Document retrieval program, document retrieval apparatus and document retrieval method

Abstract

To provide a document retrieval apparatus, a document retrieval method and a document retrieval program, in document retrieval using retrieval keywords, which can provide the candidates of suitable retrieval keywords.SOLUTION: A document retrieval program according to an embodiment causes a computer to realize a document retrieval function, a word group creation function and a word group selection function. The document retrieval function retrieves a document related to a retrieval text inputted by a user in a document database stored with plural documents. The word group creation function creates plural word groups which classify suggested words extracted from the retrieved document using information about a document structure or classification information based on the meaning of words. The word group selection function selects the word group to be provided to the user from among the plural word groups.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The embodiment of the present invention relates to a document searching program, a document searching device, and a document searching method. [Background technology]

[0002] A document search system is a system that accepts search text such as search keywords and questions as inquiries from users, and outputs documents by referencing a document DB (document database). Document search systems are provided on the Internet, and search for and output related documents from among documents stored in a document DB based on search keywords and questions entered by users.

[0003] Conventional document search systems automatically collect documents published on the Internet, and for each document, store the words that appear in the document and the occurrence probability of each word in the document. When a user's query is received, documents are extracted from the stored set of documents in descending order of the occurrence probability of the words contained in the received input sentence, and the extracted documents and sentences and paragraphs containing the words in the extracted documents are output. There is also a known method of performing morphological analysis on natural language received as an input sentence, identifying keywords contained in the input sentence, and automatically creating a search request.

[0004] However, in such document search systems, the user must think for himself / herself of appropriate keywords and sentences to search for documents containing the desired information. For this reason, there are methods that assist the user in entering keywords by recommending words extracted from documents in search results as search keyword candidates. In such methods, by recommending keywords that are thought to contain the information the user is looking for, the user is no longer required to think for himself / herself of appropriate keywords and sentences to search for documents containing the desired information, and can efficiently reach the desired information. Such search keyword candidates are also called suggested words.

[0005] These search keyword candidates are selected from all sentences in the document. In addition, the document contains various document components such as titles, chapters, and paragraphs. Therefore, miscellaneous keywords selected from various document components in the document are recommended as search keywords. In this case, it becomes difficult for users to compare search keywords with each other, and it becomes difficult to select keywords that can lead to a document that contains the information they are looking for. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2020-123131 A Summary of the Invention [Problem to be solved by the invention]

[0007] An object of the present invention is to provide a document retrieval device, a document retrieval method, and a document retrieval program that are capable of presenting appropriate search keyword candidates in a document retrieval using a search keyword. [Means for solving the problem]

[0008] In order to solve such problems, the document search program of the embodiment causes a computer to realize a document search function, a word group generation function, and a word group selection function. The document search function searches a document database storing a plurality of documents for documents related to a search text input by a user. The word group generation function uses information on document structure or classification information based on the meanings of words to generate a plurality of word groups into which suggested words extracted from the searched documents are classified. The word group selection function selects a word group to be presented to a user from the plurality of word groups. [Brief description of the drawings]

[0009] [Figure 1]FIG. 1 is a diagram showing an example of the configuration of a document search system according to a first embodiment. [Diagram 2] FIG. 1 is a diagram showing an example of the configuration of a document searching apparatus according to a first embodiment. [Diagram 3] 5 is a flowchart illustrating a processing procedure of a document search process according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of a data flow in a document search process according to the first embodiment. [Diagram 5] FIG. 2 is a diagram showing an example of a document used as a search target in the first embodiment. [Figure 6] FIG. 4 is a diagram for explaining an example of step S303 in FIG. 3. [Figure 7] FIG. 4 is a diagram for explaining an example of step S304 in FIG. 3. [Figure 8] FIG. 11 is a diagram for explaining a method of presenting suggested words according to a modified example of the first embodiment. [Figure 9] FIG. 11 is a diagram showing an example of the configuration of a document searching apparatus according to a second embodiment. [Figure 10] 10 is a flowchart illustrating a processing procedure of a document search process according to the second embodiment. [Figure 11] FIG. 11 is a diagram showing an example of a data flow in a document search process according to the second embodiment. [Figure 12] FIG. 11 is a diagram for explaining an example of step S1002 in FIG. [Figure 13] 11 is a diagram for explaining an example of steps S1003 and S1004 in FIG. 10. [Figure 14] FIG. 11 is a diagram for explaining an example of thesaurus information used in step S1003 in FIG. [Figure 15] 11 is a diagram for explaining a modified example of thesaurus information used in step S1003 in FIG. [Figure 16] FIG. 13 is a diagram showing an example of the configuration of a document searching apparatus according to a third embodiment. [Figure 17] FIG. 13 is a diagram showing an example of a data flow in a document search process according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of a document search program, a document search device, and a document search method will be described in detail with reference to the drawings. In the following description, components having substantially the same functions and configurations are denoted by the same reference numerals, and duplicated descriptions will be given only when necessary.

