JP2009151627A - Information association system, information association method and information association program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately associate related pieces of information with one another. <P>SOLUTION: This information association system comprises a keyword importance determining means for extracting a keyword on the basis of an operation history and determining a degree of importance of the extracted keyword, an access information importance determining means for extracting the accessed information on the basis of the operation history and determining a degree of importance of the extracted accessed information, a specifying means for specifying the information including the keyword from the information extracted and accessed by the accessed information importance determining means, and an associating means for associating the information including the keyword specified by the specifying means on the basis of the degree of importance of the keyword determined by the keyword importance determining means, and the degree of importance of the accessed information determined by the accessed information importance determining means. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an information association system, an information association method, and an information association program for associating information.

  By automatically associating multiple pieces of information used during a certain work and storing the related information, and by automatically searching for related information, it is possible to save time and to reuse information. This is an important technology for effective use of information.

  A method for automatically associating information from a user's operation history is described in Patent Document 1. FIG. 17 is a block diagram illustrating a configuration example of a file relation acquisition device described in Patent Document 1. The file-related acquisition device shown in FIG. 17 includes a file access device 15, a file access monitoring device 16, and a file storage device 14.

  The file access monitoring device 16 collects file editing information including the editing start date and time, the editing end date and time, the total visible time information, and the storage history for the file in the file storage device 14 opened by the file access device 15. Next, a file having a storage history is extracted from the collected file editing information as an editing target file.

  For the extracted editing target file, based on the editing start time information and editing end time information, the file name and visible time of one or more other reference files that were open during the time that the editing target file was open Get cumulative information. Further, the file name of the acquired reference file and the total visible time information are registered as related file information in association with the file to be edited. In addition, it is assumed that a long-viewable cumulative time is strongly related.

  Patent Document 2 describes a method of automatically extracting a search term from a user input history, automatically searching for a related document, and displaying it. FIG. 18 is a block diagram illustrating a configuration example of an electronic file search device described in Patent Document 2. The electronic file search apparatus shown in FIG. 18 sequentially determines whether or not a character input unit 110 for inputting a character string or an editing operation for creating or editing a document, and whether the input character satisfies a predetermined condition. If the determination unit 120 determines that the determination unit 120 satisfies the condition, the search word extraction unit 130 extracts a search word from the input character string, and the search word extracted by the search word extraction unit 130 is used. A search unit 140 that searches the document database and a result display unit 150 that displays search results searched by the search unit 140 are provided. The search unit 140 calculates, for each document, a weighted sum of the number of search words in the text of the search result and the number of appearances thereof, and the result display unit 150 displays the result in descending order of the total value.

JP 2006-293936 A JP 2005-173999 A

  However, in the method described in Patent Document 1, in order to associate the ones that were open at the same time, if there were a plurality of work in parallel, or if another work was interrupted in the middle of a certain work, When there is information that is displayed regardless of the edge of the screen, irrelevant information is associated. Moreover, it is not associated unless it is opened at the same time. Therefore, it is not always possible to correctly associate related information.

  Further, in the method described in Patent Document 2, when a general word becomes a search word, the number of appearances is used for weighting the search word, so that there is a possibility that the general word comes to the top of the search result. Because it is high, there is a possibility that unrelated files may be ranked higher in the search result ranking. Further, since all document DBs are searched, information that is not used and not very useful is also displayed in the search results. Therefore, it is not always possible to correctly associate related information.

  Accordingly, an object of the present invention is to provide an information association system, an information association method, and an information association program that can correctly associate related information.

  An information association system according to the present invention detects a keyword based on an operation history, detects a keyword importance level determination unit that determines the importance level of the detected keyword, and detects and detects accessed information based on the operation history. An access information importance determining means for determining the importance of accessed information, a specifying means for specifying information including a keyword from the accessed information detected by the access information importance determining means, and a keyword importance determining means. An association means for associating information including the keyword specified by the specifying means based on the determined importance of the keyword and the importance of the accessed information determined by the access information importance determining means To do.

