JP2014102625A - Information retrieval system, program, and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To output a retrieval result having less retrieval leakage and retrieval noise in an information retrieval system.SOLUTION: An information retrieval system 1 comprises: a technology classification database 31 storing technology fields, technology ranges (themes) belonging to the fields and technology characteristics (terms) for each theme; a technology content database 35 accumulating technology contents; an input character string acquisition part 11 acquiring an input character string from a retriever; a conceptualization part 15 collating the input character string with the terms stored in the technology classification database 31, extracting themes including matched terms, specifying one theme from among the extracted themes, and extracting a term group including the specified theme; a content search part 17 performing text search on the technology content database 35 using the term group as a keyword, and acquiring a technology content having a good evaluation; and a content display part 19 outputting display data for displaying the acquired technology content.

Description

  The present invention relates to information search processing. More specifically, the present invention relates to a search process for searching for information by conceptualizing a range of technology desired to be searched from a given character string.

  In engineering, product planning, etc., collecting technical information is indispensable. As technical information, information stored in a web, which is a document system used as standard on the Internet, an intranet, and the like is widely used. A text search process is used as means for searching for such information.

  As a conventional search method, there is a search method using a given character string as a keyword. For example, it is implemented in a product search system that searches for a product by inputting a character string indicating a product name or specification (conventional method ( 1)).

  As another conventional search method, there is a method of performing data mining on a large amount of text data such as free text, and searching for information by analyzing correlations and appearance patterns. (Conventional method (2)).

  As another conventional search method, there is a method of assigning a classification code to a technical document to be searched and performing a search using the classification code. For example, a patent search device that searches a patent publication with a classification is known. (Conventional method (3)).

JP 2002-351896 A

  Since the conventional method (1) is a match search with a given keyword, there is a problem that a desired search result cannot be obtained unless a product name, specification, and terminology are input.

  However, there are not many searchers who can input an appropriate keyword for obtaining desired technical information. For example, if you want to get information about "means for drilling holes in a glass plate", you can get search results related to "drill" of the means you already know, but other means you really want to know, For example, technical information related to laser, water jet, punching, etc. cannot be obtained as a search result.

  In general, the search accuracy depends on whether a searcher can input an appropriate keyword. However, the need for searching for technical information arises because there is not enough knowledge about the technical information to be searched, and in most cases the need for searching is no longer necessary when the technical information to be searched is sufficient. For this reason, it is difficult for searchers to come up with appropriate keywords.

  Although the above conventional method (2) can solve the problem of the conventional method (1), there is another problem. That is, since the conventional method (2) provides an associative result using the co-occurrence of a given word, there is a problem that there are many search results (search noise) that do not match the original search purpose or intention. is there.

  The conventional method (3) can solve the problems of the conventional methods (1) and (2), but has another problem. That is, when the number of classification codes assigned to the search target information is small, the search target classification is not flexible, but when there are many classification codes, there is a problem of search noise. Furthermore, when the keyword input by the searcher is not appropriate, the search range based on the classification code becomes inappropriate, and search omission may occur. In addition, the search target is limited to information with classification codes, and there is a problem that information that can be collected is limited. Another problem is that it is inconvenient for a searcher because a cross-sectional search cannot be performed for information such as articles and products stored in other databases.

  The present invention has been made in consideration of these conventional methods, and its purpose is to reduce search noise and search omission even when a word or sentence input by a searcher is not appropriate as a search keyword, and It is an object of the present invention to provide an information search technique capable of searching for a general search target.