[0011] (First embodiment) Fig. 1 is a diagram showing a configuration of a document search system 1 including a document search device 100 according to a first embodiment. The document search system 1 is a computer network system that executes an interactive document search to select document data matching a user's query from a document database based on the query. As shown in Fig. 1, the document search system 1 includes the document search device 100, a document DB (document database) 200, and a client terminal 300.

[0012] The document search device 100 is connected to a document DB 200 and a client terminal 300 via a network or the like. The network is, for example, a LAN (Local Area Network). The connection to the network may be a wired connection or a wireless connection. The network is not limited to a LAN, and may be the Internet, a public communication line, or the like.

[0013] The document DB 200 is a computer that holds a database that accumulates multiple document data to be searched. As the document data, for example, document data in HTML format or PDF format can be used, but data in any other format is also acceptable. In the following explanation, "document data" will be simply called "document." Each document is composed of multiple sentences, words, symbols, etc. The type of document to be searched may be a report, an instruction manual, or any other type of document.

[0014] The client terminal 300 is a computer used by a user of the document retrieval system 1. The client terminal 300 has a processor, an input device, a display device, and a communication device as hardware, and functions as a user interface of the document retrieval system 1. For example, the client terminal 300 accepts input of text related to a document to be searched (hereinafter referred to as search text) input by a user via an input device. The client terminal 300 transmits the input search text to the document retrieval device 100.

[0015] The document search device 100 functions as a server device of the document search system 1. Specifically, the document search device 100 receives a search text from the client terminal 300, searches for a document related to the search text from among documents stored in the document DB 200 based on the received search text, and transmits the searched document (hereinafter referred to as a search document) to the client terminal 300.

[0016] Furthermore, the document search device 100 selects multiple search keywords to be recommended to the user from within the searched documents in order to further narrow down the searched documents, and transmits the extracted search keywords to the client terminal 300. The client terminal 300 receives the search keywords and document search results from the document search device 100, and displays them on a display device. In the following description, the search keywords presented to the user and candidates for the search keywords presented are referred to as suggested words.

[0017] Fig. 2 is a diagram showing an example of the configuration of the document search device 100. As shown in Fig. 2, the document search device 100 is a computer having a processing circuit 11, a storage device 12, an input device 13, a communication device 14, and a display device 15. Data communication between the processing circuit 11, the storage device 12, the input device 13, the communication device 14, and the display device 15 is performed via a bus.

[0018] The processing circuit 11 has a processor such as a CPU (Central Processing Unit) and a memory such as a RAM (Random Access Memory). The processing circuit 11 has a document search unit 111, a block division unit 112, a word group generation unit 113, a word group selection unit 114, and a suggested word presentation unit 115. The processing circuit 11 executes a document search program to realize the document search function, the block division function, the word group generation function, the word group selection function, and the suggested word presentation function by each of the above units. The document search program is stored in a non-transitory computer-readable recording medium such as the storage device 12. The document search program may be implemented as a single program that describes all the functions of each of the above units, or may be implemented as multiple modules divided into several functional units. In addition, each of the above units may be implemented by an integrated circuit such as an Application Specific Integrated Circuit (ASIC). In this case, they may be implemented in a single integrated circuit, or may be implemented individually in multiple integrated circuits.

[0019] The storage device 12 is configured by a ROM (Read Only Memory), an HDD (Hard Disk Drive), an SSD (Solid State Drive), an integrated circuit storage device, etc. The storage device 12 stores a document search program and the like.

[0020] Various commands are input from an operator through the input device 13. A keyboard, a mouse, various switches, a touch pad, a touch panel display, etc. can be used as the input device 13. An output signal from the input device 13 is supplied to the processing circuit 11.

[0021] The communication device 14 is an interface for performing data communication with an external device connected to the document search device 100 via a network. As an example, the communication device 14 performs data communication with the document DB 200 and the client terminal 300.

[0022] The display device 15 displays various information. As the display device 15, a CRT (Cathode-Ray Tube) display, a liquid crystal display, an organic EL (Electro Luminescence) display, an LED (Light-Emitting Diode) display, a plasma display, or any other display known in the art can be appropriately used. The display device 15 may also be a projector.

[0023] Next, the functions performed by each part of the processing circuit 11 will be described in detail. The document search unit 111 searches documents related to the search text input by the user from among documents stored in the document DB 200, and acquires the searched search document from the document DB 200. The search text is input by the user at the client terminal 300. The search text may be input as natural language such as a question, or may be input as a word such as a search word or a suggested word described later. The word may be input as a single word, or may be input as a word string including a plurality of words. The document search unit 111 extracts words from the search text received from the client terminal 300, searches the document DB 200 for documents including the extracted words, and acquires the searched document as a search document. The document search unit 111 outputs the acquired search document as a candidate document to be provided to the user.