  An information association method according to the present invention detects a keyword based on an operation history, detects a keyword importance level determining step for determining the importance level of the detected keyword, and detects and detects accessed information based on the operation history. An access information importance determining step for determining the importance of accessed information, a specifying step for identifying information including a keyword from the accessed information detected in the access information importance determining step, and a keyword importance determining step. An association step for associating information including the keyword specified in the specific step based on the determined importance of the keyword and the importance of the accessed information determined in the access information importance determination step .

  An information association program according to the present invention detects a keyword on a computer based on an operation history, detects keyword importance based on an operation history, and detects accessed information based on an operation history. An access information importance determination process for determining the importance of the detected accessed information, a specifying process for identifying information including a keyword from the accessed information detected in the access information importance determination process, and a keyword importance Based on the importance level of the keyword determined in the determination process and the importance level of the accessed information determined in the access information importance level determination process, an association process for associating information including the keyword specified in the specific process is executed. It is characterized by.

  According to the present invention, there is an effect that related information can be correctly associated.

  First, an outline of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a minimum configuration example of an information association system according to the present invention. The information association system illustrated in FIG. 1 includes a keyword importance level determination unit 21, an access information importance level determination unit 41, a specifying unit 61, and an association unit 62.

  The keyword importance determination means 21 detects a keyword based on the operation history, and determines the importance of the detected keyword.

  The access information importance level determination unit 41 detects accessed information based on the operation history, and determines the importance level of the detected accessed information.

  The specifying unit 61 specifies information including a keyword from the accessed information detected by the access information importance level determining unit 41.

  The associating means 62 determines the keyword specified by the specifying means 61 based on the importance of the keyword determined by the keyword importance determining means 21 and the importance of the accessed information determined by the access information importance determining means 41. Associate information to include.

  If configured as shown in FIG. 1, related information can be correctly associated.

  Next, embodiments of the present invention will be described with reference to the drawings. FIG. 2 is a block diagram showing a configuration example of an information association system according to the present invention. The information association system shown in FIG. 2 includes a user operation monitoring unit 10, a keyword importance level determination unit 20, a keyword DB (database) 30, an access information importance level determination unit 40, an access information DB (database) 50, A related analysis generation means 60 and a related storage DB (database) 70 are provided. The information association system is realized by an information processing apparatus such as a personal computer (PC) that operates according to a program.

  The user operation monitoring means 10 collects user operation histories for a set period. The user operation monitoring unit 10 generates keyword information from the collected history, and transmits (outputs) the keyword information to the keyword importance level determination unit 20.

  FIG. 3 is an explanatory diagram illustrating an example of keyword information. As shown in FIG. 3, the keyword information is information including a “detected character string” indicating a character string detected as a keyword and a “detected place” indicating a place where the character string is detected. The “detected location” indicating the location where the character string is detected is information indicating the location where the keyword is input, such as a document file, a clipboard other than the document file, and an application such as a search tool. The user operation monitoring means 10 generates keyword information by extracting information indicating a keyword and a place where the keyword is input from the operation history.

  In addition, the user operation monitoring unit 10 generates access information from the collected history and outputs the access information to the access information importance level determination unit 40.

  FIG. 4 is an explanatory diagram illustrating an example of access information. As shown in FIG. 4, the access information is information including “location of detection information”, “presence / absence of editing history”, “number of display times”, and “display time” indicating accessed information. The “location of detection information” indicating the accessed information is, for example, a path or URL of a file or directory. The user operation monitoring means 10 generates “access information” by extracting “location of detection information”, “presence / absence of editing history”, “display count” and “display time” from the operation history.

  The keyword importance level determination unit 20 receives the keyword information from the user operation monitoring unit 10 and determines the importance level of the keyword (“detected character string”) based on the “detected place” included in the keyword information. The keyword and the importance are stored in the keyword DB 30 in the format as shown in FIG.

