WO2013062814A1 - Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within - Google Patents

Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within Download PDF

Info

Publication number
WO2013062814A1
WO2013062814A1 PCT/US2012/060467 US2012060467W WO2013062814A1 WO 2013062814 A1 WO2013062814 A1 WO 2013062814A1 US 2012060467 W US2012060467 W US 2012060467W WO 2013062814 A1 WO2013062814 A1 WO 2013062814A1
Authority
WO
WIPO (PCT)
Prior art keywords
search text
pages
document
highlight option
searching
Prior art date
Application number
PCT/US2012/060467
Other languages
French (fr)
Inventor
Basker S. KRISHNAN
Hanoz J. KATELI
Bryan Heesch
Original Assignee
Imagescan, Inc.
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
Application filed by Imagescan, Inc. filed Critical Imagescan, Inc.
Priority to EP12844445.2A priority Critical patent/EP2771781A4/en
Priority to CN201280059083.0A priority patent/CN103959232B/en
Publication of WO2013062814A1 publication Critical patent/WO2013062814A1/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33Querying
    • G06F16/338Presentation of query results

Definitions

  • This disclosure relates generally to apparatus and methods for visual presentation of search results. More particularly, the disclosure relates to visually presenting search results to enable use of cognitive pattern recognition.
  • an apparatus and method for searching and displaying using cognitive pattern recognition including searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
  • CIF scaled common image format
  • a method for searching and displaying using cognitive pattern recognition including searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
  • CIF scaled common image format
  • an apparatus for searching and displaying using cognitive pattern recognition comprising a processor and a memory, the memory containing program code executable by the processor for performing the following: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
  • an apparatus for searching and displaying using cognitive pattern recognition comprising a processor and a memory, the memory containing program code executable by the processor for performing the following: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
  • CIF scaled common image format
  • Advantages of the present disclosure may include reducing the steps and time needed to search for an object (e.g., a document) or information within the object.
  • Another possible advantage includes increased accuracy and built in fault tolerance, for example, for OCR (optical character recognition) errors and misfiles in locating an object or information within the object.
  • OCR optical character recognition
  • Figure 1 illustrates an example of a flow diagram 1 00 for searching and displaying results using cognitive pattern recognition.
  • Figure 2 illustrates a first example of pages of at least one or more document where the search text exists wherein a highlight option is disabled.
  • Figure 3 illustrates a first example of pages of at least one or more document where the search text exists wherein a highlight option is enabled.
  • Figure 4 illustrates the first example of Figure 2 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages.
  • Figure 5 illustrates the second example of Figure 3 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages.
  • Figure 6 illustrates an example of a device comprising a processor in communication with a memory for executing the algorithm in the flow diagram illustrated in Figure 1 .
  • Figure 7 illustrates an example of a device suitable for searching and displaying results using cognitive pattern recognition in the flow diagram illustrated in Figure 1 .
  • Figure 8 illustrates a first example of a set of documents displayed from a search result.
  • Figure 9 illustrates a second example of a set of documents displayed from a search result.
  • Figure 1 0 illustrates a third example of a set of documents displayed from a search result.
  • Figure 1 1 illustrates a fourth example of a set of documents displayed from a search result.
  • a search may be based on not just words contained in a document, but also the user's memory of a visual image of the document and/or the approximate date of the document. For example, different documents or versions of a same document may contain many identical keywords. However, the visual presentation (i.e., display) of the first page (or any other page) of different documents or types of documents may differ. Thus, there's a need for a search & display approach that can utilize the aspects of keyword searching and visual presentation (i.e., display) of the document being searched to quickly and efficiently locate the document in a document repository (e.g., database.).
  • a document repository e.g., database.
  • FIG. 1 illustrates an example of a flow diagram 100 for searching and displaying results using cognitive pattern recognition.
  • search at least one document for at least one search text, wherein the at least one search text is associated with a highlight option.
  • the highlight option allows a user to determine which search text should be differentiated from the remaining text of a document when the search text found within the document. The differentiation allows a user to quickly distinguish the search text from the rest of the remaining text.
  • the search text with the highlight option enabled is differentiated from the remaining text of the document in one or more of the following manner: highlighted by a different color (i.e., color differentiation), bolded, italicized, underlined, etc.
  • a different color i.e., color differentiation
  • bolded italicized
  • underlined etc.
  • the highlight option includes a color differentiation (e.g., a yellow color) added to a search text.
  • the highlight option includes varying the fonts, the mark-ups, or an added visual distinction to the search text.
  • the highlight option includes adding a border around the search text.
  • different search text may be associated with different highlight options. For example, a first search text may be highlighted in yellow while a second search text may be bolded.
  • a first search text may be highlighted in yellow while a second search text may be bolded.
  • multiple search text may be associated with different highlight options, that is, with different examples of distinguishing the multiple search text from each.
  • search text as used in the present disclosure may be a single word, a collection of words (i.e., a phrase of contiguous words), a symbol, a regular expression, a number, a special character and/or any combination thereof.
  • the at least one search text comprises multiple search text to be searched concurrently with one or more documents.
  • a search text is a keyword, a date or date range, a meta data, etc.
  • the at least one document is searched based on one or more of the following : an attribute, an attribute range or a special definition.
  • an attribute may be a significant identifier such as a social security number and the search might involve a single, multiple (within a range) or all SSNs within documents in a repository.
  • an attribute may be a special symbol or a special character.
  • an attribute range may be all dates within a specified range (e.g., from Jan 1 , 2000 - Dec 30, 201 0).
  • an attribute range may be all amounts found within a range (e.g., $50,000 to $1 00,000 or 1 liter to 1 000 liters, etc.) within documents.
  • the special definition may be a list of predefined synonyms.
  • the special definition may be a list of antonyms.
  • the highlight option associated with one search text is enabled, such that, for example, the search text would be highlighted in yellow each time it occurs on a page of a document of a repository or database.
  • the repository is the Internet.
  • the repository is a private database.
  • each of the search text is associated with a highlight option which may be enabled or disabled.
  • multiple search text with their highlight option enabled may be differentiated differently from each other. For example, a first search text with its highlight option enabled may be bolded, a second search text with its highlight option enabled may be underlined, a third search text with its highlight option enabled may be italicized. And, another search text may have its highlight option disabled such that it is not differentiated from the remaining text (non-searched text) of the document.
  • presenting a quantity of the at least one document may include presenting one or more documents.
  • common image format is a digital representation of a document which retains the look and feel of the document in a printed form or it is a visual representation of the pages within digitally converted paper or electronically created documents.
  • the first page of each of the quantity of the searched documents is presented in the scaled common image format (CIF).
  • a first page of each of the quantity of the searched documents is presented in the scaled common image format (CIF).