[0024] The block division unit 112 divides each retrieved document into a plurality of document blocks based on information about the document structure. For example, the block division unit 112 divides each retrieved document into a plurality of document blocks by classifying each sentence included in the retrieved document into one of a plurality of document blocks according to the document structure. The information about the document structure is, for example, HTML tags attached to the document, sentences included in each paragraph number, and the order of each sentence in the document. The block division unit 112 outputs block information about the document blocks including the division results of each document as information about the document structure.

[0025] The word group generating unit 113 generates a plurality of word groups into which the suggested words extracted from the searched document are classified. Specifically, the word group generating unit 113 extracts suggested words used to narrow down the documents for each document block, and generates a word group consisting of the suggested words for each document block. At this time, the word group generating unit 113 generates a word group consisting of suggested words extracted from the same type of document block in each document for each document block. The suggested words are words used to narrow down the documents, and can also be called recommended search words effective for narrowing down the document search. The suggested words are typically one noun, but may be adjectives, verbs, etc., or may be sentences including multiple words. For example, known natural language processing can be used to extract the suggested words. The suggested words extracted from the searched document are used as candidates for suggested words to be presented to the user. The word group generating unit 113 may be called a word group extracting unit.

[0026] When extracting suggested words, the word group generation unit 113 extracts all words contained in each document as suggested words, for example, by performing natural language analysis on the documents. When generating word groups, the word group generation unit 113 extracts suggested words for each document block, for example, and generates word groups for each document block by collecting suggested words extracted from the same document block from each search document. The word group generation unit 113 outputs the generated word groups and sets of suggested words belonging to the word groups as information related to the word groups.

[0027] Each word group includes suggested words of each document extracted from the same document block. In addition, multiple suggested words may be extracted from one document in each word group. In addition, suggested words belonging to the document block word group are not extracted from documents that do not have that document block. Therefore, a word group may be composed of suggested words extracted from a portion of the retrieved documents.

[0028] The word group selection unit 114 selects a word group to be presented to the user from among a plurality of word groups. At this time, the word group selection unit 114 selects a word group to be presented to the user based on a score indicating the document narrowing performance of the suggested words. Specifically, the word group selection unit 114 calculates a score (hereinafter referred to as a group score) of each word group based on a score (hereinafter referred to as a word score) indicating the document narrowing performance of each suggested word belonging to each word group, compares the group scores of each word group, and selects a word group (hereinafter referred to as a selected group) to be presented to the user. At this time, the word group selection unit 114 selects a word group composed of suggested words with high document narrowing performance by selecting a word group with a high word score. The number of word groups to be selected may be one or more.

[0029] The word score, which indicates the document narrowing down performance, is an index indicating whether the word is an important word that characterizes the document. For example, the number of occurrences in the document, the entropy based on the number of occurrences, tf-idf, etc. can be used as the word score. All documents stored in the document DB 200 may be used to calculate the word score, or related documents extracted according to the user's input may be used. The word score of each suggested word may be calculated and stored in advance, or may be calculated when the group score is calculated. For example, the total value, maximum value, median value, average value, etc. of the word scores of each suggested word belonging to a word group may be used as the group score. In addition, the suggested words used to calculate the group score may be limited. For example, a predetermined number of suggested words may be extracted in descending order of word scores in each word group, and the group score may be calculated using only the word scores of the extracted suggested words. The group score can be used as an index indicating the effectiveness of the suggested words belonging to the word group for document narrowing down.

[0030] The suggested word presentation unit 115 presents the suggested words belonging to the selected word group to the user. Specifically, the suggested word presentation unit 115 displays the suggested words belonging to the selection group selected by the word group selection unit 114 on the display device 15 or the display device of the client terminal 300. At this time, only a predetermined number of suggested words may be displayed in descending order of word score among the suggested words belonging to the selection group.

[0031] Of the suggested words contained in the searched document, only the suggested words belonging to the selected word group are displayed on the display device of the client terminal 300. Each word group is generated for each document block classified according to its position in the document. For this reason, in one word group, suggested words with the same position in the document are extracted from each document. Therefore, only suggested words with the same position in the document are presented to the user.

[0032] In addition, the suggested words to be presented to the user are selected from a word group made up of suggested words with high document narrowing performance based on the word scores of the suggested words to which they belong, so that only important words that characterize the document are presented to the user.

