JP2005018530A - Information processor, information processing program, and information processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To facilitate document search by effective keyword information, by integrating document search through the use of information on an operation history. <P>SOLUTION: A history collection means 2 of a client terminal 1 collects history data indicating the operation history, and transmits the data to a history server 4. A history acquisition part 5 of the history server 4 stores the received history data in a history DB 10, and a keyword extraction part 7 extracts a keyword included in the history data, weights the keyword and registers the weighted keyword with an index DB 12. In addition, if it has been set to analyze the history data, a history analysis part 6 analyzes the history data. Then the keyword extraction part 7 extracts a keyword based on the analysis result, weights the keyword, and registers the weighted keyword with the index DB 12. Thereby, the client terminal 1 retrieves a desired document on the basis of the keyword information registered with the index DB 12, by using an index search part 3. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an information processing apparatus, an information processing program, and an information processing method for searching for a document using a keyword in a computer system that uses an electronic document such as an office document or a Web document.
[0002]
[Prior art]
In recent years, with the spread of networks and high-performance personal computers (hereinafter referred to as PCs), the creation and use of electronic documents in the office environment has become more common, and the amount of information in electronic documents continues to increase day by day. . Document retrieval technology for retrieving necessary information from a large amount of electronic document information is essential in an environment where electronic documents are flooded, and the performance of the document retrieval system improves the efficiency of office work. Has an important impact. Further, as a document search technique, a keyword search technique using a keyword assigned to a document in advance by a user, a full-text search technique for searching a specified character string from document contents, or a search technique that combines the characteristics of both. There is an index type search technology that automatically extracts keywords from document contents and creates index information in advance to improve the accuracy of full-text search and speed up the search. Among them, index type search technology that is a search system using an index is excellent in performance when searching an unspecified number of documents, and is a search technology widely used including Web information search sites. .
[0003]
The performance of index-type search greatly depends on how important keywords can be extracted from document contents. Natural language analysis processing to extract appropriate keywords and index information weighting processing based on keyword appearance frequency For example, various measures are taken to generate index information. There are also attempts to use information other than character strings included in content in order to improve search accuracy. For example, Google's (registered trademark) Web search engine uses link information between Web documents for keyword weighting, and obtains high search results in a range in which search targets are specified as Web and documents.
[0004]
Further, for example, Patent Document 1 below discloses a technique for performing an image search with a simple operation. This technique records past operation contents and operation date / time of image data as search information, and extracts a desired image when the search information matches a search item specified at the time of search.
Furthermore, for example, Patent Document 2 below discloses a technique for performing information retrieval based on a bookmark that can specify desired information on a Web browser. In this technique, keywords are extracted from bookmark information and bookmark usage history, and information matching the keywords is notified to the user.
[0005]
[Patent Document 1]
JP-A-7-239854 (see paragraph numbers 0017 to 0040 and FIGS. 1 to 3)
[Patent Document 2]
JP 2001-195422 A (paragraph numbers 0005 to 0013 and FIGS. 1 to 4)
[0006]
[Problems to be solved by the invention]
However, the generation of index information is still a major technical issue for information retrieval systems, not only improving the search accuracy, but also responding to the increased load on the CPU due to advanced index generation processing, and improving the coverage of search target documents The technical improvement of the entire system for performing a search such as support for various document formats is also a major technical problem of the document search system. From this point of view, the conventional document search device or document search device system does not say that index information is generated in an optimum system environment, and as a result, the search flexibility in the field is lacking. At the same time, the search accuracy is further prevented. These problems are still not solved in the techniques of Patent Document 1 and Patent Document 2 described above.
[0007]
The present invention has been made in view of the above-described problems, and an object of the present invention is to unify a document search method using access history information to a document indicating how a document is used and how it has been used. Accordingly, an object of the present invention is to provide an information processing apparatus, an information processing program, and an information processing method capable of facilitating document search by generating effective keyword information with a small processing load.
[0008]
[Means for Solving the Problems]
In order to achieve the above object, the present invention provides an information processing apparatus that generates a keyword for searching a document, and obtains history information obtained from an access history when the document is operated. And keyword extraction means for extracting the keyword for document search from the history information based on the history information acquired by the history acquisition means.