  The information search system according to the present invention has a plurality of viewpoints on a field indicating a range to which the technology is applied, a theme indicating a range of the technology belonging to the field, and characteristics of the technology included in the technology range for each theme. A technical classification database that stores technical classifications that define terms associated with each other, and a technical content database that stores technical contents indicating technical information. The information search system further includes an input character string acquisition unit that acquires an input character string that is a word or a combination of words input by a searcher, and a technical classification term stored in the technical classification database. A conceptualization unit for collating in a column, extracting all themes including matching terms, identifying at least one theme from the extracted themes, and extracting a plurality of term groups included in the identified theme; and the extraction A content search unit that searches the technical content database by using the term group as a keyword, evaluates the searched technical content by a predetermined evaluation method, and acquires the technical content with good evaluation; and the acquired technical content A content display unit that outputs display data to be displayed.

  According to the information search system described above, it is possible to generate a search condition (search keyword) indicating a technical concept that the searcher originally wants to search from a character string input by the searcher, and to search technical information. For example, even if an appropriate search keyword is not given by the searcher, the range of the technology that the searcher wants to search based on the input character string is specified, and the concept related to the specified technology range is used. By performing the search process, the search target is expanded, and further, the search result is evaluated, so that a search result with less search omission and search noise can be provided.

It is a figure which shows the block structural example of the information search system in one Example. It is a figure which shows the block structural example of the conceptualization part in one Example. It is a figure which shows the data structural example of the field information and theme information of the technical classification database in one Example. It is a figure which shows the data structural example of the term information of the technical classification database in one Example. It is a figure which shows the data structural example of the term information of the technical classification database in one Example. It is a figure which shows the example of a data structure of the text database with a classification | category in one Example. It is a figure which shows the data structural example of the technical content database in one Example. It is a figure which shows the example of a processing flow of the outline | summary process of the information search system in one Example. It is a figure which shows the example of a screen which an information search system displays in one Example. In one Example, it is a figure which shows the example of a screen showing the search result which an information search system displays. It is a figure which shows the example of a more detailed process flow of the theme specific process in the 1st block structural example in one Example. It is a figure which shows the example of a more detailed process flow of the theme specific process in the 2nd block structural example in one Example. It is a figure which shows the example of a more detailed process flow of the field specific process in one Example. It is a figure which shows the example of a screen provided with the field selection area in one Example. It is a figure which shows the example of a screen which displays the literature information and product information of a search result in one Example. It is a figure which shows the example of a screen which displays the company information and product information of a search result in one Example. It is a figure which shows the hardware structural example of the information search system in one Example.

  Hereinafter, an information search system disclosed as one embodiment of the present invention will be described.

  FIG. 1 is a diagram illustrating a block configuration example of an information search system according to an embodiment.

  The information search system 1 is an information processing system that generates a search condition from a character string input by a searcher based on a previously prepared technical classification system, and searches for technical information using the generated search condition.

  The technology classification system included in the information search system 1 includes field information indicating a field (field) based on an industry to which the technology is applied, theme information indicating a category (theme) indicating the range of technologies belonging to each field, and 1 It consists of term information that defines and defines technical terms (terms) classified into a plurality of viewpoints.

  In other words, the technical classification system includes a plurality of fields, and each field has one or a plurality of themes as a subordinate structure. Furthermore, each theme has one or more hierarchical terms belonging to one or more viewpoint categories. Details of the information constituting the technical classification system will be described later.

  The information retrieval system 1 includes an input character string acquisition unit 11, a morpheme analysis unit 13, a conceptualization unit 15, a content search unit 17, and a content display unit 19, a technology classification database 31, a classified text database 33, a technology A storage device for the content database 35. The search device 10 of the information search system 1 is connected to a searcher terminal 5 that is an information processing terminal used by a searcher via a network N.

  The input character string acquisition unit 11 of the search device 10 acquires a character string (input character string) input by the searcher at the searcher terminal 5. The input character string is a word, a combination of words, or an arbitrary sentence.

  When the input character string acquisition unit 11 receives an input of a sentence as an input character string, the morpheme analysis unit 13 performs a morphological analysis on the input character string and extracts an independent word from the morpheme. The morpheme analysis unit 13 performs a known general morpheme analysis process.