[0033] (Document search processing) Next, the operation of the document search process executed by the document search device 100 will be described. The document search process is a process of presenting suggested words for narrowing down documents that the user wants to acquire. The document search device 100 starts the document search process based on receiving a question sentence or a search word input by the user from the client terminal 300. FIG. 3 is a flowchart showing an example of the procedure of the document search process. FIG. 4 is a diagram showing an example of the data flow in the document search process. Note that the processing procedures in each process described below are merely examples, and each process can be appropriately changed as much as possible. Also, steps can be omitted, replaced, and added to the processing procedures described below as appropriate depending on the embodiment.

[0034] Here, as an example, we will explain the case where a single word is entered as a search word, and suggested words are presented to help the user narrow down the documents they need from among HTML format documents (hereinafter referred to as procedural documents) that explain various procedures.

[0035] (Step S301) In the document search process, first, the document search unit 111 searches documents stored in the document DB 200 for documents related to a search word acquired from the client terminal 300. At this time, the document search unit 111 searches the document DB 200 for all documents containing the search word, and acquires the retrieved documents as search documents from the document DB 200. The document search unit 111 outputs the acquired search documents to the block division unit 112 as document search results.

[0036] (Step S302) Next, the block division unit 112 divides each document included in the search document into a number of document blocks. Fig. 5 is a diagram showing an example of the document structure of a procedural document 500 in HTML format. The procedural document 500 shown in Fig. 5 can be divided into a first document block 510 in which the "procedure name" is written, a second document block 520 in which the "paragraph names for each item related to the procedure" are written, and a third document block 530 in which "items in bullet points" are written. Each sentence included in the procedural document 500 in Fig. 5 has an HTML tag indicating that it is classified as a "procedure name". <h1> This is an HTML tag that indicates that the item is classified as a "paragraph name for each item related to the procedure."< / h1> <h2>、 , and the HTML tag indicating that it is classified as a "bullet item" The block division unit 112 uses HTML tags as document structure information to classify each sentence included in the searched document into one of document blocks of "procedure name," "paragraph names for each item related to the procedure," and "item list." Using the classification results of each sentence, the block division unit 112 divides each document into a document block corresponding to the "procedure name," a document block corresponding to the "paragraph names for each item related to the procedure," and a document block corresponding to the "item list." The block division unit 112 outputs the division results of each document to the word group generation unit 113 as block information.

[0037] (Step S303) Next, the word group generating unit 113 generates a word group for each document block using the division result of the document block. FIG. 6 is a schematic diagram showing how word groups are generated from a plurality of procedural documents 500. The word group generating unit 113 extracts suggested words from the first document block 510 of each procedural document 500, and generates a first word group 610 using the extracted suggested words. Similarly, the word group generating unit 113 generates a second word group 620 consisting of suggested words extracted from the second document block 520 of each procedural document 500, and a third word group 630 consisting of suggested words extracted from the third document block 530 of each procedural document 500. Only suggested words extracted from the same document block belong to each word group 610, 620, 630. The word group generating unit 113 outputs the generated word groups 610, 620, 630 to the word group selecting unit 114 together with the suggested words belonging to each word group.

[0038] (Step S304) Next, the word group selection unit 114 selects a word group to be presented to the user from the generated word groups 610, 620, and 630. Fig. 6 is a schematic diagram showing how a word group is selected from the word groups 610, 620, and 630. At this time, the word group selection unit 114 first calculates the entropy of each suggested word as a word score. The numerical value next to each suggested word in Fig. 7 indicates the entropy of each suggested word.

[0039] Next, the word group selection unit 114 calculates the sum of the entropy of the suggested words belonging to each word group as the group score of each word group 610, 620, 630. The word group selection unit 114 compares the group scores of each word group 610, 620, 630, and selects the first word group 610 having the highest group score as the word group to be presented to the user. Instead of the sum of the word scores, the maximum value, median value, average value, etc. of the word scores may be used as the group score. The word group selection unit 114 outputs the selected first word group 610 to the suggested word presentation unit 115 as the word group selection result.

[0040] (Step S305) Next, the suggestion word presentation unit 115 transmits all the suggestion words included in the selected first word group 610 to the client terminal 300, and displays the transmitted suggestion words on the display device of the client terminal 300, thereby presenting the suggestion words to the user. At this time, in addition to the suggestion words included in the first word group 610, a list of searched documents is displayed at the same time.

[0041] Note that only a predetermined number of suggested words may be presented to the user. In this case, the suggested word presentation unit 115, for example, refers to the word scores of the suggested words included in the first word group 610, selects a predetermined number of suggested words in descending order of word score, and presents the selected suggested words to the user.

[0042] The user can perform an operation to select a suggested word related to the document that the user wants to search from among the suggested words presented.

[0043] When one of the suggested words is selected by the user (step S306-YES), the document searching device 100 executes the processes of steps S301-S305 again. At this time, the document searching device 100 uses the selected suggested word as a search text to search for documents containing the selected suggested word from among the searched documents, and narrows down the documents again. After that, the document searching device 100 divides the narrowed down searched documents into document blocks, generates word groups for each document block, again selects word groups to be presented, and presents the suggested words included in the presented word groups to the user. This updates the suggested words presented to the user.