  FIG. 5 is an explanatory diagram illustrating an example of information stored in the keyword DB 30. As shown in FIG. 5, the keyword DB 30 stores information including “keyword” and “importance”. The “keyword” is the same information as the “detected character string” included in the keyword information. The “importance” corresponding to the “keyword” stored in the keyword DB 30 may be expressed as “keyword importance” or “keyword importance”.

  The access information importance level determination means 40 determines the importance level for each “location of detection information” based on “edit history presence / absence”, “display count”, and “display time” included in the input access information. The access information importance level determination means 40 stores the location of the detection information and the importance level of the information in the access information DB 50 in the format shown in FIG.

  FIG. 6 is an explanatory diagram illustrating an example of information stored in the access information DB 50. As illustrated in FIG. 6, the access information DB 50 stores information including “location of detection information” and “importance”. The “location of detection information” is the same information as the “location of detection information” included in the access information. The “importance” corresponding to “location of detection information” stored in the access information DB 50 may be expressed as “importance of access information” or “importance of access information”.

  The related analysis generation means 60 searches the information in the location written in the “location of detection information” stored in the access information DB 50 with the “keyword” stored in the keyword DB 30, and specifies information including the keyword.

  Further, the relation analysis generation means 60 determines whether to associate the identified information and which information is to be associated with which information based on the importance of the keyword and the importance of the access information. The related analysis generation means 60 stores information (related information) determined to be related to the related storage DB 70 in the format shown in FIG. The association analysis generation means 60 associates information including keywords based on, for example, a predetermined rule that associates the importance of keywords with the importance of access information.

  FIG. 7 is an explanatory diagram illustrating an example of information stored in the related storage DB 70. As shown in FIG. 7, the related storage DB 70 stores information including “access information path”, “related access information path”, and “keyword”. The related analysis generation means 60 stores the information determined to be related in the related storage DB 70 as “access information path” and “related access information path”. Further, the “keyword” used for the search is stored in association with the “access information path” and the “related access information path”.

  Next, the operation of the present embodiment will be described with reference to the drawings.

  First, the operation of the user operation monitoring unit 10 will be described with reference to FIG. FIG. 8 is a flowchart showing the operation of the user operation monitoring means 10.

  For example, the user operation monitoring unit 10 is activated at the same time when the PC is activated, and starts monitoring user operations (step S11). The user operation monitoring means 10 detects the user's character string operation (step S12), and further detects the place where the character string is operated (step S13). Then, the user operation monitoring unit 10 transmits (outputs) the detected character string and data (keyword information) indicating the place where the character string is operated (detected) to the keyword importance level determining unit 20 (step S14). .

  The character string operation is, for example, an operation such as character input from a keyboard or copy and paste of a character string. The operated location is, for example, a file name, a search tool, a clipboard, or the like.

  Next, the user operation monitoring unit 10 detects access to the information by the user (step S15), and collects the location of the detection information, the presence / absence of the editing history, the number of display times, and the display time for the detected information. It outputs to the access information importance determination means 40 (step S16).

  Next, the operation of the keyword importance level judging means 20 will be described with reference to FIG. FIG. 9 is a flowchart showing the operation of the keyword importance level judging means 20.

  The keyword importance level determination unit 20 is activated at the same time as the PC is activated, for example. Alternatively, it may be activated by the user operation monitoring means 10. The keyword importance determination unit 20 receives (inputs) data (keyword information) from the user operation monitoring unit 10 (step S21).

  Next, the keyword importance determination means 20 determines the importance of the character string as a keyword from the location where the character string is detected (step S22). That is, the keyword importance level determination means 20 determines the importance level of the “detected character string” based on the “detected place” included in the input keyword information. For example, the keyword importance level determination means 20 determines the importance level according to a predetermined rule. The keyword importance determination means 20 stores the “keyword” and the “importance” of the keyword in the keyword DB 30 (step S23).

  Next, the operation of the access information importance level determination means 40 will be described with reference to FIG. FIG. 10 is a flowchart showing the operation of the access information importance level judging means 40.