[0009]
Further, the present invention is an information processing program for causing a computer to execute a process for generating a keyword for searching for a document, and obtains history information obtained from an access history when the document is operated. Based on the history information acquired by the history acquisition step, the computer is caused to execute an acquisition function and a keyword extraction function for extracting the document search keyword from the history information.
[0010]
The present invention is also an information processing method for generating a keyword for searching a document, a history acquisition step for acquiring history information obtained from an access history when the document is operated, and the history acquisition step And a keyword extraction step of extracting the document search keyword from the history information based on the history information acquired by the above.
[0011]
DETAILED DESCRIPTION OF THE INVENTION
The document search apparatus of the present invention is based on operation history information obtained from a history of operating a document, such as operation content information of a document, business content information using the document, or related document information of a document. Generate a keyword for search, generate index information using this keyword, register it in the database, and then search the document using this index information, or embed the generated keyword in the document As a result, the document search is performed using the keyword. This makes it possible to use highly accurate information that is highly likely to be actually used as a search keyword, and can also be applied to a search for non-text sentences. In addition, it is possible to perform a high-accuracy search that covers all documents by a full-text search.
[0012]
Embodiments of the present invention will be described below.
FIG. 1 is a block diagram showing a configuration of a document search system according to an embodiment of the present invention. This document search system exists on a network with a client terminal 1 on which a user operates a document, and acquires (saves) history, analyzes history, extracts keywords and creates index information, and various databases (hereinafter referred to as “database”). A history server 4 that manages a database (abbreviated as DB) and a file server 13 that stores user documents and enables access to the documents via a network are connected to the LAN 14. .
[0013]
A client terminal 1 on which a user operates a document includes a history collection unit 2 as a history collection unit that collects document history information, and an index search unit 3 as an index search unit that searches for documents including a predetermined keyword. It has a configuration.
[0014]
The history collection unit 2 is a software module incorporated in the client terminal 1, and has a function of collecting document information accessed by detecting an event of an application operation performed by a user and transmitting the document information to the history server 4. ing.
[0015]
The index search unit 3 is a software application of the client terminal 1 and searches the index DB 12 existing in the history server 4 for a document or a document part including the keyword specified by the user, and the search result is sent to the user in descending order of weight. It has a function to present.
[0016]
The history server 4 includes a history acquisition unit 5 as a history acquisition unit, a history analysis unit 6 as a history analysis unit, a keyword extraction unit 7 as a keyword extraction unit, an index creation unit 9, a history DB 10, a document information DB 11, and an index DB 12 It is the composition provided with.
[0017]
In the configuration shown in FIG. 1, the history server 4 exists on the network and is realized as a server function, and performs history information storage, history information analysis, and index management. However, such a server function may exist in the client terminal 1. In addition, the functions of history information storage, analysis, and index management may be provided in different servers. The index management function uses a search system using an existing index.
[0018]
The history acquisition unit 5 is a software module that operates on the history server 4 and has a function of receiving document access history data transmitted from the client terminal 1 and storing it in the history DB 10.
[0019]
The history analysis unit 6 has a function of analyzing document access history data stored in the history DB 10, extracting a document access count and a related document of a specific document or document part, and storing the document in the document information DB 11. Yes. Here, the related document refers to a document / part referenced when creating the document / part, a derived document created using the document / part, and when the document / part is accessed in parallel. This refers to information such as documents that are frequently used.
[0020]
The history analysis unit 6 is an additional component for increasing the search effect according to the present invention, and the history analysis unit 6 is not a constituent requirement in all of the present invention.
[0021]
When extracting related documents from history information, it is not possible to know which is related history only by history information. Therefore, business analysis processing from document access history and document association from business history created by business analysis processing. Process.
The business history generation process from the document access history is performed as follows, for example. Focusing on characteristic document access histories such as printing, file storage, and mail transmission that occur at the time of business separation, business history is created by separating document access history that is continuous in time series.