  • the presenting of the quantity is done in a predetermined order.
  • the predetermined order is based on a meta data parameter.
  • at least one meta data parameter is presented along with the scaled common image format (CIF).
  • a portion of a meta data parameter is presented along with the scaled common image format (CIF).
  • the meta data parameter is modified before being presented.
  • the at least one meta data parameter is a date information.
  • the date information may be a date the document is created, a date contained within the document, a date the document is processed, such as scanned, or a date assigned to the document, etc.
  • the selected amount is the pages wherein the at least one search text exists on each of the pages and wherein the search text is presented with the highlight option enabled.
  • the selected amount is a chosen quantity of pages, and may range, for example, from a single page to multiple pages. In one example, the selected amount of pages is from a single document.
  • block 150 add a visual distinction to one or more pages of the quantity where the at least one search text exists from the rest of the pages of each document of the quantity.
  • the selected amount includes all the pages with the added visual distinction.
  • the selected amount is from a single document.
  • steps in blocks 1 10 through 150 are written in a particular order (the step in block 150 follows the step in block 140 which follows the step in block 130 which follows the step in block 120 which follows the step in block 1 10), the order of the steps may be interchanged without affecting the scope or spirit of the present disclosure.
  • some of the steps in Figure 1 are performed by a computer, such as a personal computer.
  • some of the steps in Figure 1 are performed by a handheld device that incorporates at least one processor.
  • Figure 2 illustrates a first example of pages of at least one or more document where the search text exists.
  • the highlight option of the search text is disabled.
  • Figure 3 illustrates a second example of pages of at least one or more document where the search text exists. In this example of Figure 3, the highlight option of the search text is enabled.
  • Figure 4 illustrates the first example of Figure 2 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages.
  • the second and third pages are presented with borders.
  • a user determines whether some of the pages are to be presented in the different format.
  • the user may determine what the different format should be, for example, in using borders or some other different formatting.
  • the user may determine the one or more criteria for some of the pages to be presented in the different format.
  • One skilled in the art would understand that other forms of different formats, not limited to borders as illustrated herein, may be used without restricting the scope and spirit of the present disclosure.
  • Figure 5 illustrates the second example of Figure 3 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages.
  • the second and third pages are presented with borders where the highlight search text is found.
  • a user determines whether some of the pages are to be presented in the different format.
  • the user may determine what the different format should be, for example, in using borders or some other different formatting.
  • the user may determine the one or more criteria for some of the pages to be presented in the different format.
  • One skilled in the art would understand that other forms of different formats, not limited to borders as illustrated herein, may be used without restricting the scope and spirit of the present disclosure.
  • cognitive pattern recognition is based on prior cognitive knowledge. For example, recognition is based on a collective memory about the document being searched.
  • the cognition pattern being recognized may be based on memory of one or more of the following: file format (e.g., Word, Excel etc.), approximate date of the document (last month, last quarter, last year etc.), from and to details on correspondence/email/fax, keywords within documents, key sections within documents (e.g., pricing details within a proposal or termination clause within a contract); memory of how various digital file formats look.
  • recognition is based on cognitive intelligence.
  • the search is for a document that one is not familiar with, however aspects of the document are known to the searcher.
  • the search is for a tax form, a court document or a lab report, etc., wherein each has its unique image pattern that is easily recognizable.
  • the location of the search text e.g., highlighted keyword(s)
  • common image format e.g., miniature visual display
  • the processing units may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described therein, or a combination thereof.
  • ASICs application specific integrated circuits
  • DSPs digital signal processors
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGAs field programmable gate arrays
  • processors controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described therein, or a combination thereof.
  • the implementation may be through modules (e.g., procedures, functions, etc.) that perform the functions described therein.
  • the software codes may be stored in memory units and executed by a processor unit.
  • the steps or functions described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.
  • Computer- readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another.
  • a storage media may be any available media that can be accessed by a computer.
  • such computer- readable media can comprise memory stick, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
  • any connection is properly termed a computer-readable medium.
  • the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave
  • the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium.
  • Disk and disc includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
  • a processor is coupled with a memory which stores data, meta data, program instructions, etc. to be executed by the processor for implementing or performing the various flow diagrams, logical blocks and/or modules described herein.
  • Figure 6 illustrates an example of a device 600 comprising a processor 610 in communication with a memory 620 for executing the algorithm in the flow diagram illustrated in Figure 1 .
  • the memory 620 is located within the processor 610.
  • the memory 620 is external to the processor 610.
  • the processor includes circuitry for implementing or performing the various flow diagrams, logical blocks and/or modules described herein.
  • Figure 7 illustrates an example of a device 700 suitable for searching and displaying results using cognitive pattern recognition in the flow diagram illustrated in Figure 1 .
  • the device 700 is implemented by at least one processor comprising one or more modules configured to search using cognitive pattern recognition as described herein in blocks 710, 720, 730, 740 and 750.
  • each module comprises hardware, firmware, software, or any combination thereof.
  • the device 700 is also implemented by at least one memory in communication with the at least one processor.
  • Figure 8 illustrates a first example of a set of documents displayed from a search result.
  • the set of documents are displayed in a scaled common image format (CIF) with meta data information in the image tag.
  • CIF scaled common image format
  • Figure 9 illustrates a second example of a set of documents displayed from a search result.
  • the set of documents may be displayed in a scaled CIF with meta data information in the image tag.
  • the search text e.g., keyword(s)
  • Figure 10 illustrates a third example of a set of documents displayed from a search result.
  • the set of documents may be displayed in a scaled CIF with meta data information in the image tag.
  • Figure 10 illustrates a third example of a set of documents displayed from a search result.
  • the set of documents may be displayed in a scaled CIF with meta data information in the image tag.
  • the pages with all the search text e.g., keyword(s) found are displayed.
  • the display includes pages with the search text the highlight option enabled as well as the search text with the highlight option disabled.
  • the search text with the highlight option enabled is displayed differently than the search text with the highlight option disabled.
  • Figure 1 1 illustrates a fourth example of a set of documents displayed from a search result.
  • the set of documents may be displayed in a scaled CIF with meta data information in the image tag.
  • all the pages within a document are displayed. This includes pages with the search text the highlight option enabled as well as the search text with the highlight option disabled.
  • the search text with the highlight option enabled is displayed differently than the search text with the highlight option disabled.