  The access information importance level determination means 40 is activated at the same time when the PC is activated, for example. Alternatively, it may be activated by the user operation monitoring means 10. The access information importance level determination unit 40 receives data (access information) from the user operation monitoring unit 10 (step S31).

  Next, the access information importance level determination means 40 determines the importance level of the access information from the presence / absence of the edit history of the access information, the number of display times, and the display time (step S32). That is, the access information importance level determination means 40 determines the importance level for each “location of detection information” based on “edit history presence / absence”, “number of display times”, and “display time” included in the input access information. To do. The access information importance level determination means 40 stores the “location of detection information” indicating the path of the information and the obtained “importance level” in the access information DB 50 (step S33).

  Next, the operation of the related analysis generation means 60 will be described with reference to FIG. FIG. 11 is a flowchart showing the operation of the relation analysis generation means 60.

  The association analysis generation unit 60 is activated at the same time when the PC is activated, for example. The related analysis generation means 60 acquires (extracts) “keyword” and its “importance” from the keyword DB 30 at regular intervals (step S41). The related analysis generation means 60 searches the information in the collection path (“location of detection information”) stored in the access information DB 50 using the extracted “keyword” as a search key, and acquires the search result (step) S42). In step S42, the relation analysis generation unit 60 extracts “location of detection information” and “importance” indicating the location of information including “keyword”, for example, as a search result.

  Next, the related analysis generation means 60 has a high importance level among the access information stored in the access information DB 50 (for example, “detection information whose corresponding“ importance level ”is“ high ”or“ medium ”). If there is a place ")", it is confirmed whether the information already exists in the related storage DB 70 or not. If it exists, the information keyword (for example, “keyword” stored in the related storage DB 70) is searched for other information in the collection path (“location of detected information”) stored in the access information DB 50, and the search result Is acquired (step S43).

  For example, the related analysis generation means 60 searches for “access information path” and “related access information path” in the related storage DB 70 with “location of detected information” whose corresponding “importance” is “high” or “medium”. And corresponding keywords are extracted. Then, using the keyword extracted from the related storage DB 70 as a search key, the related analysis generation unit 60 searches information in “location of detected information” in the access information DB 50 and acquires a search result.

  In step S43, the relation analysis generation means 60 extracts, for example, a plurality of combinations of “location of detection information” and “importance” as search results.

  The association analysis generation means 60 associates the search result information in consideration of the importance of the keyword information and the importance of the access information, and stores it in the association DB (step S44). That is, the relation analysis generation means 60 uses a plurality of “detections” searched in steps S42 and S43 according to the “importance” (keyword importance) corresponding to the “keyword” used as the search key in steps S42 and S43. Decide how to associate the “location of information”.

  For example, if the importance level of the keyword is “high”, the relation analysis generation unit 60 associates all the searched “locations of detection information” with each other regardless of the importance level of the access information.

  Further, when the importance level of the keyword is “medium”, the relation analysis generation means 60 has a corresponding importance level of “medium” or “high” among the searched “locations of detection information”. Associate each other, and do not associate the corresponding importance level “low”.

  When the importance level of the keyword is “low”, the related analysis generation unit 60 determines whether the corresponding importance level is “low” or “medium” among the searched “locations of detection information”. , And the corresponding importance level is “medium” and “high”. Here, when there is no “location of detection information” having a corresponding importance level of “medium”, a corresponding importance level of “low” is associated with a “high” level. In addition, the corresponding importance levels are “high”.

  That is, the relation analysis generation means 60 associates “location of detected information” searched based on the keyword according to the importance of the keyword and the importance of the access information.

  Next, the operation of this embodiment will be described using a specific example.

  Assume that the user operation monitoring means 10 monitors character string operations during a certain day, collects data (keyword information) shown in FIG. FIG. 12 is an explanatory diagram illustrating an example of keyword information.

  Further, it is assumed that the user operation monitoring unit 10 monitors access to user information during the same period, collects data (access information) shown in FIG. 13, and sends it to the access information importance level determination unit 40. FIG. 13 is an explanatory diagram illustrating an example of access information.