For example, the following processing is performed as the document association processing from the business history. After aggregating data in a spreadsheet, pasting the results into a presentation document or referencing past emails to create new emails, a pattern that is fixed to some extent regardless of the type of business. Since it is considered that the access according to this occurs, the relation can be derived by defining this access pattern in advance and comparing it with the document access history without the business history. For example, from the pattern “document B updated after opening document A within the same business”, “B is derivative information of A” contrary to the relationship “A is reference information of B”. Can lead to the relationship.
[0022]
The keyword extraction unit 7 includes a weighting unit 8 as a weighting unit, extracts keyword information from information stored in the history DB 10 and the document information DB 11, weights the keyword information, and records the keyword information in the index DB 12. A keyword extraction method and a weighting method will be described later.
The index creation unit 9 as an index creation unit uses the keywords extracted by the keyword extraction unit 7, the history information stored in the history DB 10, and the document information stored in the document information DB 11 (analysis result of the history analysis unit 6). Create index information based on it.
[0023]
The history DB 10 is a database that stores history information transmitted from the client terminal 1. The detailed configuration of the history DB 10 will be described later with reference to FIG.
The document information DB 11 is a database that stores information obtained by analyzing history information stored in the history DB 10. The detailed configuration of the document information DB 11 will be described later with reference to FIG.
The index DB 12 is a database that records the index information created by the index creation unit 9. The detailed configuration of the index DB 12 will be described later with reference to FIG. The index DB 12 may be an index DB attached to an existing index search system.
[0024]
The file server 13 has a file DB 13a for storing the user's document, and is a server that enables access to the document via the network. However, the document to be managed in the present invention is only on the file server 13. Instead, it may be a document on the client terminal 1 or on the Internet.
[0025]
FIG. 2 is a diagram showing an example of the configuration and contents of the history DB 10 shown in FIG. In FIG. 2, the date and time when the document access occurred in the client terminal 1 is recorded in the “date and time” item column. For example, as in “2003/03/19 14:34:12”, the date and time of access occurrence is recorded from the year, month, day to hour, minute, second.
In the “operation content” item column, the operation content performed on the document by the user is recorded. The types of operations include Open, Save, Delete, Print, Send (mail transmission), and the like.
[0026]
In the “user name” item column, user information for identifying the user who performed the operation is recorded. For example, the name of the user who performed the operation is recorded.
In the “document” item column, information for identifying a document to be investigated is recorded. For example, if the investigation target is a web document, a URL (for example, HYPERLINK "http://www.b-car.co.jp" http: // www. b-car. co. jp ), And if it is a Windows shared file, the network path (eg, Windows, server name, share name, path name, file name) HYPERLINK "\\\\ server1 \\ dsr \\ cars.doc" \\ server1 \ dsr \ cars. doc ).
[0027]
In the “document title” item column, the title of the document obtained from the application when the user operates the document is recorded. For example, in the case of a new car information document, new car information (for example, company A new car information) of each automobile company, event information about the new car (for example, spring new car), and the like are recorded.
In the “page” item, the page number of the target operation is recorded. Note that this field is blank when the operation target is the entire document.
In the “transmission / output destination” item column, information on the transmission destination or the output destination is recorded with respect to the history of document transmission and output operations. For example, if the content of the operation is a print, the name of the printer that performed the print (for example, Printer A), or the Send (send) by e-mail, the user name of the user included in the destination (for example, Fujiwara) Record.
[0028]
In the “peripheral keyword” item column, keyword information (for example, vehicle type A, vehicle type B, motorcycle, etc.) included in the operated document is recorded. Note that the keyword information may be included in advance in the document to be operated, or may be generated dynamically from the document content by the history collection means 2 of the client terminal 1. As an example in which the keyword information is included in the document in advance, there is a document created by the Microsoft Office application (registered trademark). There are several existing methods for dynamically generating keywords from document content.
[0029]
For example, the computer divides text information into vocabulary units by morphological analysis processing that analyzes natural language by decomposing parts of speech in the document, counts the number of occurrences of each vocabulary in the document, and the number of appearances A method is used in which keywords having a large number of characters are used. In addition, if the target of the search operation is not the entire document but a part of the document such as a page, the keyword is extracted from the information contained in the target page instead of extracting the keyword from the entire document. The method is used. At this time, the peripheral keyword is not essential, and the processing may be omitted according to the system load.