Abstract

An apparatus and method for searching and displaying using cognitive pattern recognition including searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.

Description

APPARATUS AND METHOD FOR DISPLAYING
SEARCH RESULTS USI NG COGN ITIVE PATTERN RECOGNITION IN LOCATING DOCUMENTS AN D IN FORMATION WITH IN
BACKGROUND OF THE INVENTION
This disclosure relates generally to apparatus and methods for visual presentation of search results. More particularly, the disclosure relates to visually presenting search results to enable use of cognitive pattern recognition.
In current document files, it is known that many documents with similar or even identical words exist. Thus, with the commonality of words and phrases in different documents or even different versions of the documents, it is time consuming to find an exact document quickly and efficiently. Often, a keyword search could produce a list of many documents with the same word and even include all the various versions of the different documents containing the keyword. This is especially problematic if the keyword used in the search is a common word for a particular application.
SUMMARY OF THE INVENTION
Disclosed is an apparatus and method for searching and displaying results using cognitive pattern recognition. According to one aspect, an apparatus and method for searching and displaying using cognitive pattern recognition including searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
According to another aspect, a method for searching and displaying using cognitive pattern recognition including searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
According to another aspect, an apparatus for searching and displaying using cognitive pattern recognition, the apparatus comprising a processor and a memory, the memory containing program code executable by the processor for performing the following: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
According to another aspect, an apparatus for searching and displaying using cognitive pattern recognition, the apparatus comprising a processor and a memory, the memory containing program code executable by the processor for performing the following: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
Advantages of the present disclosure may include reducing the steps and time needed to search for an object (e.g., a document) or information within the object. Another possible advantage includes increased accuracy and built in fault tolerance, for example, for OCR (optical character recognition) errors and misfiles in locating an object or information within the object.
It is understood that other aspects will become readily apparent to those skilled in the art from the following detailed description, wherein it is shown and described various aspects by way of illustration. The drawings and detailed description are to be regarded as illustrative in nature and not as restrictive. BRI EF DESCRI PTION OF THE DRAWINGS
Figure 1 illustrates an example of a flow diagram 1 00 for searching and displaying results using cognitive pattern recognition.
Figure 2 illustrates a first example of pages of at least one or more document where the search text exists wherein a highlight option is disabled.
Figure 3 illustrates a first example of pages of at least one or more document where the search text exists wherein a highlight option is enabled.
Figure 4 illustrates the first example of Figure 2 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages.
Figure 5 illustrates the second example of Figure 3 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages.
Figure 6 illustrates an example of a device comprising a processor in communication with a memory for executing the algorithm in the flow diagram illustrated in Figure 1 .
Figure 7 illustrates an example of a device suitable for searching and displaying results using cognitive pattern recognition in the flow diagram illustrated in Figure 1 .
Figure 8 illustrates a first example of a set of documents displayed from a search result.
Figure 9 illustrates a second example of a set of documents displayed from a search result.
Figure 1 0 illustrates a third example of a set of documents displayed from a search result.
Figure 1 1 illustrates a fourth example of a set of documents displayed from a search result.
DETAILED DESCRI PTION OF THE PREFERRED EMBODIMENTS
The detailed description set forth below in connection with the appended drawings is intended as a description of various aspects of the present disclosure and is not intended to represent the only aspects in which the present disclosure may be practiced. Each aspect described in this disclosure is provided merely as an example or illustration of the present disclosure, and should not necessarily be construed as preferred or advantageous over other aspects. The detailed description includes specific details for the purpose of providing a thorough understanding of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form in order to avoid obscuring the concepts of the present disclosure. Acronyms and other descriptive terminology may be used merely for convenience and clarity and are not intended to limit the scope of the present disclosure.
While for purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance with one or more aspects, occur in different orders and/or concurrently with other acts from that shown and described herein. For example, those skilled in the art will understand and appreciate that a methodology could alternatively be represented as a series of interrelated states or events, such as in a state diagram. Moreover, not all illustrated acts may be required to implement a methodology in accordance with one or more aspects.
A search may be based on not just words contained in a document, but also the user's memory of a visual image of the document and/or the approximate date of the document. For example, different documents or versions of a same document may contain many identical keywords. However, the visual presentation (i.e., display) of the first page (or any other page) of different documents or types of documents may differ. Thus, there's a need for a search & display approach that can utilize the aspects of keyword searching and visual presentation (i.e., display) of the document being searched to quickly and efficiently locate the document in a document repository (e.g., database.). For example, the human brain can quickly identify the visual pattern of a needed document(s) using cognitive pattern recognition (CPR), and distinguish between like document patterns using meta data tags displayed alongside the document display in scaled CIF. One skilled in the art would understand that a document repository may include an electronic repository or an electronic database. Figure 1 illustrates an example of a flow diagram 100 for searching and displaying results using cognitive pattern recognition. In block 1 10, search at least one document for at least one search text, wherein the at least one search text is associated with a highlight option. In one example, the highlight option allows a user to determine which search text should be differentiated from the remaining text of a document when the search text found within the document. The differentiation allows a user to quickly distinguish the search text from the rest of the remaining text. In one example, the search text with the highlight option enabled is differentiated from the remaining text of the document in one or more of the following manner: highlighted by a different color (i.e., color differentiation), bolded, italicized, underlined, etc. One skilled in the art would understand that the list of ways to "differentiate" a text from the remaining text as presented herein is not an exclusive list and that other manners of differentiating a search text may be part of the highlight option without affecting the scope and/or spirit of the present disclosure.