  Keyword 1 is a character string input as a search key to the Web search tool. Based on the operation history indicating that the user has input the character string Keyword1 to the Web search tool, the user operation monitoring means 10 has “Detected character string” as “Keyword1” and “Detected location” is “ The keyword information “input to the search tool” is generated (see FIG. 12).

  Further, as a result of searching by inputting Keyword1 as a search key into the Web search tool, the Web pages are http: // websiteA /, http: // websiteB /, http: // websiteC /, and http: // websiteD. Suppose / is searched. Based on the operation history indicating that the user has accessed the retrieved Web page, the user operation monitoring unit 10 sets “extraction information location” to http: // websiteA /, http: // websiteB /, http: // Access information such as websiteC / and http: // websiteD / is generated (see FIG. 13).

  Also, it is assumed that Keyword1 is a character string included in the “C: \ A project specification”, and the user has performed a Web search to examine Keyword1.

  Keyword 3 is a character string obtained by copying and pasting a part of “D: \ A project plan” shown in FIG. 13 into “C: \ A project specification”. That is, Keyword3 is a character string included in the files “D: \ A project plan” and “C: \ A project specification”.

  The user operation monitoring means 10 is based on the operation history indicating that the user has copied the character string Keyword3 included in the file “D: \ A project plan” and pasted the file “C: \ A project specification”. Keyword information and access information are generated. The keyword information is information in which “detected character string” is “Keyword3” and “detected location” is “clipboard” (see FIG. 12). Also, the access information is “location of extracted information”. "Is the information" D: \ A project plan "and" C: \ A project specification "(see FIG. 13).

  Keyword 4 is a character string input by the user as a search key to the file search tool in order to search for the “C: \ B project member table” shown in FIG. That is, Keyword4 is a character string input as a search key to the file search tool. Based on the operation history indicating that the user has input the character string Keyword4 to the file search tool, the user operation monitoring means 10 has “Detected character string” as “Keyword4” and “Detected location” is “ The keyword information “input to the search tool” is generated (see FIG. 12).

  Keyword 4 is a character string included in the files “C: \ B project schedule” and “C: \ B project member table”.

  In addition, “C: \ A Project Specification 2nd Edition” is an edited version of “C: \ A Project Specification” that has been renamed and saved. Version "and" C: \ A Project Specification "are not opened at the same time. Based on the operation history indicating that the user has accessed the files “C: \ A project specification” and “C: \ A project specification second edition”, the user operation monitoring means 10 determines “location of extracted information”. Is generated as “C: \ A Project Specification” and “C: \ A Project Specification Second Edition” (see FIG. 13).

  The keyword importance level determination unit 20 receives data (keyword information) and determines the importance level of the keyword information based on the “detected place” included in the keyword information. Here, for example, it is assumed that the importance is determined in three stages of high, medium, and low. For example, since what is copied to the clipboard can be regarded as being copied and pasted between information, it is regarded as an important keyword and the importance is increased. The input to the search tool is an important keyword, but it is determined that the importance is lower than that of the clipboard, and the importance is medium. Others are less important. As a result, the keyword importance level determination means 20 generates data as shown in FIG. 14 and stores it in the keyword DB 30. FIG. 14 is an explanatory diagram illustrating an example of registration in the keyword DB 30.

  For example, the access information importance level determination unit 40 determines the importance level of access information in three stages of high, medium, and low. For example, it is determined that the importance of an editing history is high, the importance of the display is 5 or more, or the importance of the display time of 10 minutes or more is medium, and the others are low, and is shown in FIG. Such data is generated and stored in the access information DB 50. FIG. 15 is an explanatory diagram illustrating an example of registration in the access information DB 50.

  Next, the association analysis generation means 60 searches the data in the collection location (“location of detection information”) in the access information DB 50 using the keyword stored in the keyword DB 30 as a key, and associates the information of the search result.

  For example, the relation analysis generation means 60 associates all the search results (“detection information location”) searched for with a keyword having a high keyword importance, regardless of the access information importance.