[0030]
FIG. 3 is a diagram showing an example of the configuration and contents of the document information DB shown in FIG. That is, this figure shows the configuration and contents of the document information DB 11 that records the document information obtained by analyzing the history information stored in the history DB 10.
In the “document” item column, an identifier (for example, c: ¥ abc.doc) of a document to be searched for document information is described. The description method of the information included in this field is the same as the information of the “document” item described in the configuration and contents of the history DB 10 shown in FIG. That is, if the search target is a web document, a URL is recorded, and if it is a Windows shared file, a network path including Windows, a server name, a shared name, a path name, and a file name is recorded.
[0031]
In the “page” item column, the page number to be searched is recorded when the search target is not the whole document but one part in the document. If the search target is the entire document, this field is blank.
In the “access count” field, the number of accesses that have occurred for the document or part to be searched is recorded.
In the item column of “reference document / reference count”, a document (for example, def.doc) referred to when creating or updating a document or part to be searched is recorded. In order to distinguish frequently referred documents from other documents, the number of references is recorded together with the document name. For example, def. When doc is referenced three times, def. Record as doc / 3.
[0032]
In the item column of “derived document / referenced count”, a document (for example, cars.doc) created by referring to a document or part to be searched is recorded. In addition, when the derived document is created, the number of times that the search target document is referred is recorded.
In the item column of “simultaneous use document”, a document that is frequently used at the same time when a document or a part to be searched is accessed (for example, HYPERLINK “http://www.a-car.co”). .Jp " http: // www. a-car. co. jp ).
In the “keyword” item column, keyword information (for example, vehicle type A, vehicle type B, etc.) included in the document or part to be searched is recorded. The keyword information includes keyword information recorded in the peripheral keywords of the history DB 10 and keywords extracted from the titles recorded in the document titles of the history DB 10.
[0033]
FIG. 4 is a diagram showing an example of the configuration and contents of the index DB 12 shown in FIG. That is, this figure shows the configuration and contents of the index DB 12 used for searching for documents using keywords. The index DB 12 that is actually used has an efficient DB configuration in order to speed up the search process, but here a simple configuration is illustrated for simplicity.
[0034]
In the “document” item column, identification information (for example, c: ¥ abc.doc) of a document to be searched is recorded. In this example, the same information as the field information in the “document” item column included in the history DB 10 or the document information DB 11 described above is recorded.
In the “page” item column, the page number of the part is recorded when the search result is not the whole document but the part of the document.
In the “keyword” item column, a list of keywords included in the target document or part (for example, company A, car, car life, etc.) is recorded. When the index DB 12 is shared by the existing document search system and the document search system according to the present invention, both the keyword information generated by the existing document search system and the keyword information generated by the document search system according to the present invention are the same. Present in the keyword list.
[0035]
In the “weight” item column, the weight (importance) for each keyword is recorded. A keyword having a larger weight value is recognized as a keyword that better represents the target document / part. For example, in “c: ¥ abc.doc” in the “document” item column, the weight of “car type A” is “10” and the weight of “car model B” is “3”. "Means that the importance of the keyword is much higher than" car type B ".
In the document search process using the index DB 12, the keyword field of the index DB 12 is searched with the keyword specified by the user, the document / part including the keyword is specified, and sorted in descending order of the weight assigned to the keyword. As a search result.
[0036]
Next, an operation sequence performed by the document search system of the present invention will be described in detail using a flowchart. FIG. 5 is a flowchart showing the flow of history collection processing performed by the client terminal in the document search system according to the present embodiment. First, the history collection unit 2 incorporated in the client terminal 1 starts a user application operation event process. That is, the history collection unit 2 detects a document operation performed by the user and starts a series of search processes (step S1). When the search process is started, the history collection unit 2 collects document information such as a file name, a page number, a title, and operation contents from the application as operation history information according to the contents of the event. At this time, the history collection unit 2 extracts peripheral keywords from the content of the opened document (step S2). Then, the history collection unit 2 transmits the information collected in step S2 to the history server 4 as operation history information (step S3).
[0037]
FIG. 6 is a flowchart showing a flow of processing from reception of operation history information to update of the index DB, which is performed by the history server 4 in the document search system according to the present embodiment. That is, this figure shows the flow of processing until the history server 4 extracts and registers keywords from the operation history information.