In one example, the highlight option includes a color differentiation (e.g., a yellow color) added to a search text. In another example, the highlight option includes varying the fonts, the mark-ups, or an added visual distinction to the search text. In yet another example, the highlight option includes adding a border around the search text. One skilled in the art would understand that the examples listed of the highlight option are not limiting and that other examples of differentiating a search text from the rest of the text on a page of a document are within the spirit and scope of the present disclosure.
In one aspect, different search text may be associated with different highlight options. For example, a first search text may be highlighted in yellow while a second search text may be bolded. One skilled in the art would understand that multiple search text may be associated with different highlight options, that is, with different examples of distinguishing the multiple search text from each.
A "search text" as used in the present disclosure may be a single word, a collection of words (i.e., a phrase of contiguous words), a symbol, a regular expression, a number, a special character and/or any combination thereof. In one aspect, the at least one search text comprises multiple search text to be searched concurrently with one or more documents. In one example, a search text is a keyword, a date or date range, a meta data, etc.
In one aspect, the at least one document is searched based on one or more of the following : an attribute, an attribute range or a special definition. For example, an attribute may be a significant identifier such as a social security number and the search might involve a single, multiple (within a range) or all SSNs within documents in a repository. For example, an attribute may be a special symbol or a special character. For example, an attribute range may be all dates within a specified range (e.g., from Jan 1 , 2000 - Dec 30, 201 0). For example, an attribute range may be all amounts found within a range (e.g., $50,000 to $1 00,000 or 1 liter to 1 000 liters, etc.) within documents. In one aspect, the special definition may be a list of predefined synonyms. In another aspect, the special definition may be a list of antonyms.
Following block 1 1 0, in block 1 20, select to enable or to disable the highlight option. In one example, the highlight option associated with one search text is enabled, such that, for example, the search text would be highlighted in yellow each time it occurs on a page of a document of a repository or database. In one example, the repository is the Internet. In another example, the repository is a private database. In one example with multiple search text, each of the search text is associated with a highlight option which may be enabled or disabled. And, in another example, multiple search text with their highlight option enabled may be differentiated differently from each other. For example, a first search text with its highlight option enabled may be bolded, a second search text with its highlight option enabled may be underlined, a third search text with its highlight option enabled may be italicized. And, another search text may have its highlight option disabled such that it is not differentiated from the remaining text (non-searched text) of the document.
In block 1 30, present a quantity of the at least one document in a scaled common image format (CI F). One skilled in the art would understand that presenting a quantity of the at least one document (as defined in block 1 30) may include presenting one or more documents.
In one aspect, common image format (CI F) is a digital representation of a document which retains the look and feel of the document in a printed form or it is a visual representation of the pages within digitally converted paper or electronically created documents. In one example, the first page of each of the quantity of the searched documents is presented in the scaled common image format (CIF). In one example, a first page of each of the quantity of the searched documents is presented in the scaled common image format (CIF). In one example, the presenting of the quantity is done in a predetermined order. And, in one example, the predetermined order is based on a meta data parameter. In one aspect, at least one meta data parameter is presented along with the scaled common image format (CIF). In another aspect, a portion of a meta data parameter is presented along with the scaled common image format (CIF). In one example, the meta data parameter is modified before being presented. In one aspect, the at least one meta data parameter is a date information. The date information, for example, may be a date the document is created, a date contained within the document, a date the document is processed, such as scanned, or a date assigned to the document, etc.
Following block 130, in block 140, display a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled. In one example, the selected amount is the pages wherein the at least one search text exists on each of the pages and wherein the search text is presented with the highlight option enabled. In one example, the selected amount is a chosen quantity of pages, and may range, for example, from a single page to multiple pages. In one example, the selected amount of pages is from a single document.
Following block 140, in block 150, add a visual distinction to one or more pages of the quantity where the at least one search text exists from the rest of the pages of each document of the quantity. In one example, the selected amount includes all the pages with the added visual distinction. In one example, the selected amount is from a single document.
One skilled in the art would understand that although the steps in blocks 1 10 through 150 are written in a particular order (the step in block 150 follows the step in block 140 which follows the step in block 130 which follows the step in block 120 which follows the step in block 1 10), the order of the steps may be interchanged without affecting the scope or spirit of the present disclosure. In one aspect, some of the steps in Figure 1 are performed by a computer, such as a personal computer. In another aspect, some of the steps in Figure 1 are performed by a handheld device that incorporates at least one processor.
Figure 2 illustrates a first example of pages of at least one or more document where the search text exists. In this example of Figure 2, the highlight option of the search text is disabled. Figure 3 illustrates a second example of pages of at least one or more document where the search text exists. In this example of Figure 3, the highlight option of the search text is enabled.
Figure 4 illustrates the first example of Figure 2 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages. As illustrated in Figure 4, the second and third pages are presented with borders. In one aspect, a user determines whether some of the pages are to be presented in the different format. Furthermore, the user may determine what the different format should be, for example, in using borders or some other different formatting. And, the user may determine the one or more criteria for some of the pages to be presented in the different format. One skilled in the art would understand that other forms of different formats, not limited to borders as illustrated herein, may be used without restricting the scope and spirit of the present disclosure.