[0044] The user repeats the operation of selecting one of the suggested words presented until the user finds the desired document. This causes the above steps S301 to S306 to be repeatedly executed, narrowing down the documents and presenting suggested words repeatedly. When the user finds the desired document (step S306-NO), the document search process ends.

[0045] The effects of the document searching device 100 according to this embodiment will be described below.

[0046] The document search device 100 according to this embodiment includes a document search unit 111, a block division unit 112, a word group generation unit 113, and a word group selection unit 114. The document search unit 111 searches a document DB 200 that stores a plurality of documents for documents related to a search text input by a user. Specifically, the document search unit 111 searches the document DB 200 for documents that include words included in the search text. The word group generation unit 113 generates a plurality of word groups that classify suggested words extracted from the searched document. The word group selection unit 114 selects a word group to be presented to the user from the plurality of word groups.

[0047] The document search device 100 according to the present embodiment further includes a block division unit 112. The block division unit 112 divides each of the search documents into a plurality of document blocks. For example, the block division unit 112 classifies each sentence included in the search document into a plurality of document blocks based on the document structure. For example, HTML tags, the order of sentences in the document, and paragraph numbers of sentences are used as the document structure. The block division unit 112 divides each document into a plurality of document blocks by classifying each sentence included in the document into one of a plurality of document blocks. The word group generation unit 113 extracts suggested words used for document narrowing from the search document based on information on the document structure, and generates word groups for each document block that are composed of suggested words extracted from the same type of document block of each document. The word group selection unit 114 selects word groups to be presented to the user based on word scores indicating the document narrowing performance of the suggested words. At this time, the word group selection unit 114 calculates a group score for each word group using the word scores of the suggested words belonging to each word group, and selects a word group to be presented by comparing the group scores.

[0048] The word score may be, for example, an entropy score based on the number of occurrences of a word, the number of occurrences in a document, tf-idf, or other numerical value indicating the degree to which the word is important in characterizing the document. The group score may be, for example, the sum, median, average, or maximum value of the word scores.

[0049] The document retrieval device 100 further includes a suggested word presentation unit 115. The suggested word presentation unit 115 presents suggested words belonging to the selected word group to the user.

[0050] With the above configuration, the document search device 100 according to the present embodiment classifies the suggested word candidates extracted from each document into document blocks according to the document structure, so that the suggested word candidates can be divided into document blocks according to their positions in the document. Then, by recommending only words contained in a specific document block as suggested words to be used in narrowed search, only words that are similarly positioned in the document can be presented to the user as suggested words. When selecting suggested words to narrow down documents, multiple suggested words that are similarly positioned in the document are presented, so that the user can narrow down documents by comparing important words that characterize the documents, and can more efficiently search for documents containing the information he or she wants to know.

[0051] For example, as shown in FIG. 5-FIG. 7, when a first word group 610 composed of suggested words belonging to a first document block 510 is selected, a list of suggested words classified as "procedure name" is presented to the user. Words with the same position in the document are presented as search word options, so the user can appropriately determine which word to select to find a document containing the information he or she wants to know. In addition, suggested words may be classified into multiple document blocks based on the order of sentences in the document or the paragraph numbers of the sentences. Since sentences or paragraphs with the same order in the document are similarly positioned in the document, by presenting only suggested words belonging to the selected document block, it is possible to present only words with similar positions in the document to the user.

[0052] Furthermore, the word group selection unit 114 selects a word group consisting of suggested words with high document narrowing performance based on the word score indicating the document narrowing performance. Therefore, words that are important in the document and useful for distinguishing it from other documents can be presented to the user. Since the user can narrow down documents by comparing important words that characterize the documents, the user can more efficiently find documents that contain the information he or she wants to know.

[0053] (Modification of the first embodiment) The word group presented to the user may be one or more. When multiple word groups are presented to the user, the word group selection unit 114 selects, for example, the top two word groups with the highest group scores, and the suggested word presentation unit 115 presents the suggested words belonging to the selected multiple word groups to the user. In this case, the suggested word presentation unit 115 may display information about the word group to which each suggested word belongs in association with the suggested word. For example, as shown in FIG. 8, the name of the word group to which the suggested word belongs may be displayed in association with each suggested word. When the suggested words belonging to the selected word group are presented to the user, the information about the word group to which the suggested word belongs is presented so that the user can understand, so that the user can know which group each suggested word belongs to. This allows the user to select a keyword to search for a document containing the information he or she wants to know while comparing suggested words belonging to the same word group. Also, only when the number of suggested words belonging to the selected word group is small, multiple word groups may be selected to ensure the number of suggested words presented to the user. Even when one word group is presented to the user, information such as the name of the selected word group may be displayed together with the suggested words. By understanding the selected word group, the user can understand the position of the presented suggested words in the document.