[0038]
First, when the history server 4 enters a history collection system (step S11), the history acquisition unit 5 of the history server 4 determines whether or not history data has been received from the client terminal 1 (step S12). Here, if history data has not been received yet (step S12, No), it waits until history data is received. On the other hand, when the history acquisition unit 5 detects that the history data has been received from the client terminal 1, a series of processes for performing a keyword search is started (Yes in step S12).
[0039]
That is, in the history server 4, the history acquisition unit 5 stores the received history data in the history DB 10, and the keyword extraction unit 7 extracts the keyword information included in the received history data (step S13). The content of the keyword extraction process by the keyword extraction unit 7 will be described later with reference to FIG. Further, the keyword extraction unit 7 weights the keyword information extracted by the weighting unit 8, and registers this keyword information in the index DB 12 (step S14). Thereby, the index search unit 3 of the client terminal 1 can search for a desired document by arranging the keyword information registered in the index DB 12 in descending order of weight. The content of the keyword weighting process performed by the keyword extraction unit 7 will be described later with reference to FIG.
[0040]
Furthermore, in this embodiment, keywords can be extracted and registered effectively by adding the following steps S15 to S18. That is, it is determined whether or not the document search system is set to perform history analysis (that is, whether or not the history analysis unit 6 is configured) (step S15) and set to perform history analysis. If it is set (that is, the history analysis unit 6 is configured) (step S15, Yes), the history analysis unit 6 starts analysis processing of history data. Then, the history analysis unit 6 uses the history data recorded in the history DB 10 to analyze history data such as the number of document accesses and related documents (step S16). The processing for analyzing the related document from the history data is performed using an existing processing procedure. If the document search system is not set to perform history analysis in step S15 (that is, the history analysis unit 6 is not configured) (step S15, No), the search process is terminated as it is.
[0041]
Next, when the history analysis unit 6 analyzes the history in step S16, the keyword extraction unit 7 extracts the keyword information from the analysis result (contents of the document information DB) performed by the history analysis unit 6 and weights it. Is performed (step S17). The keyword information extraction and weighting processing performed by the keyword extraction unit 7 will be described later with reference to FIGS. Then, the index creating unit 9 creates an index using the keyword extracted by the keyword extracting unit 7 and weighting information, and registers it in the index DB 12 (step S18). Accordingly, the index search unit 3 of the client terminal 1 can search for a desired document by arranging the keyword information in descending order based on the index information registered in the index DB 12.
[0042]
FIG. 7 is a diagram illustrating an example of rules when the keyword extraction unit 7 of the history server 4 extracts keywords. That is, FIG. 7 shows that in steps S13 and S14 of the flowchart shown in FIG. 6, the keyword extraction unit 7 extracts keywords included in the history data from the history DB 10 and the document information DB 11, and the index creation unit 9 adds them to the index DB 12. This is an example of rules for registering as a keyword or for registering the keyword extracted from the analysis result by the keyword extraction unit 7 as an additional keyword in the index DB 12 in steps S18 and S19. . Note that the keyword extraction rules shown in FIG. 7 can be arbitrarily selected and used according to the configuration and load of the document search system, and it is not necessary to use all the rules. Also, a new rule can be added and used.
[0043]
Hereinafter, the keyword extraction rules performed by the keyword extraction unit 7 will be described in detail with reference to FIG.
In the “add creator” rule, the name of the creator who created the document is extracted as an additional keyword, and is registered in the index DB 12 by the index creation unit 9.
In the “add creation date” rule, the date and time when the document was created is extracted as an additional keyword and is registered in the index DB 12 by the index creation unit 9.
In the “add server name where document is located” rule, the server name of the server where the document is located is extracted as an additional keyword and registered in the index DB 12 by the index creation unit 9.
[0044]
In the “add contents of access to document” rule, operation contents performed by the user such as browsing, printing, deletion, transfer, transmission, etc. are extracted as additional keywords, and the index creating unit 9 stores them in the index DB 12. Let me register.