  The conceptualization unit 15 searches for a theme indicating a range of technology that the searcher wants to search using words, combinations of words, or independent words extracted from the input character string, and uses a predetermined evaluation method. A theme with good evaluation is specified, and a term group indicating technical features belonging to the specified theme is acquired.

  The content search unit 17 performs OR condition search processing for the technical content database 35 using the acquired term group, evaluates the search result by a predetermined evaluation method, and acquires technical content with good evaluation.

  The content display unit 19 displays the acquired technical content on the searcher terminal 5.

  The conceptualization unit 15 of the search device 10 includes a theme search unit 151 and a term group acquisition unit 153 as one configuration example (first configuration example) as shown in FIG. Furthermore, when taking the first configuration example, the classified text database 33 of the information search system 1 is not necessary.

  The theme search unit 151 extracts themes that match the retrieved independent words from the themes constituting the technical classification system stored in the technical classification database 31, and evaluates the themes with a predetermined evaluation method, Identify at least one good theme.

  The term group acquisition unit 153 acquires all the terms (term groups) included in the identified theme.

  The conceptualization unit 15 can further include a field specifying unit 159 in the first configuration example.

  The field specifying unit 159 extracts each field to which each theme extracted by the theme search unit 151 belongs from the technical classification database 31 and evaluates each extracted field using the evaluation of the theme belonging to the field. Identify the evaluation field. Furthermore, when there are a plurality of fields with similar evaluations, the field specifying unit 159 displays a plurality of fields corresponding to the searcher terminal 5 and specifies the fields indicated in the input field selection.

  The conceptualization unit 15 of the search device 10 includes a classified text search unit 157 and a term group acquisition unit 153 as another configuration example (second configuration example), as shown in FIG.

  The classified text search unit 157 extracts and extracts the text having the term that matches the independent word extracted from the term given to the text stored in the classified text database 33 and the term given to the text. Each theme extracted by the evaluation method using text is evaluated, and at least one theme with good evaluation is specified.

  The conceptualization unit 15 can further include a field specifying unit 159 in the second configuration example.

  Since the term group acquisition unit 153 and the field identification unit 159 are the same as those in the first configuration example, the description thereof is omitted.

  The technology classification database 31 is a database that holds a classification system that classifies technologies from various viewpoints including attributes, uses, and purposes.

  3 to 5 are diagrams showing data configuration examples of the technology classification database 31.

  The technology classification database 31 includes field information 311, theme information 313, and term information 315.

  The field information 311 is information indicating a field (field) classified based on the industry to which the technology is applied. As shown in FIG. 3A, in the field information 311, a “field name” indicating the name of each field and a “field ID” that is field identification information are stored in association with each other. For example, the field ID “2B” and the field name “livestock and fishery” indicate that the technology applied to livestock and fishery among natural resources is classified.

  The theme information 313 is information indicating a category (theme) indicating the scope of technology. As shown in FIG. 3B, the theme information 313 includes a “theme name” that indicates the name of the technical range, a “theme ID” that is the theme identification information, and a “field ID” that indicates the field to which the theme belongs. It is stored in association with each other. For example, the theme ID “104” and the theme name “aquaculture” indicate that the technology belongs to the livestock and fisheries of the field ID “2B” and is a classification into which technologies related to aquaculture are classified.

  The term information 315 is information indicating terminology (term) indicating technical features classified into one theme. The technical features indicated by the terms of the term information 315 are classified and defined based on a plurality of viewpoints.

  As shown in FIG. 4 and FIG. 5, the term information 315 is constructed for each theme and associates “viewpoint classification” indicating the name of the classification on the viewpoint with “viewpoint code” that is identification information of the viewpoint classification. Further, for each viewpoint classification, a correspondence between a “term name” indicating a technical feature and a “term code” that is identification information of the term is defined. Each viewpoint classification includes a set of one or a plurality of term codes and term names (hereinafter simply referred to as terms), and a plurality of terms may be defined hierarchically.