[0054] Instead of displaying the name of the word group, the suggested word may be displayed in such a way that the word group to which it belongs can be distinguished by changing the color, font, and display position of the letters depending on the word group to which each suggested word belongs.

[0055] Second embodiment A second embodiment will be described. This embodiment is a modification of the configuration of the first embodiment as follows. Descriptions of the same configuration, operation, and effects as those of the first embodiment will be omitted. In this embodiment, multiple word groups are generated by classifying suggested words according to the meaning of the words.

[0056] 9 is a diagram showing an example of the configuration of the document searching device 100 according to this embodiment. As shown in Fig. 9, the processing circuit 11 includes a suggested word extracting unit 116 and a word group generating unit 117 instead of the block dividing unit 112 and the word group generating unit 113 in Fig. 2.

[0057] The suggestion word extraction unit 116 extracts suggestion words used to narrow down documents from the search document. For example, the suggestion word extraction unit 116 extracts a plurality of suggestion words from the entire search document by performing known natural language processing on each sentence included in the search document.

[0058] The word group generating unit 117 generates a plurality of word groups by classifying the suggested words extracted from the search document. The word group generating unit 117 of the present embodiment classifies each extracted suggested word into a plurality of items using classification information based on the meaning of the word, and generates a word group for each classification item. The classification information based on the meaning of the word is, for example, information that specifies the meaning of the word, the hierarchical relationship of the word, the hierarchical relationship of the word in the concept hierarchy, the hierarchical relationship based on the inclusion relationship of the word, the similarity relationship of the word, and the like. For example, thesaurus information can be used as the classification information based on the meaning of the word. In this case, a general Japanese thesaurus may be used, or a thesaurus specific to the industry to which the document to be searched belongs may be used. By using the thesaurus specific to the industry, the classification accuracy can be improved. The classification information based on the meaning of the word may be stored in the storage device 12 in advance, or may be acquired from an external system.

[0059] (Document search processing) Next, the operation of the document search process executed by the document search device 100 according to this embodiment will be described. FIG. 10 is a flowchart showing an example of the procedure of the document search process. Also, FIG. 11 is a diagram showing an example of the data flow in the document search process. Note that the processing procedures in each process described below are merely examples, and each process can be modified as appropriate as possible. Also, steps can be omitted, replaced, or added to the processing procedures described below as appropriate depending on the embodiment.

[0060] Here, as an example, a case will be described in which suggested words are presented to narrow down documents required by a user from documents explaining various insurance policies in the insurance industry (hereinafter referred to as insurance documents). (Step S1001) Next, the document search unit 111 searches documents related to the search word acquired from the client terminal 300 from the documents stored in the document DB 200 in the same manner as in step S301 in the first embodiment.

[0061] (Step S1002) Next, the suggested word extraction unit 116 extracts suggested words from each searched document. Fig. 12 is a diagram showing an example of an insurance document 1200. Fig. 12 is a schematic diagram showing how suggested words are extracted from a plurality of insurance documents 1200. As shown in Fig. 12, the suggested word extraction unit 116 extracts suggested words from all the searched insurance documents 1200, and outputs the extracted suggested word list 1210 to the word group generation unit 117.

[0062] (Step S1003) Next, the word group generating unit 117 generates a plurality of word groups using the meanings and inclusion relationships of the suggested words as classification information based on the meanings of the words. FIG. 13 is a schematic diagram showing how each suggested word included in the extracted suggested word list 1210 is classified to generate a plurality of word groups. FIG. 14 is a diagram showing an example of a thesaurus for the insurance industry. In FIG. 13, the word group generating unit 117 classifies each suggested word included in the suggested word list 1210 into one of "coverage target", "procedure content", and "service content" using the thesaurus for the insurance industry shown in FIG. 14. Then, the word group generating unit 117 generates a first word group 1310 to which the word used as "coverage target" belongs, a second word group 1320 to which the word used as "procedure content" belongs, and a third word group 1330 to which the word used as "service content" belongs. For example, when the word "automobile" is classified as "coverage" in the insurance industry thesaurus, the suggested word "automobile" is determined to belong to the first word group 1310, as shown in Fig. 13. The word group generation unit 113 outputs the generated word groups 1310, 1320, and 1330 to the word group selection unit 114, together with the suggested words belonging to each word group. 13 and 14, an example is described in which a thesaurus for the insurance industry is used as classification information based on the meaning of words, but each extracted suggested word may be classified using a general Japanese thesaurus as shown in Fig. 15. In this case, the word group generating unit 117 classifies each suggested word into categories such as "medical care," "biology," and "vehicles," and generates word groups to which the classified words belong for each category.