In the “add destination” rule, when the document is transmitted by e-mail or the like, the user name of the destination (transmission destination) is extracted as an additional keyword, and is registered in the index DB 12 by the index creation unit 9. .
In the “add access frequency” rule, additional keywords such as “high frequency” and “low frequency” are extracted according to the access frequency of the document, and are registered in the index DB 12 by the index creation unit 9.
That is, “high frequency” is registered in the index DB 12 when the access frequency is high, and “low frequency” is registered when the access frequency is low.
[0045]
In the “add access count” rule, additional keywords such as “popular” when the total access count is high and “unpopular” when the total access count is low are extracted according to the document access count. Then, the index creation unit 9 registers it in the index DB 12.
In the “add output destination” rule, when the document is printed out, the printer name of the output destination is extracted as an additional keyword, and is registered in the index DB 12 by the index creation unit 9.
That is, the device name of the data output destination is registered in the index DB 12.
[0046]
In the “add related document keyword” rule, keyword information included in the related document of the reference document, derived document, and simultaneous use document recorded in the document information DB 11 is extracted as an additional keyword of the target document, and an index is created. The part 9 is registered in the index DB 12.
In the “add related document title” rule, keyword information included in the related document titles of the reference document, derivative document, and simultaneous use document recorded in the document information DB 11 is extracted as an additional keyword of the target document, and indexed. The creation unit 9 registers in the index DB 12.
[0047]
FIG. 8 is a diagram illustrating an example of rules when the keyword extraction unit 7 weights keywords. That is, FIG. 8 is a diagram showing an example of rules when the keyword extraction unit 7 weights the keywords and registers them in the index DB 12 in step S14 and step S18 of the flowchart shown in FIG.
Note that the rules shown in FIG. 8 can be arbitrarily selected and used according to the configuration and load of the document search system, and it is not necessary to use all the rules. Also, a new rule can be added and used.
[0048]
As in the case of “the number of accesses of the document including the keyword> 10”, as a rule when the number of accesses to the related document is large, the weight of the keyword is increased when the keyword of the related document of the document is registered. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
As a rule when the number of accesses to the part of the related document is large, such as “the number of accesses of the part including the keyword> 10”, the keyword weight is increased when the keyword of the part of the document related document is registered. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
[0049]
As a rule when there is a history of printing a part including the keyword in the past, such as “number of output of the part including the keyword> 1,” the weight of the keyword is increased considering that the document / part is an important document. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
When registering a keyword for a reference document / part when a document is created or updated, such as “Keyword of related document with reference count of 2 or more”, when the reference number for the reference document / part is large, Increase keyword weights by assuming that keywords are highly relevant. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
[0050]
When registering a keyword of a derived document / part created by referring to a document as a rule of “derived keyword”, if the number of references from the derived document / part is large, the keyword is strongly related. Think and increase keyword weight. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
As a rule of “keyword of related document that has been printed”, among the keywords included in the related document, the weight of the keyword of the related document that has been subjected to specific high importance processing such as printing or transmission is increased. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
As a rule of “document created by a specific user”, the weight of a keyword included in a document created by a specific user is increased. That is, the index creation unit 9 increases the keyword weight by “1” and registers it in the index DB 12.
[0051]
The embodiment described above is an example for explaining the present invention, and the present invention is not limited to the above-described embodiment, and various modifications can be made within the scope of the gist of the invention. That is, in the above embodiment, the extracted keyword information is registered in the index DB 12. However, the present invention is not limited to this, and the keyword information may be embedded (added) in the document itself. For example, in a document created by the Microsoft Office application (registered trademark), an area for recording keyword information is prepared in the document, and in HTML and XML documents, the keyword information is different from the document content. The area for recording is defined. In addition, since the keyword information extracted by the document search system of the present invention is included in the document itself, the document search system of the present invention can be used even when used in combination with a full-text search system without an index DB. The same effect as the embodiment can be realized.
[0052]
In the embodiment of the present invention, the function for carrying out the invention is recorded in advance in the apparatus. However, the present invention is not limited to this, and the same function may be downloaded from the network to the apparatus. Those having these functions stored in a recording medium may be installed in the apparatus. The recording medium may be in any form as long as it can store a program such as a CD-ROM and can be read by the apparatus. In addition, the function obtained by installing or downloading in advance may be realized in cooperation with an OS (operating system) inside the apparatus.