  The viewpoint classification is set in a multifaceted manner and corresponding to the theme. In each viewpoint classification, an object (including an issue), an object (thing etc.), an application, a structure, a material, a manufacturing method, a usage method, a management method, and the like are arbitrarily set according to the theme.

  FIG. 4 is an example of the term information 315 for the theme name “Aquaculture (104)”. The term information 315 in FIG. 4 includes, for example, “fish (010)”, “squid / octopus (020)”, “crustacea (030)”, etc., when the viewpoint name (viewpoint code) is “object (AA)”. It is shown that “primary salmon (011)” is set as the lower term of the term “fish (010)”.

  FIG. 5 is an example of term information 315 for the theme name “Feed (150)”. The term information 315 in FIG. 5 includes, for example, “net crack (010)”, “small seaweed basin (020)”, and “land aquaculture equipment (030)” when the viewpoint name (viewpoint code) is “device (BA)”. It is shown that primary terms such as can be set and lower terms can be set.

  The classified text database 33 is a database that accumulates text to which themes and terms based on the classification system of the technical classification database 31 are assigned as classification codes.

  FIG. 6 is a diagram illustrating a data configuration example of the classified text database 33.

  The text stored in the classified text database 33 includes a document ID, a title, a theme ID, a term code, and a text (body). “Document ID” is information for identifying text, “Title” is the title of the document, and “Text” is the content of the text of the document. One or more classification codes, that is, one or more theme IDs may be set in the text, and one or more term codes may be set for each theme ID.

  The technical content database 35 is a database that accumulates technical content indicating various technical information. The information search system 1 may include a plurality of technical content databases 35. The technical content database 35 includes a database to which the information search system 1 can be connected via a network such as the Internet or an intranet.

  Here, the technical information included in the technical content covers not only the technology itself but also information related to the technology of companies or research institutions that provide the technology, and the technical content is a text indicating the technical information. Data including data may be used, and image data, audio data, and the like may be included. Technical contents are specifically patent documents, papers, product manuals, product catalogs, specifications, technical explanations, analysis / application examples, experimental reports, technical news, technical magazines, news releases, companies, research institutions Business reports.

  FIG. 7 is a diagram illustrating a data configuration example of technical content stored in the technical content database 35.

  FIG. 7A shows an example data structure of technical content (product content) that provides product information. The product content in FIG. 7A includes data such as a product ID, a product name, a company name, an explanatory text, and a link. “Product ID” is information for identifying the product, “Product name” is the name of the product, and “Company name” is the name of the company that manufactures and provides the product. The “description text” is a body text that explains the feature, use, etc. of the product. “Link” is arbitrary information, and indicates a link to a site to a company or related organization that provides information related to a product.

  FIG. 7B shows a data configuration example of technical content (paper content) that provides a technical paper. The article content in FIG. 7B includes data such as a document ID, a title, an author name, a summary text, and a body text. “Document ID” is information for identifying a paper, “Title” is the title of the paper, and “Author” is the name of the paper author. “Summary text” is text describing the summary of the paper, and “body text” is text of the paper itself.

  Next, the process flow of the information search system 1 will be described. In the following description, the general interface function and its operation regarding the input of information from the searcher and the output of information to the searcher are known and will not be described.

  FIG. 8 is a diagram illustrating a processing flow example of the outline processing of the information search system 1.

  Step S1: The input character string acquisition unit 11 of the search device 10 acquires a character string (input character string) input by the searcher at the searcher terminal 5. The input character string is a word, a combination of words, a free sentence, or the like.

  FIG. 9 is a diagram illustrating an example of a screen displayed by the information search system 1. A screen 100 shown in FIG. 9 is displayed on the searcher terminal 5. The screen 100 includes a character input area 101 in which a searcher can freely input a phrase or sentence, a search button 103 for instructing execution of a search, and a result display area 105 for displaying technical contents of the search result.

