20070198603A1 (en) * 2006-02-08 2007-08-23 Konstantinos Tsioutsiouliklis Using exceptional changes in webgraph snapshots over time for internet entity marking
US8429177B2 (en) 2006-02-08 2013-04-23 Yahoo! Inc. Using exceptional changes in webgraph snapshots over time for internet entity marking
US8131703B2 (en) * 2006-04-14 2012-03-06 Adobe Systems Incorporated Analytics based generation of ordered lists, search engine feed data, and sitemaps
US20070244883A1 (en) * 2006-04-14 2007-10-18 Websidestory, Inc. Analytics Based Generation of Ordered Lists, Search Engine Fee Data, and Sitemaps
CN100456296C (zh) * 2006-06-28 2009-01-28 腾讯科技（深圳）有限公司 一种多媒体文件搜索引擎的排序方法
US20080016053A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Administration Console to Select Rank Factors
US20080016061A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using a Core Data Structure to Calculate Document Ranks
US8204888B2 (en) 2006-07-14 2012-06-19 Oracle International Corporation Using tags in an enterprise search system
US20080016098A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using Tags in an Enterprise Search System
US20080016052A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using Connections Between Users and Documents to Rank Documents in an Enterprise Search System
US20080016072A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Enterprise-Based Tag System
US20080016071A1 (en) * 2006-07-14 2008-01-17 Bea Systems, Inc. Using Connections Between Users, Tags and Documents to Rank Documents in an Enterprise Search System
US7873641B2 (en) 2006-07-14 2011-01-18 Bea Systems, Inc. Using tags in an enterprise search system
US8938447B2 (en) 2006-07-17 2015-01-20 Koninklijke Philips N.V. Determining an ambient parameter set
WO2008010158A1 (en) 2006-07-17 2008-01-24 Koninklijke Philips Electronics N.V. Determining an ambient parameter set
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
US20080071797A1 (en) * 2006-09-15 2008-03-20 Thornton Nathaniel L System and method to calculate average link growth on search engines for a keyword
US20080082481A1 (en) * 2006-10-03 2008-04-03 Yahoo! Inc. System and method for characterizing a web page using multiple anchor sets of web pages
US7912831B2 (en) * 2006-10-03 2011-03-22 Yahoo! Inc. System and method for characterizing a web page using multiple anchor sets of web pages
US8458163B2 (en) * 2006-10-12 2013-06-04 Google Inc. System and method for enabling website owner to manage crawl rate in a website indexing system
US20120023091A1 (en) * 2006-10-12 2012-01-26 Vanessa Fox System and Method for Enabling Website Owner to Manage Crawl Rate in a Website Indexing System
US7672943B2 (en) * 2006-10-26 2010-03-02 Microsoft Corporation Calculating a downloading priority for the uniform resource locator in response to the domain density score, the anchor text score, the URL string score, the category need score, and the link proximity score for targeted web crawling
US20080104113A1 (en) * 2006-10-26 2008-05-01 Microsoft Corporation Uniform resource locator scoring for targeted web crawling
US20080195631A1 (en) * 2007-02-13 2008-08-14 Yahoo! Inc. System and method for determining web page quality using collective inference based on local and global information
US7809705B2 (en) 2007-02-13 2010-10-05 Yahoo! Inc. System and method for determining web page quality using collective inference based on local and global information
US20080229828A1 (en) * 2007-03-20 2008-09-25 Microsoft Corporation Establishing reputation factors for publishing entities
US20090012937A1 (en) * 2007-07-03 2009-01-08 Sungkyunkwan University Foundation For Corporate Collaboration Apparatus, method and recorded medium for collecting user preference information by using tag information
US20090013033A1 (en) * 2007-07-06 2009-01-08 Yahoo! Inc. Identifying excessively reciprocal links among web entities
US20090063471A1 (en) * 2007-08-29 2009-03-05 Partnet, Inc. Systems and methods for providing a confidence-based ranking algorithm
US8352511B2 (en) 2007-08-29 2013-01-08 Partnet, Inc. Systems and methods for providing a confidence-based ranking algorithm
US7840569B2 (en) 2007-10-18 2010-11-23 Microsoft Corporation Enterprise relevancy ranking using a neural network
US9348912B2 (en) 2007-10-18 2016-05-24 Microsoft Technology Licensing, Llc Document length as a static relevance feature for ranking search results
US8812493B2 (en) 2008-04-11 2014-08-19 Microsoft Corporation Search results ranking using editing distance and document information
US20090307056A1 (en) * 2008-06-09 2009-12-10 Optiweber, Inc. Collecting and scoring online references
US8190594B2 (en) 2008-06-09 2012-05-29 Brightedge Technologies, Inc. Collecting and scoring online references
US8620892B2 (en) 2008-06-09 2013-12-31 Brightedge Technologies, Inc. Collecting and scoring online references
WO2009152007A3 (en) * 2008-06-09 2010-03-18 Brightedge Technologies, Inc. Collecting and scoring online references
USRE48437E1 (en) 2008-06-09 2021-02-16 Brightedge Technologies, Inc. Collecting and scoring online references
US8656266B2 (en) * 2008-12-18 2014-02-18 Google Inc. Identifying comments to show in connection with a document
US20100162093A1 (en) * 2008-12-18 2010-06-24 Google Inc. Identifying comments to show in connection with a document
US8738635B2 (en) 2010-06-01 2014-05-27 Microsoft Corporation Detection of junk in search result ranking
US9495462B2 (en) 2012-01-27 2016-11-15 Microsoft Technology Licensing, Llc Re-ranking search results
US20140344288A1 (en) * 2013-05-14 2014-11-20 Google Inc. Presenting Related Content in a Stream of Content
US10127287B1 (en) * 2013-05-14 2018-11-13 Google Llc Presenting related content in a stream of content
US9298778B2 (en) * 2013-05-14 2016-03-29 Google Inc. Presenting related content in a stream of content
US11803918B2 (en) 2015-07-07 2023-10-31 Oracle International Corporation System and method for identifying experts on arbitrary topics in an enterprise social network
CN107798068A (zh) * 2017-09-26 2018-03-13 浙江极赢信息技术有限公司 一种失信用户数据的处理方法、系统及相关装置
USRE49927E1 (en) 2021-02-16 2024-04-16 Brightedge Technologies, Inc. Identifying and evaluating online references

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US20080147649A1 (en) 2008-06-19

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