[0063] (Step S1004) Next, the word group selection unit 114 calculates a group score for each word group using the word scores of each suggested word, in a manner similar to the processing of step S304 in the first embodiment, and selects a word group to present to the user by comparing the group scores of each word group.

[0064] (Step S1005) Next, the suggestion word presentation unit 115 presents to the user the suggestion words included in the word group selected as the word group, in the same manner as in the process of step S305 in the first embodiment.

[0065] Also, similarly to the first embodiment, the user can repeat the operation of selecting one suggested word from the multiple suggested words presented until the user finds the desired document.

[0066] The effects of the document searching device 100 according to this embodiment will be described below.

[0067] The document search device 100 according to the present embodiment includes a document search unit 111, a word group selection unit 114, a suggested word extraction unit 116, and a word group generation unit 117. The suggested word extraction unit 116 extracts suggested words used to narrow down documents from the entire search document. The word group generation unit 117 generates a plurality of word groups into which suggested words extracted from the searched document are classified, similar to the word group generation unit 113 of the first embodiment. At this time, the word group generation unit 117 generates a plurality of word groups using classification information based on the meaning of words. The classification information is, for example, information including the meaning of words, the hierarchical relationship of words, the hierarchical relationship of words in the concept hierarchy, or the hierarchical relationship based on the inclusion relationship of words. The word group generation unit 117 classifies the extracted suggested words into a plurality of items using, for example, thesaurus information having classification information, and generates a plurality of word groups for each classification result. As in the first embodiment, the document search device 100 further includes a suggested word presentation unit 115 that presents suggested words belonging to the selected word group to the user.

[0068] With the above configuration, in this embodiment too, candidate suggested words extracted from each document are classified into multiple word groups according to their position in the document, and only words belonging to specific word groups are recommended as suggested words to be used in narrowed-down searches, so that only words with similar positions in the document can be presented to the user as suggested words, just like in the first embodiment.

[0069] For example, as shown in Figures 12-13, when the first word group 1310 is selected, a list of suggested words classified as "covered" is presented to the user. Since words with the same position in the document are presented as search word options, the user can appropriately determine which word to select in order to search for a document containing the desired information.

[0070] Furthermore, as in the first embodiment, a word group composed of words in a document that have high document narrowing-down performance is selected, so that a user can narrow down documents using suggested words that represent the characteristics of the document, and can more efficiently find documents that contain the desired information.

[0071] (Modification of the second embodiment) When suggestion words belonging to the selected word group are presented to the user, multiple words classified into the same meaning or type may be integrated into one word using thesaurus information. For example, among the suggestion words belonging to the first word group 1310 in FIG. 13, the words "dog" and "cat" may be integrated into the word "animal" and presented. In this case, for example, the sum or average value of the word scores of "dog" and "cat" is used as the word score of "animal". When selecting and presenting a predetermined number of suggestion words with high word scores from the suggestion words belonging to the selected word group, by integrating and presenting words with similar meanings, a larger variety of words can be presented to the user as options.

[0072] (Third embodiment) The third embodiment will be described. This embodiment is a modification of the configurations of the first and second embodiments as follows. Descriptions of the configurations, operations, and effects similar to those of the first and second embodiments will be omitted. In this embodiment, a plurality of word groups are generated based on the document structure, and further, a plurality of word groups are generated based on the meanings of words.

[0073] Fig. 16 is a diagram showing an example of the configuration of the document searching device 100 according to this embodiment. As shown in Fig. 16, the processing circuitry 11 includes a document searching unit 111, a block dividing unit 112, a word group generating unit 113, a word group selecting unit 114, and a suggested word presenting unit 115 described in the first embodiment, as well as a suggested word extracting unit 116 and a word group generating unit 117 described in the first embodiment.

[0074] 17 is a diagram showing an example of a data flow in the document search process executed by the document search device 100 according to this embodiment. In this embodiment, the document search unit 111 outputs the document search result to both the block division unit 112 and the suggested word extraction unit 116.

[0075] In the block division unit 112, similarly to the first embodiment, each search document is divided into a plurality of document blocks, and the division results are output as block information to the word group generation unit 113. In the word group generation unit 113, a plurality of word groups are generated for each document block, and the generated word groups are output to the word group selection unit 114.

[0076] In the suggestion word extraction unit 116, similarly to the second embodiment, suggestion words are extracted from each search document, and the extracted suggestion words are output to the word group generation unit 117. In the word group generation unit 117, a plurality of word groups are generated by classifying the suggestion words based on the meanings of the words, and the generated word groups are output to the word group selection unit 114.