  When the search button 103 is pressed by a mouse click or the like, the input character string acquisition unit 11 acquires the input character string input to the character input area 101. In this example, “aquaculture improvement” is acquired. In this example, “aquaculture” and “improvement” are extracted.

  Step S2: The morpheme analysis unit 13 performs a morpheme analysis process on the input character string acquired by the input character string acquisition unit 11, and extracts an independent word (word).

  Step S3: The conceptualization unit 15 searches the theme using either the technical classification database 31 or the classified text database 33 using the extracted word, and specifies one best evaluation theme from the searched themes.

  In this example, it is assumed that the theme IDs are “104 (culture)”, “150 (feed)”,... In the order of good evaluation values, and “104 (culture)” is specified as the best evaluation theme. .

  Step S4: The term group acquisition unit 153 extracts a plurality of terms belonging to the identified theme. Alternatively, when the term information 315 of the technical classification database 31 has a hierarchical structure, the term group acquisition unit 153 selects a term that matches the input character string from terms belonging to the specified theme and a parent-child relationship (parent-child relationship) You may make it extract only the term which has. That is, the term group acquisition unit 153 extracts all the terms belonging to the lower order of the terms matching the input character string, the terms connected to the upper order, or both of these terms.

  In this example, the term group acquisition unit 153 extracts all the terms from the term information 315 of the theme IDs “104 (culture)” and “150 (feed)” in the technical classification database 31.

  Step S5: The content search unit 17 performs a text search of the OR condition for the technical content in the technical content DB 35 using the extracted term group. The content search unit 17 can execute any search method as long as it is a known search method. For example, the content search unit 17 executes a search method called a weighted OR search or an evaluation OR search.

  Step S6: The content display unit 19 generates, from the identified technical content, a technical content having a high similarity to the term group, and generates display data including the technical content in the order of good evaluation. 5 displays the display data.

  FIG. 10 is a diagram illustrating an example of a screen that displays search results.

  The content display unit 19 displays in the result display area 105 of the screen 100 shown in FIG. 10 displayed on the searcher terminal 5 the technical content of the search result by the term group belonging to the identified theme. In this example, display data including product information shown in FIG. 7A, product information shown in FIG. 7B, and literature information is generated and displayed. It should be noted that the content display unit 19 does not indicate the type of technical information corresponding to the pressed display area by the mouse click operation (pressed) of the next display button (next button) 105 ′ provided in the result display area 105 of the screen 100. Display technical contents in order of good evaluation.

  Further, the content display unit 19 displays, on the screen 100, themes excluding the specified theme from the extracted themes in order of good evaluation, and displays a theme selection area 113 that can be selected by the searcher. In this example, themes such as “feed”,... Are displayed in the theme selection area 113 in the order of evaluation.

  When a theme different from the theme whose search result is displayed in the result display area 105 is selected in the theme selection area 113 of the screen 100, the conceptualization unit 15 sets the selected theme as a specified theme (step S3 ), All term groups belonging to the theme are extracted (step S4), and content search processing is executed with the extracted term groups (step S5). The content display unit 19 displays the screen 100 showing the content search result by the term group extracted from the selected theme (step S6).

  Below, the more detailed process of the theme search process of step S3 is demonstrated.

  FIG. 11 is a diagram illustrating a more detailed process flow example of the theme search process in the first configuration example.

  The theme search unit 151 of the conceptualization unit 15 uses the words extracted by the morphological analysis unit 13 to perform an OR condition search process for terms in the technical classification database 31 and extracts all themes having matching terms (step S31). ).

  In this example, the theme IDs “104 (culture)”, “150 (feed)”, etc. are searched from the theme information 313 of the technical classification database shown in FIG. 3B by the terms “aquaculture” and “improvement”. Suppose.