Figure 5 illustrates the second example of Figure 3 where some of the pages are presented with a visual distinction (i.e., in a different format) than the rest of the pages. As illustrated in Figure 5, the second and third pages are presented with borders where the highlight search text is found. In one aspect, a user determines whether some of the pages are to be presented in the different format. Furthermore, the user may determine what the different format should be, for example, in using borders or some other different formatting. And, the user may determine the one or more criteria for some of the pages to be presented in the different format. One skilled in the art would understand that other forms of different formats, not limited to borders as illustrated herein, may be used without restricting the scope and spirit of the present disclosure.
In one aspect, cognitive pattern recognition is based on prior cognitive knowledge. For example, recognition is based on a collective memory about the document being searched. The cognition pattern being recognized may be based on memory of one or more of the following: file format (e.g., Word, Excel etc.), approximate date of the document (last month, last quarter, last year etc.), from and to details on correspondence/email/fax, keywords within documents, key sections within documents (e.g., pricing details within a proposal or termination clause within a contract); memory of how various digital file formats look.
In another example, recognition is based on cognitive intelligence. For example, the search is for a document that one is not familiar with, however aspects of the document are known to the searcher. In one example, the search is for a tax form, a court document or a lab report, etc., wherein each has its unique image pattern that is easily recognizable. In another example, the location of the search text (e.g., highlighted keyword(s)) within a page in common image format allows cognitive pattern recognition. Based on common image format (e.g., miniature visual display) of documents containing highlighted keyword(s), one can quickly recognize and comprehend the relevance of various documents like Correspondence, Presentations, Proposals Cost Estimates for Cleanup etc. as events on a time line or as a relevant document pertaining to an issue.
One skilled in the art would understand that the steps disclosed in the example flow diagram in Figure 1 may be interchanged in their order without departing from the scope and spirit of the present disclosure. Also, one skilled in the art would understand that the steps illustrated in the flow diagrams are not exclusive and other steps may be included or one or more of the steps in the example flow diagrams may be deleted without affecting the scope and spirit of the present disclosure.
Those of skill would further appreciate that the various illustrative components, logical blocks, modules, and/or algorithm steps described in connection with the examples disclosed herein may be implemented as electronic hardware, firmware, computer software, or combinations thereof. To clearly illustrate this interchangeability of hardware, firmware and software, various illustrative components, blocks, modules, and/or algorithm steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope or spirit of the present disclosure.
For example, for a hardware implementation, the processing units may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described therein, or a combination thereof. With software, the implementation may be through modules (e.g., procedures, functions, etc.) that perform the functions described therein. The software codes may be stored in memory units and executed by a processor unit. Additionally, the various illustrative flow diagrams, logical blocks, modules and/or algorithm steps described herein may also be coded as computer-readable instructions carried on any computer-readable medium known in the art or implemented in any computer program product known in the art.
In one or more examples, the steps or functions described herein may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer- readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer- readable media can comprise memory stick, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
In one example, the illustrative components, flow diagrams, logical blocks, modules and/or algorithm steps described herein are implemented or performed with one or more processors. In one aspect, a processor is coupled with a memory which stores data, meta data, program instructions, etc. to be executed by the processor for implementing or performing the various flow diagrams, logical blocks and/or modules described herein. Figure 6 illustrates an example of a device 600 comprising a processor 610 in communication with a memory 620 for executing the algorithm in the flow diagram illustrated in Figure 1 . In one aspect, the memory 620 is located within the processor 610. In another aspect, the memory 620 is external to the processor 610. In one aspect, the processor includes circuitry for implementing or performing the various flow diagrams, logical blocks and/or modules described herein.
Figure 7 illustrates an example of a device 700 suitable for searching and displaying results using cognitive pattern recognition in the flow diagram illustrated in Figure 1 . In one aspect, the device 700 is implemented by at least one processor comprising one or more modules configured to search using cognitive pattern recognition as described herein in blocks 710, 720, 730, 740 and 750. For example, each module comprises hardware, firmware, software, or any combination thereof. In one aspect, the device 700 is also implemented by at least one memory in communication with the at least one processor.
Figure 8 illustrates a first example of a set of documents displayed from a search result. In this first example, illustrated in Figure 8, the set of documents are displayed in a scaled common image format (CIF) with meta data information in the image tag.
Figure 9 illustrates a second example of a set of documents displayed from a search result. In this second example, the set of documents may be displayed in a scaled CIF with meta data information in the image tag. For example, in Figure 9, only the pages with the search text (e.g., keyword(s)) that are marked are displayed.
Figure 10 illustrates a third example of a set of documents displayed from a search result. In this third example, the set of documents may be displayed in a scaled CIF with meta data information in the image tag. For example, in Figure
10, the pages with all the search text (e.g., keyword(s)) found are displayed. In one example, the display includes pages with the search text the highlight option enabled as well as the search text with the highlight option disabled. In one example, the search text with the highlight option enabled is displayed differently than the search text with the highlight option disabled.
Figure 1 1 illustrates a fourth example of a set of documents displayed from a search result. In this fourth example, the set of documents may be displayed in a scaled CIF with meta data information in the image tag. For example, as illustrated in Figure 1 1 , all the pages within a document are displayed. This includes pages with the search text the highlight option enabled as well as the search text with the highlight option disabled. In one example, the search text with the highlight option enabled is displayed differently than the search text with the highlight option disabled.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the spirit or scope of the disclosure.