  In addition, for example, the relation analysis generation means 60 associates the access information importance levels that are medium or higher among the search results ("location of detection information") with the keyword having a medium keyword importance level, and accesses information importance level Do not associate low grades.

  For example, the relation analysis generation means 60 associates a search result with a keyword having a low keyword importance level (“location of detected information”) with a low access information importance level with the information in the access information importance level. Associates the medium degree information with the high access information importance degree information. If there is no “detection information location” having a medium access information importance level, the related analysis generation means 60 selects information with a low access information importance level (“detection information location”) and a high access information importance level. Information ("location of detection information"). Further, it is assumed that the relation analysis generation means 60 determines that information with high access information importance (“location of detection information”) is associated with each other.

  For example, as a result of searching for information existing in “location of detection information” stored in the access information DB 50 using Keyword 1 as a key, the relation analysis generation unit 60 results in “C: \ A project specification”, “C: \ "A project specification second edition", "http: // websiteA /", "http: // websiteB /", "http: // websiteC /", and "http: // websiteD /" are extracted.

  The association analysis generation means 60 associates “C: \ A project specification” having a high access information importance level with “http: // websiteA /” having a medium access importance level in accordance with the determination rule described above. "C: \ A project specification" with high importance and "http: // websiteD /" with medium access importance are related, and "C: \ A project specification second with high access information importance" Version ”is associated with“ http: // websiteA / ”with medium access importance,“ C: \ A Project Specification Second Edition ”with high access information importance, and“ http: Associate // websiteD / ”. Also, the “C: \ A project specification” having a high access information importance level is associated with the “C: \ A project specification second edition” having a high access information importance level. That is, the association analysis generation means 60 associates information based on a determination rule that associates the importance of keywords with the importance of access information.

  Next, the relation analysis generation means 60 searches for information existing in “location of detection information” stored in the access information DB 50 using Keyword 3 as a key, and a part of “D: \ A project plan” and “ C: \ A Project Specification "is extracted. The association analysis generation means 60 associates “D: \ A project plan” with “C: \ A project specification” in accordance with the above rules.

  Next, the association analysis generation means 60 searches for information existing in “location of detection information” stored in the access information DB 50 using Keyword 4 as a key, and performs “C: \ B project schedule” and “C: \ B Extract project member table. The association analysis generation means 60 associates the “C: \ B project schedule” with the “C: \ B project member table” in accordance with the above association rules.

  Note that Keyword2, Keyword5, and Keyword6 have 0 search results. Like “http: // portalZ /” (see FIG. 13), even if it has been displayed for a long time, it is not associated if there is no relevant information. As a result, related data as shown in FIG. 16 is stored in the related storage DB 70. FIG. 16 is an explanatory diagram illustrating a registration example of the related storage DB 70.

  As described above, according to the present embodiment, even when a plurality of operations are performed in parallel or when there is information displayed regardless of the edge of the screen, only relevant information is automatically displayed. Can be related to each other. The reason is that keywords are extracted from the user's operation history, and information is associated with the search result of the keywords, so that only those having the same keyword are associated with each other. Therefore, according to the present embodiment, it is possible to correctly associate related information as compared with the invention described in Patent Document 1.

  Moreover, according to this Embodiment, the information which was not opened simultaneously can be associated. The reason is that a keyword is extracted from the user's operation history and information is associated with the result of searching with the keyword, so that information that is not open at the same time can be associated if it contains the same keyword. Therefore, according to the present embodiment, it is possible to correctly associate related information as compared with the invention described in Patent Document 1.

  According to the present embodiment, it is possible to prevent irrelevant information from being associated with each other by searching only with important keywords. Therefore, according to the present embodiment, it is possible to correctly associate related information as compared with the invention described in Patent Document 2.