  The theme search unit 151 uses the extracted terms to evaluate each searched theme by a predetermined evaluation method (step S32). For example, the theme search unit 151 evaluates the searched theme based on the rarity, duplication, and completeness of terms. Rareness is a measure that examines the number of themes that have terms that match a word, and the smaller the number of themes that have terms, the better the evaluation of the themes that have the terms. Redundancy is a measure by which the number of occurrences of a term that matches a word in one theme is examined, and the larger the number of occurrences in the theme, the better the evaluation of the theme having that term. Comprehensiveness is a measure by which the ratio of the term to the whole term of the theme is examined, and the higher the ratio of the term matching the word to all the terms, the better the evaluation of the theme having the term. The theme search unit 151 calculates an evaluation value of each extracted theme by using one or a combination of these scales.

  Then, the theme search unit 151 specifies the theme with the best evaluation (step S33).

  FIG. 12 is a diagram illustrating a more detailed process flow example of the theme search process in the second configuration example.

  The classified text search unit 157 uses the independent words (words) extracted by the morphological analysis unit 13 to perform a text search on the classified text stored in the classified text database 33 using an OR condition, and finds the classified text. Extract (step S35).

  The classified text search unit 157 may narrow down the classified text to be acquired, and acquire a predetermined number of classified texts. In this example, the classified text search unit 157 evaluates the classified text by calculating the rarity, redundancy, and completeness of the words as the weighting of the words, as in the process of step S32 in FIG. Get a good number of classified texts. Note that the classified text search unit 157 may execute another known narrowing process.

  Next, the classified text search unit 157 extracts themes given to the acquired classified texts (step S36), evaluates the extracted themes, and extracts a predetermined number of themes in order of good evaluation ( Step S37). For example, the number of classified texts is calculated for each extracted theme, and the higher the number of classified texts, the better the evaluation. Further, instead of using the number of classified texts, an evaluation using the similarity of terms that match a word may be performed, or an evaluation combining the similarity and the number of classified texts may be performed.

  The classified text search unit 157 specifies the theme of the best evaluation (step S38).

  Further, the information search system 1 can cause the searcher to select the field to which the extracted theme belongs, and display the search result of the selected field. In this case, the field specifying unit 159 of the information search system 1 executes a field specifying process between steps S3 and S4 shown in FIG. Further, the process of step S3 is re-executed for the field specified by the field specifying process described below.

  In the information search system 1, when the conceptualization unit 15 of the search device 10 includes the field specifying unit 159, the field specifying unit 159 performs the following processing.

  FIG. 13 is a diagram showing a more detailed processing flow example of the field specifying process.

  The field specifying unit 159 acquires the field to which each theme extracted in the process of step S3 executed by the theme search unit 151 in the first configuration example or the classified text search unit 157 in the second configuration example belongs ( Step S41).

  The field specifying unit 159 summarizes the extracted themes for each field (step S42) and evaluates each field (step S43). In this example, the field specifying unit 159 sets the sum of evaluation values of the collected themes as the field evaluation value as the field evaluation.

  When there are a plurality of fields with similar calculated evaluation values (Y in step S44), the field specifying unit 159 displays a plurality of field names to the searcher to acquire the searcher's field selection (step S45), The field indicated in the field selection is specified (step S46). If there are not a plurality of fields with similar evaluation values (N in step S44), the field with the best evaluation value is specified (step S47).

  FIG. 14 is a diagram showing an example of a screen having a field selection area 121 for selecting a field. A screen 100 shown in FIG. 14 is an example of a screen showing search results when the word extracted from the input character string is “ramen”.

  The extracted word “ramen” is a term related to the structure of structures such as bridges, and is also the name of a grain processed product. The evaluation values of the two fields are close.

  The field specifying unit 159 displays two fields “bridge or overpass” specified from “ramen” and “cereal-derived products, soups, and other foods” in the field selection area 121 of the screen 100, and the searcher's field Accept selection.

  This allows the searcher to select a technical field, even if the words extracted from the input character string are technical terms used in a plurality of fields and it is difficult to determine the technical field to be searched. Search results can be displayed.