Claims

Claims:
1 . A method for searching and displaying using cognitive pattern recognition comprising: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
2. The method of claim 1 , wherein the selected amount is the pages wherein the at least one search text exists on each of the pages and wherein the search text is presented with the highlight option enabled.
3. The method of claim 1 further comprising adding a visual distinction to all pages of the quantity, wherein the at least one search text exists from the rest of the pages of each document of the quantity.
4. The method of claim 1 , wherein the searching at least one document is based on one or more of the following: an attribute, an attribute range or a special definition.
5. The method of claim 4, wherein the special definition is a list of predefined synonyms or a list of predefined antonyms.
6. A method for searching and displaying using cognitive pattern recognition comprising: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
7. An apparatus for searching and displaying using cognitive pattern recognition, the apparatus comprising a processor and a memory, the memory containing program code executable by the processor for performing the following: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; presenting a quantity of the at least one document in a scaled common image format (CIF); and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
8. The apparatus of claim 7, wherein the selected amount is the pages wherein the at least one search text exists on each of the pages and wherein the search text is presented with the highlight option enabled.
9. The apparatus of claim 7, wherein the memory further comprising program code for adding a visual distinction to all pages of the quantity, wherein the at least one search text exists from the rest of the pages of each document of the quantity.
10. An apparatus for searching and displaying using cognitive pattern recognition, the apparatus comprising a processor and a memory, the memory containing program code executable by the processor for performing the following: searching at least one document for at least one search text, wherein the at least one search text is associated with a highlight option; selecting to enable or to disable the highlight option; and displaying a selected amount of pages in the scaled common image format (CIF), wherein the at least one search text is shown according to whether the highlight option is enabled or disabled.
PCT/US2012/060467 2011-10-24 2012-10-16 Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within WO2013062814A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP12844445.2A EP2771781A4 (en) 2011-10-24 2012-10-16 Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within
CN201280059083.0A CN103959232B (en) 2011-10-24 2012-10-16 For the apparatus and method of search result to be shown using cognitive pattern recognition in locating documents and information therein

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US13/280,281 2011-10-24
US13/280,281 US10467273B2 (en) 2011-10-24 2011-10-24 Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within

Publications (1)

Publication Number Publication Date
WO2013062814A1 true WO2013062814A1 (en) 2013-05-02

Family

ID=48136858

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2012/060467 WO2013062814A1 (en) 2011-10-24 2012-10-16 Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within

Country Status (4)

Country Link
US (1) US10467273B2 (en)
EP (1) EP2771781A4 (en)
CN (2) CN108509623A (en)
WO (1) WO2013062814A1 (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10956475B2 (en) 2010-04-06 2021-03-23 Imagescan, Inc. Visual presentation of search results
US11010432B2 (en) 2011-10-24 2021-05-18 Imagescan, Inc. Apparatus and method for displaying multiple display panels with a progressive relationship using cognitive pattern recognition
US9772999B2 (en) 2011-10-24 2017-09-26 Imagescan, Inc. Apparatus and method for displaying multiple display panels with a progressive relationship using cognitive pattern recognition
US10467273B2 (en) 2011-10-24 2019-11-05 Image Scan, Inc. Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within
EP3602321B1 (en) * 2017-09-13 2023-09-13 Google LLC Efficiently augmenting images with related content
US11645295B2 (en) 2019-03-26 2023-05-09 Imagescan, Inc. Pattern search box

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7373612B2 (en) * 2002-10-21 2008-05-13 Battelle Memorial Institute Multidimensional structured data visualization method and apparatus, text visualization method and apparatus, method and apparatus for visualizing and graphically navigating the world wide web, method and apparatus for visualizing hierarchies
US7596574B2 (en) * 2005-03-30 2009-09-29 Primal Fusion, Inc. Complex-adaptive system for providing a facted classification
US20100246884A1 (en) * 2009-03-27 2010-09-30 Shoupu Chen Method and system for diagnostics support
US20110218990A1 (en) * 2002-06-12 2011-09-08 Jordahl Jena J Data storage, retrieval, manipulation and display tools enabling multiple hierarchical points of view
US20110246453A1 (en) * 2010-04-06 2011-10-06 Krishnan Basker S Apparatus and Method for Visual Presentation of Search Results to Assist Cognitive Pattern Recognition
US20110258049A1 (en) * 2005-09-14 2011-10-20 Jorey Ramer Integrated Advertising System