[0077] Word group selection unit 114 acquires multiple word groups from each of word group generation units 113 and 117, and selects a word group to present to the user from all acquired word groups. At this time, word group selection unit 114 calculates a group score for all acquired word groups using the word scores of the suggested words, for example, and selects the word group with the highest group score from among all word groups as the word group to be presented. Note that one word group with the highest group score may be selected, or multiple word groups may be selected in descending order of group score.

[0078] With the above-described configuration, the document search device 100 of this embodiment can select word groups that are more useful for document narrowing down by selecting word groups with high group scores that represent the document narrowing down performance within a document from both word groups classified based on document structure and word groups classified according to classifications based on word meanings.

[0079] The word group selection unit 114 may randomly select the word groups to be presented without using the word scores and group scores. Even in this case, only words that belong to a specific word group are presented as suggested words, so that the user can easily compare suggested words that are similarly positioned in the document and appropriately determine which words to select in order to find a document containing the desired information.

[0080] Thus, according to any of the above-described embodiments, it is possible to provide a document retrieval program, a document retrieval device, and a document retrieval method that are capable of presenting suitable search keyword candidates in a document retrieval using a search keyword.

[0081] The present invention is not limited to the above-described embodiment, and the components can be modified and embodied in the implementation stage without departing from the gist of the invention. In addition, various inventions can be formed by appropriately combining the multiple components disclosed in the above-described embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0082] 1...document search system, 100...document search device, 200...document DB, 300...client terminal, 11...processing circuit, 111...document search unit, 112...block division unit, 113, 117...word group generation unit, 114...word group selection unit, 115...suggested word presentation unit, 116...suggested word extraction unit, 12...storage device, 13...input device, 14...communication device, 15...display device, 500, 1200...document, 510, 520, 530...document block, 610, 620, 630, 1310, 1320, 1330...word group, 1210...suggested word list. < / h2>

Claims

1. On the computer, A document search function that searches a document database storing multiple documents for documents that contain words included in a search text entered by a user; a block division function for dividing each of the retrieved documents into a plurality of document blocks based on information regarding the document structure; a word group generating function for extracting suggested words for use in narrowing down documents for each of the document blocks and generating word groups composed of the suggested words for each of the document blocks; a word group selection function for selecting a word group to be presented to a user based on a score indicating the document narrowing down performance of the suggested words; A document search program to achieve this.

2. On the computer, A document search function that searches a document database storing multiple documents for documents that contain words included in a search text entered by a user; a suggestion word extraction function for extracting suggestion words to be used for narrowing down documents from the searched documents; a word group generating function for generating a plurality of word groups by classifying the extracted plurality of suggested words using classification information based on the meaning of the words; a word group selection function for selecting a word group to be presented to a user based on a score indicating the document narrowing down performance of the suggested words; A document search program to achieve this.

3. The information about the document structure includes HTML tags, a sentence order, or a sentence paragraph number.

2. The document retrieval program according to claim 1.

4. The classification information includes a meaning of a word, a hierarchical relationship of words, a hierarchical relationship of words, a hierarchical relationship of words in a concept hierarchy, or a hierarchical relationship based on an inclusion relationship of words.

3. The document retrieval program according to claim 2.

5. the word group selection function calculates a sum, an average, a maximum or a median of the score for each of the word groups, and selects a word group to be presented to the user based on the calculation result; 3. The document retrieval program according to claim 1.

6. the word group selection function selects one word group as a word group to present to the user; 3. The document retrieval program according to claim 1.

7. the word group selection function selects a plurality of word groups as word groups to be presented to the user; 3. The document retrieval program according to claim 1.

8. In order to further realize a suggestion word presentation function of presenting to a user suggestion words belonging to a selected word group, 3. The document retrieval program according to claim 1.

9. the suggestion word presentation function presents to the user information indicating the word group to which the suggestion word belongs in addition to the suggestion word belonging to the selected word group; 9. The document retrieval program according to claim 8.

10. On the computer, A document search function that searches a document database storing a plurality of documents for documents related to a search text input by a user; a word group generating function that generates a plurality of word groups by classifying the suggested words extracted from the searched documents using information about the document structure or classification information based on the meaning of words; a word group selection function for selecting a word group to be presented to a user from among the plurality of word groups; A document search program to achieve this.

11. a document search unit that searches a document database storing a plurality of documents for documents related to a search text input by a user; a word group generating unit that generates a plurality of word groups by classifying the suggested words extracted from the searched documents using information about document structure or classification information based on the meaning of words; a word group selection unit that selects a word group to be presented to a user from among the plurality of word groups; A document search device comprising:

12. Searching for documents related to a search text input by a user from a document database storing a plurality of documents; generating a plurality of word groups by classifying the suggested words extracted from the searched documents using information about document structure or classification information based on the meaning of words; selecting a word group from the plurality of word groups for presentation to a user; A document retrieval method comprising:

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