  FIG. 15 and FIG. 16 are diagrams showing other screen examples displayed on the searcher terminal 5 by the information search system 1.

  The information search system 1 can display the technical content as a search result for each type of technical information. In this case, the content search unit 17 searches across a plurality of technical content databases 35 each storing product information, literature information, company information, etc., and classifies the searched technical content based on the type of technical information. View from technical content, good evaluation.

  FIG. 15 is a diagram illustrating an example of a screen when document information and product information are displayed as search results. The screen 100 shown in FIG. 15 includes a document search result display area 115 indicating document information and a product search result display area 117 indicating product information as display areas for search results corresponding to the result display area 105.

  Mouse click operation of the next display button (next button) 115 ′ (not shown) provided in the document search result display area 115 of the screen 100 or the next display button (next button) 117 ′ provided in the product search result display area 117. By (pressing), the content display unit 19 displays technical contents that are not displayed with the type of technical information corresponding to the pressed display area in the order of good evaluation.

  FIG. 16 is a diagram showing an example of a screen when displaying company information and product information as search results. A screen 100 shown in FIG. 16 includes a product search result display area 117 and a company search result display area 119 indicating company information as display areas for search results corresponding to the result display area 105.

  Furthermore, the information search system 1 can set link information for other related technical information and subsidiary information in the technical information displayed on the screen 100.

  When generating the search result display data to be displayed on the screen 100, the content display unit 19 can add link information to a related site or the like for each technical content of the search result. For example, as shown in FIG. 16, the content display unit 19 sets and displays link information to a company site related to the product in each product information to be displayed in the product search result display area 117 of the screen 100.

  The search device 10 of the information search system 1 described above can be implemented as dedicated hardware including the processing unit shown in FIG.

  The search device 10 includes a CPU 301, a memory 302, a display control unit 304, a display device 303, a storage device (hard disk) 305, an input device (keyboard) 306, and a communication control unit 307 as shown in FIG. It can be implemented as a computer 300 connected by, for example.

  Furthermore, the search device 10 can be implemented as a program that can be executed by the computer 300. In this case, a program that realizes the function of the processing unit of the information search system 1 shown in FIG. 1 is installed and executed on the computer 100.

  That is, an execution program that causes the computer 300 to execute the functions of the input character string acquisition unit 11, the morphological analysis unit 13, the conceptualization unit 15, the content search unit 17, and the content display unit 19 illustrated in FIG. By doing so, the search device 10 can be implemented. The execution program is not only a recording medium such as a CD-ROM, CD-RW, DVD-R, DVD-RAM, DVD-RW, or flexible disk, but also other storage devices provided at the end of the communication line. It may be stored in a computer hard disk or the like.

  Note that the elements constituting the information search system 1 may be realized in any combination. A plurality of components may be realized as one member, and one component may be configured from a plurality of members. In addition, the information search system 1 is not limited to the above-described embodiment, and various improvements and changes may naturally be made without departing from the gist of the present invention. For example, in the above-described embodiment, the search target of the information search system 1 has been described using technical information such as literature information, product information, and company information as an example. It can also be applied to other information retrieval such as experiment reports.

  As described above, according to the information search system 1 according to the present invention, it is desired to search instead of a search process using only words (culture, improvement) extracted from the character string “improvement of culture” input by the searcher. It is possible to execute a search process using terms that form a concept of technology in a range specified as a technology-related theme. As a result, a search process is performed using a terminology (eg, a term group shown in FIG. 4) representing a concept that the searcher cannot present with the input character string, and a search result (technical information) having a good evaluation is obtained from the entire search result. ) Is displayed on the searcher terminal 5.

  That is, according to the information search system 1, technical content that has a low evaluation in the search result and is less likely to be displayed by a conventional search method using an input character string, for example, the product shown in FIG. Product information and the like of the name “disposable product” can be displayed at the top of the search results, and a search process in consideration of search noise and search omission can be realized.