Family Cites Families (67)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6507872B1 (en) 1992-09-25 2003-01-14 David Michael Geshwind Class of methods for improving perceived efficiency of end-user interactive access of a large database such as the world-wide web via a communication network such as “The Internet”
US5692176A (en) 1993-11-22 1997-11-25 Reed Elsevier Inc. Associative text search and retrieval system
US5995976A (en) 1996-10-11 1999-11-30 Walker Asset Management Limited Partnership Method and apparatus for distributing supplemental information related to printed articles
US7146381B1 (en) 1997-02-10 2006-12-05 Actioneer, Inc. Information organization and collaboration tool for processing notes and action requests in computer systems
US6029171A (en) 1997-02-10 2000-02-22 Actioneer, Inc. Method and apparatus for group action processing between users of a collaboration system
US6184885B1 (en) * 1998-03-16 2001-02-06 International Business Machines Corporation Computer system and method for controlling the same utilizing logically-typed concept highlighting
US6834276B1 (en) 1999-02-25 2004-12-21 Integrated Data Control, Inc. Database system and method for data acquisition and perusal
US6665838B1 (en) 1999-07-30 2003-12-16 International Business Machines Corporation Web page thumbnails and user configured complementary information provided from a server
US6968332B1 (en) * 2000-05-25 2005-11-22 Microsoft Corporation Facility for highlighting documents accessed through search or browsing
CA2340531C (en) 2001-03-12 2006-10-10 Ibm Canada Limited-Ibm Canada Limitee Document retrieval system and search method using word set and character look-up tables
NO316480B1 (en) 2001-11-15 2004-01-26 Forinnova As Method and system for textual examination and discovery
US8635531B2 (en) * 2002-02-21 2014-01-21 Ricoh Company, Ltd. Techniques for displaying information stored in multiple multimedia documents
US7225407B2 (en) 2002-06-28 2007-05-29 Microsoft Corporation Resource browser sessions search
US7418661B2 (en) 2002-09-17 2008-08-26 Hewlett-Packard Development Company, L.P. Published web page version tracking
CN1701343A (en) 2002-09-20 2005-11-23 德克萨斯大学董事会 Computer program products, systems and methods for information discovery and relational analyses
US7194693B2 (en) * 2002-10-29 2007-03-20 International Business Machines Corporation Apparatus and method for automatically highlighting text in an electronic document
CN1300718C (en) * 2002-10-31 2007-02-14 卡西欧计算机株式会社 Information display device and information display processing program
US7747428B1 (en) * 2003-09-24 2010-06-29 Yahoo! Inc. Visibly distinguishing portions of compound words
ATE496141T1 (en) 2003-12-06 2011-02-15 Abbott Lab METHOD AND SYSTEM FOR ANALYZING REACTIONS USING AN INFORMATION SYSTEM
US7707210B2 (en) * 2003-12-18 2010-04-27 Xerox Corporation System and method for multi-dimensional foraging and retrieval of documents
US20080065636A1 (en) 2003-12-31 2008-03-13 Miller Arthur O Method for storing and retrieving data objects
US8150824B2 (en) 2003-12-31 2012-04-03 Google Inc. Systems and methods for direct navigation to specific portion of target document
US8612208B2 (en) * 2004-04-07 2013-12-17 Oracle Otc Subsidiary Llc Ontology for use with a system, method, and computer readable medium for retrieving information and response to a query
WO2006042142A2 (en) 2004-10-07 2006-04-20 Bernard Widrow Cognitive memory and auto-associative neural network based pattern recognition and searching
US20060080292A1 (en) * 2004-10-08 2006-04-13 Alanzi Faisal Saud M Enhanced interface utility for web-based searching
EP1800223A4 (en) 2004-10-14 2008-11-19 Onstream Systems Ltd A process for electronic document redaction
US7512892B2 (en) * 2005-03-04 2009-03-31 Microsoft Corporation Method and system for displaying and interacting with paginated content
US7773822B2 (en) 2005-05-02 2010-08-10 Colormax, Inc. Apparatus and methods for management of electronic images
US20060277167A1 (en) * 2005-05-20 2006-12-07 William Gross Search apparatus having a search result matrix display
US8417697B2 (en) * 2005-08-22 2013-04-09 Google Inc. Permitting users to remove documents
US8627222B2 (en) * 2005-09-12 2014-01-07 Microsoft Corporation Expanded search and find user interface
US7689933B1 (en) 2005-11-14 2010-03-30 Adobe Systems Inc. Methods and apparatus to preview content
WO2007082308A2 (en) * 2006-01-13 2007-07-19 Bluespace Software Corp. Determining relevance of electronic content
US7644373B2 (en) * 2006-01-23 2010-01-05 Microsoft Corporation User interface for viewing clusters of images
US8725729B2 (en) * 2006-04-03 2014-05-13 Steven G. Lisa System, methods and applications for embedded internet searching and result display
US8935290B2 (en) * 2006-05-03 2015-01-13 Oracle International Corporation User interface features to manage a large number of files and their application to management of a large number of test scripts
US8661031B2 (en) * 2006-06-23 2014-02-25 Rohit Chandra Method and apparatus for determining the significance and relevance of a web page, or a portion thereof
US20100299201A1 (en) * 2006-06-30 2010-11-25 Steven Thrasher Searching data storage systems and devices
US7991769B2 (en) 2006-07-07 2011-08-02 Yahoo! Inc. System and method for budgeted generalization search in hierarchies
US7689613B2 (en) 2006-10-23 2010-03-30 Sony Corporation OCR input to search engine
US8296808B2 (en) 2006-10-23 2012-10-23 Sony Corporation Metadata from image recognition
US8209605B2 (en) 2006-12-13 2012-06-26 Pado Metaware Ab Method and system for facilitating the examination of documents
US20080263022A1 (en) * 2007-04-19 2008-10-23 Blueshift Innovations, Inc. System and method for searching and displaying text-based information contained within documents on a database
US20090228777A1 (en) 2007-08-17 2009-09-10 Accupatent, Inc. System and Method for Search
CA2697948A1 (en) 2007-08-31 2009-03-05 Papier Virtuel Inc./Virtual Paper Inc. System and method for the automated creation of a virtual publication
US7870130B2 (en) * 2007-10-05 2011-01-11 International Business Machines Corporation Techniques for identifying a matching search term in an image of an electronic document
US20090158181A1 (en) 2007-12-18 2009-06-18 Mellmo Llc User interface method and apparatus to navigate a document file
JP5167821B2 (en) * 2008-01-11 2013-03-21 株式会社リコー Document search apparatus, document search method, and document search program
CN101216837A (en) * 2008-01-18 2008-07-09 索意互动(北京)信息技术有限公司 Method and system for displaying search result based on matching user personalized configuration
US8078630B2 (en) * 2008-02-22 2011-12-13 Tigerlogic Corporation Systems and methods of displaying document chunks in response to a search request
US8924421B2 (en) * 2008-02-22 2014-12-30 Tigerlogic Corporation Systems and methods of refining chunks identified within multiple documents
US8200649B2 (en) 2008-05-13 2012-06-12 Enpulz, Llc Image search engine using context screening parameters
US20090313352A1 (en) 2008-06-11 2009-12-17 Christophe Dupont Method and System for Improving the Download of Specific Content
US8259124B2 (en) * 2008-11-06 2012-09-04 Microsoft Corporation Dynamic search result highlighting
US8244755B2 (en) 2009-06-29 2012-08-14 International Business Machines Corporation Search engine optimization using page anchors
US20110035383A1 (en) * 2009-08-06 2011-02-10 Ghimire Shankar R Advanced Text to Speech Patent Search Engine
WO2011044578A1 (en) * 2009-10-11 2011-04-14 Patrick Walsh Method and system for performing classified document research
US20110119262A1 (en) * 2009-11-13 2011-05-19 Dexter Jeffrey M Method and System for Grouping Chunks Extracted from A Document, Highlighting the Location of A Document Chunk Within A Document, and Ranking Hyperlinks Within A Document
US9047283B1 (en) * 2010-01-29 2015-06-02 Guangsheng Zhang Automated topic discovery in documents and content categorization
US20110295879A1 (en) 2010-05-27 2011-12-01 Neuone, Llc Systems and methods for document management
US20130124515A1 (en) * 2010-07-23 2013-05-16 Foundationip Llc Method for document search and analysis
US20120078979A1 (en) * 2010-07-26 2012-03-29 Shankar Raj Ghimire Method for advanced patent search and analysis
US20120150861A1 (en) * 2010-12-10 2012-06-14 Microsoft Corporation Highlighting known answers in search results
US20120226500A1 (en) * 2011-03-02 2012-09-06 Sony Corporation System and method for content rendering including synthetic narration
US10467273B2 (en) 2011-10-24 2019-11-05 Image Scan, Inc. Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within
US9196075B2 (en) * 2011-11-14 2015-11-24 Microsoft Technology Licensing, Llc Animation of computer-generated display components of user interfaces and content items
US9092428B1 (en) * 2011-12-09 2015-07-28 Guangsheng Zhang System, methods and user interface for discovering and presenting information in text content