  Japanese Patent Laying-Open No. 2005-18530 (Reference 1) describes an information processing apparatus that extracts a keyword for searching a document based on history information when the document is operated. In the method described in Document 1, important keywords in each document are weighted. For example, keywords in frequently accessed documents are weighted as important keywords. However, with the method described in Document 1, it is possible to preferentially extract documents including important keywords, and it is not possible to associate documents including keywords according to the weighting of the keywords. On the other hand, in the present embodiment, the importance level of a keyword is used for associating information. Therefore, according to this embodiment, information can be associated according to the importance of a keyword.

  Further, in the method described in Document 1, there is a high possibility that general words are weighted as important keywords. Therefore, there is a problem in applying to automatically associate information. On the other hand, in the present embodiment, since the importance level of the keyword is determined based on the location where the keyword is detected, highly relevant information can be automatically associated.

  Also, in the present embodiment, unlike the invention described in Document 1, not only documents but also inputs to the clipboard, search tool, and the like are collected as keywords.

  Moreover, according to this embodiment, the effect which cannot be obtained with the invention described in the literature 1 can be acquired. That is, it is possible to prevent the operation history in a predetermined period from being collected and associated with old information or unused information.

  Hereinafter, another preferable aspect of the information association system according to the present invention will be described.

  The information association system according to the present invention monitors user operations and collects operation histories for a certain period. A character string serving as a keyword is detected from the operation history, and the character string and the detection location of the character string are sent to the keyword importance determination means 20, and the location of information accessed from the operation history and the editing of the information User operation monitoring means 10 that sends presence / absence, display count, and display time to access information importance degree determination means 40, and the importance level is determined from the detection location of the character string sent from user operation monitoring means 10, and the character string is determined as a keyword The importance level of the access information is determined from the presence / absence of the editing history, the number of display times, and the display time of the information sent from the user operation monitoring means 10 and the keyword importance level determination means 20 stored in the keyword DB 30 together with the importance level. The access information importance level judging means 40 for storing the location and the importance level of the access information in the access information DB 50, and the access information DB 50 Information stored in the stored location is searched using the keyword in the keyword DB 30 as a key, and the information searched with the same keyword is associated in consideration of the importance of the keyword and the importance of the access information, and the related storage DB 70 And a related analysis generation means 60 for storing the related information. By adopting such a configuration, it is possible to automatically associate highly related information with each other.

  In the embodiment described above, an information association system having characteristic configurations as shown in the following (1) to (5) is shown.

  (1) Keyword importance level determination means (for example, realized by the user operation monitoring means 10 and the keyword importance level determination means 20) for detecting a keyword based on the operation history and determining the importance level of the detected keyword; Based on the history, access information is detected, and access information importance determination means (for example, user operation monitoring means 10 and access information importance determination means 40) that determines the importance of the detected accessed information is realized. And specifying means (for example, realized by the related analysis generation means 60) for specifying information including the keyword from the accessed information detected by the access information importance determination means, and the keyword importance determination means Based on the importance of the accessed keyword and the importance of the accessed information judged by the access information importance judging means , Information association system is characterized in that a associating means for associating the information including the keyword that certain means identified (for example, implemented in association studies generating means 60).

  (2) The keyword importance determination unit detects information indicating a keyword and a place where the keyword is input based on the operation history, and determines the importance of the keyword based on the information indicating the place where the detected keyword is input. An information association system for determining The information associating system configured as described above can automatically determine the importance level of the keyword and correctly relate the related information.

  (3) The information associating system for determining the importance of the accessed information based on the presence / absence of the editing history of the accessed information, the number of display times, and the display time. The information associating system configured as described above can determine the importance of the automatically accessed information and correctly associate the related information.

  (4) The associating means is specified based on a predetermined rule that associates the importance of the keyword determined by the keyword importance determining means with the importance of the accessed information determined by the access information importance determining means. Information association system for associating information including selected keywords. The information association system configured as described above can automatically associate information including keywords based on a predetermined rule.

  (5) An information association system in which the keyword importance level determination unit detects a keyword based on an operation history in a predetermined period. The information association system configured as described above can associate information including a keyword with respect to a keyword input or information accessed during a predetermined period.