[0053]
【The invention's effect】
As described above, according to the present invention, since highly reliable keyword information based on a user's operation history is added to a document, search accuracy can be improved. Further, by using related document information, keywords that are not included in the document itself can be added, and search flexibility can be enhanced. In addition, even if the document to be searched is a document that does not contain text information such as images and sounds, keyword information is added using history information and related documents, and the search target by keyword is the same as for documents that contain text. can do.
[Brief description of the drawings]
FIG. 1 is a block diagram showing a configuration of a document search system in an embodiment of the present invention.
FIG. 2 is a diagram showing an example of the configuration and contents of a history DB shown in FIG.
3 is a diagram showing an example of the configuration and contents of a document information DB shown in FIG.
4 is a diagram showing an example of the configuration and contents of an index DB shown in FIG. 1. FIG.
FIG. 5 is a flowchart showing a flow of history collection processing performed by a client terminal in the document search system in the embodiment of the present invention.
FIG. 6 is a flowchart showing a flow of processing from operation history information reception to index DB update performed by the history server in the document search system according to the embodiment of the present invention.
FIG. 7 is a diagram illustrating an example of a rule when a keyword extraction unit of a history server extracts a keyword.
FIG. 8 is a diagram illustrating an example of rules when a keyword extraction unit weights keywords.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 Client terminal 2 History collection part 3 Index search part 4 History server 5 History acquisition part 6 History analysis part 7 Keyword extraction part 10 History DB 11 Document information DB 12 Index DB 13 File server 14 LAN.

Claims (13)

An information processing apparatus for generating a keyword for searching a document,
History acquisition means for acquiring history information obtained from an access history when the document is operated;
An information processing apparatus comprising: keyword extraction means for extracting the document search keyword from the history information based on the history information acquired by the history acquisition means. The information processing apparatus according to claim 1,
Based on the history information acquired by the history acquisition means, the keyword extracted by the keyword extraction means from the history information is at least one of the creator, creation date and time, creation location, access content, and access time related to the document. An information processing apparatus characterized by being related to one piece of information. The information processing apparatus according to claim 1,
The information processing apparatus according to claim 1, wherein the keyword extraction unit includes a weighting unit that adds weighting information to the keyword extracted by the keyword extraction unit based on the history information. The information processing apparatus according to claim 1,
A history analysis means for analyzing the history information based on the history information acquired by the history acquisition means,
The keyword extracting unit extracts a keyword using the history information and an analysis result of the history analyzing unit. The information processing apparatus according to claim 1,
An information processing apparatus comprising keyword adding means for adding a keyword extracted by the keyword extracting means to the document. The information processing apparatus according to claim 1,
An information processing apparatus comprising: index information generating means for generating index information for searching the document based on the keyword extracted by the keyword extracting means. The information processing apparatus according to claim 6,
Index information storage means for storing index information generated by the index information generation means;
An information processing apparatus comprising: search means for searching for a document using index information stored in the index information storage means. An information processing program for causing a computer to execute processing for generating a keyword for searching for a document,
A history acquisition function for acquiring history information obtained from an access history when the document is operated;
An information processing program for causing a computer to execute a keyword extraction function for extracting a keyword for document search from the history information based on the history information acquired by the history acquisition step. An information processing program according to claim 8,
An information processing program for causing a computer to execute an index information generation function for generating index information for searching the document based on a keyword extracted by the keyword extraction function. An information processing program according to claim 9,
An index information storage function for storing the index information generated by the index information generation function;
An information processing program for causing a computer to execute a search function for searching for a document using index information stored in the index information storage function. An information processing method for generating a keyword for searching a document,
A history acquisition step of acquiring history information obtained from an access history when the document is operated;
And a keyword extracting step of extracting the document search keyword from the history information based on the history information acquired by the history acquiring step. An information processing method according to claim 11,
An index information generating step of generating index information for searching the document based on the keyword extracted by the keyword extracting step. An information processing method according to claim 12,
An index information storage step for storing the index information generated by the index information generation step;
A search step for searching for a document using the index information stored in the index information storage step.

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