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110218990A1 (en) * 2002-06-12 2011-09-08 Jordahl Jena J Data storage, retrieval, manipulation and display tools enabling multiple hierarchical points of view
US7373612B2 (en) * 2002-10-21 2008-05-13 Battelle Memorial Institute Multidimensional structured data visualization method and apparatus, text visualization method and apparatus, method and apparatus for visualizing and graphically navigating the world wide web, method and apparatus for visualizing hierarchies
US7596574B2 (en) * 2005-03-30 2009-09-29 Primal Fusion, Inc. Complex-adaptive system for providing a facted classification
US20110258049A1 (en) * 2005-09-14 2011-10-20 Jorey Ramer Integrated Advertising System
US20100246884A1 (en) * 2009-03-27 2010-09-30 Shoupu Chen Method and system for diagnostics support
US20110246453A1 (en) * 2010-04-06 2011-10-06 Krishnan Basker S Apparatus and Method for Visual Presentation of Search Results to Assist Cognitive Pattern Recognition

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
ANTIQUEIRA ET AL.: "A complex network approach to text summarization", INFORMATION SCIENCES, vol. 179, no. 5, 15 February 2009 (2009-02-15), pages 584 - 599, XP025804827, Retrieved from the Internet <URL:http://www.sciencedirect.com/science/article/pü/S0020025508004520> [retrieved on 20121130] *
See also references of EP2771781A4 *
YOUGUO ET AL.: "The Frame of Cognitive Pattern Recognition", PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, 26 July 2007 (2007-07-26), pages 694 - 696, XP031145831, Retrieved from the Internet <URL:http://mysharing.googlecode.com/svn/trunk/paper/795431252057723.pdf> [retrieved on 20121130] *

Also Published As

Publication number Publication date
US20130103707A1 (en) 2013-04-25
CN108509623A (en) 2018-09-07
EP2771781A1 (en) 2014-09-03
EP2771781A4 (en) 2015-06-17
CN103959232A (en) 2014-07-30
US10467273B2 (en) 2019-11-05
CN103959232B (en) 2018-03-09

Similar Documents

Publication Publication Date Title
US10459984B2 (en) Apparatus and method for displaying multiple display panels with a progressive relationship using cognitive pattern recognition
US20230161787A1 (en) Systems and method for generating a structured report from unstructured data
US8219566B2 (en) System and method for determining valid citation patterns in electronic documents
US10467273B2 (en) Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within
US20190042628A1 (en) Similar document identification using artificial intelligence
US11669575B2 (en) Apparatus and method for displaying multiple display panels with a progressive relationship using cognitive pattern recognition
US9501455B2 (en) Systems and methods for processing data
US20210182325A1 (en) Visual Presentation of Search Results
US20110246453A1 (en) Apparatus and Method for Visual Presentation of Search Results to Assist Cognitive Pattern Recognition
US20150026159A1 (en) Digital Resource Set Integration Methods, Interfaces and Outputs
WO2021055102A1 (en) Cross-document intelligent authoring and processing assistant
US20200019547A1 (en) Apparatus and method for displaying search results using cognitive pattern recognition in locating documents and information within
AU2008252019A1 (en) System and method for creating a database
US11100151B2 (en) Interactive patent visualization systems and methods
Blythe et al. Resource description and access: It’s really not so bad
Traill Quality issues in vendor-provided e-monograph records
Beals Stuck in the Middle: Developing Research Workflows for a Multi-Scale Text Analysis
EP3156918A1 (en) Visual presentation of search results
Campagnolo Errata (per oculos) corrige: Visual identification of meaningless data in database records of bookbinding structures
Stertzer Foundations for digital editing, with focus on the documentary tradition
Hawkins et al. RDA and Serials: Transitioning to RDA Within a MARC 21 Framework
Koutela Data analysis from the Greek National Catalogue of Services with the use of KNIME
WO2024041745A1 (en) Artificial intelligence-based system and method for improving speed and quality of work on literature reviews
WO2015199581A2 (en) Method for preliminary conversion of initial mass of data, method for forming map of connections between components of parts of logical constructs of a converted structured initial mass of data, method for searching a converted mass of data using a component connections map, and systems and devices for implementing said methods

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 12844445

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: 2012844445

Country of ref document: EP

NENP Non-entry into the national phase

Ref country code: DE