  The present invention can be effectively applied to all operations performed on a PC.

It is a block diagram which shows the minimum structural example of the information correlation system by this invention. It is a block diagram which shows the structural example of the information correlation system by this invention. It is explanatory drawing which shows the example of keyword information. It is explanatory drawing which shows the example of access information. It is explanatory drawing which shows the example of the information which keyword DB memorize | stores. It is explanatory drawing which shows the example of the information which access information DB memorize | stores. It is explanatory drawing which shows the example of the information which related storage DB memorize | stores. It is a flowchart which shows operation | movement of a user operation monitoring means. It is a flowchart which shows operation | movement of a keyword importance determination means. It is a flowchart which shows operation | movement of an access information importance determination means. It is a flowchart which shows operation | movement of a related analysis production | generation means. It is explanatory drawing which shows the example of keyword information. It is explanatory drawing which shows the example of access information. It is explanatory drawing which shows the example of registration of keyword DB. It is explanatory drawing which shows the example of registration of access information DB. It is explanatory drawing which shows the example of registration of related storage DB. FIG. 10 is a block diagram illustrating a configuration example of a file relation acquisition device described in Patent Literature 1. FIG. 10 is a block diagram illustrating a configuration example of an electronic file search device described in Patent Document 2.

Explanation of symbols

21 Keyword importance level determination means 41 Access information importance level determination means 61 Identification means 62 Association means

Claims (9)

A keyword importance determination unit that detects keywords based on the operation history and determines the importance of the detected keywords;
An access information importance determining means for detecting accessed information based on the operation history and determining the importance of the detected accessed information;
Identification means for identifying information including a keyword from the accessed information detected by the access information importance level determination means;
Association for associating information including the keyword specified by the specifying means based on the importance of the keyword determined by the keyword importance determining means and the importance of the accessed information determined by the access information importance determining means An information association system comprising: means.   The keyword importance level determination unit detects information indicating a keyword and a place where the keyword is input based on an operation history, and determines the importance level of the keyword based on information indicating a position where the detected keyword is input. The information association system according to claim 1.   3. The information association system according to claim 1, wherein the access information importance level determination unit determines the importance level of the accessed information based on the presence / absence of the editing history of the accessed information, the number of display times, and the display time.   The associating means is specified based on a predetermined rule that associates the importance of the keyword determined by the keyword importance determining means with the importance of the accessed information determined by the access information importance determining means. The information association system according to any one of claims 1 to 3, wherein information including a keyword is associated.   The information association system according to any one of claims 1 to 4, wherein the keyword importance degree determination unit detects a keyword based on an operation history in a predetermined period. A keyword importance determination step for detecting keywords based on the operation history and determining the importance of the detected keywords;
An access information importance determination step for detecting accessed information based on the operation history and determining the importance of the detected accessed information;
A specifying step of specifying information including a keyword from the accessed information detected in the access information importance determination step;
Association that associates information including the keyword identified in the identifying step based on the importance of the keyword determined in the keyword importance determining step and the importance of the accessed information determined in the access information importance determining step An information associating method characterized by including steps.   In the keyword importance determination step, information indicating a keyword and a location where the keyword is input is detected based on an operation history, and the importance of the keyword is determined based on information indicating a location where the detected keyword is input. The information association method according to claim 6. On the computer,
A keyword importance determination process that detects keywords based on the operation history and determines the importance of the detected keywords;
An access information importance determination process for detecting the accessed information based on the operation history and determining the importance of the detected accessed information;
A specifying process for specifying information including a keyword from the accessed information detected in the access information importance determination process;
Association that associates information including the keyword specified in the specifying process based on the importance of the keyword determined in the keyword importance determination process and the importance of the accessed information determined in the access information importance determination process An information association program for executing and processing. On the computer,
In the keyword importance determination process, information indicating the keyword and the location where the keyword is input is detected based on the operation history, and the importance of the keyword is determined based on the information indicating the location where the detected keyword is input. The information association program according to claim 8 for executing processing.

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