  Therefore, the searcher is very likely to be able to acquire information content that matches the technical concept to be searched even if the input word combination or sentence is not appropriate.

  Further, according to the information search system 1, a plurality of themes related to the input character string can be displayed and can be selected by the searcher.

  Therefore, the searcher is likely to be able to acquire a more appropriate search result by recognizing a range similar to or related to the technique to be searched.

DESCRIPTION OF SYMBOLS 1 Information search system 10 Search apparatus 11 Input character string acquisition part 13 Morphological analysis part 15 Conceptualization part 151 Theme search part 153 Term group acquisition part 157 Classification text search part 159 Field specification part 17 Content search part 19 Content display part 31 Technical classification Database (DB)
33 Text database with classification (DB)
35 Technical Content Database 5 Searcher Terminal

Claims (8)

A system for retrieving information,
A field indicating a range to which the technology is applied, a theme indicating the range of the technology belonging to the field, and a term indicating the characteristics of the technology included in the technology range in association with a plurality of viewpoints for each theme. A technical classification database for storing technical classifications;
A technical content database for storing technical content indicating technical information;
An input string acquisition unit that acquires an input string that is a word or a combination of words input by a searcher;
The technical classification terms stored in the technical classification database are collated with the input character string, all themes including the matching terms are extracted, at least one theme is identified from the extracted themes, and the identified theme A conceptualization unit for extracting a plurality of term groups included in
A text search unit that searches the technical content database using the extracted term group as a keyword, evaluates the searched technical content using a predetermined evaluation method, and obtains a highly evaluated technical content; and
An information search system comprising: a content display unit that outputs display data for displaying the acquired technical content. A categorized text database for storing categorized text relating to technical information to which themes and terms based on the technical classification stored in the technical classification database are stored;
The conceptualizing unit collates the term given to the classified text stored in the classified text database with the morpheme and extracts the text with the matching term instead of the search processing of the technical classification database. The information retrieval system according to claim 1, wherein all themes included in the extracted text are extracted, and at least one theme is specified from the extracted themes based on the number of extracted texts. The conceptualization unit extracts a field to which the theme extracted from the technical classification database belongs, calculates an evaluation value of each of the extracted fields by a predetermined evaluation method, and when there are a plurality of fields having similar evaluation values The information search system according to claim 1 or 2, wherein a theme to which a field selected from the plurality of fields belongs is specified. The input character string acquisition unit acquires a sentence as the input character string,
The conceptualization unit performs morphological analysis on the input character string to extract morphemes, collates the technical classification terms stored in the technical classification database with the extracted morphemes, and includes all matching terms. The information retrieval system according to any one of claims 1 to 3, wherein a theme is extracted. The information retrieval system according to claim 1, wherein the conceptualization unit extracts all term groups included in the identified theme. When the terms of the technical classification have a hierarchical structure, the conceptualizing unit obtains all the terms belonging to the terms that match the input character string directly from the terms included in the identified theme or all the terms belonging to the lower order. The information search system according to any one of claims 1 to 4, wherein the information search system is extracted. To retrieve information, on a computer,
Get an input string that is a word or combination of words entered by a searcher,
From a plurality of viewpoints, a field indicating a range to which the technology is applied, a theme indicating a range of the technology belonging to the field, and a characteristic of the technology included in the technology range for each theme, stored in the technology classification database For the technical classification that defines the terms shown in association with each other, the term of the technical classification is collated with the input character string, all themes including the matching terms are extracted, and at least one theme is extracted from the extracted themes. Identify,
Extracting a plurality of terms included in the identified theme,
Perform a text search using the extracted term group as a keyword with respect to a technical content database storing content indicating technical information, evaluate the searched technical content by a predetermined evaluation method, and obtain a technical content with good evaluation. Acquired,
An information retrieval program for executing a process of outputting display data for displaying the acquired technical content. To retrieve information, the computer
A process of obtaining an input string that is a word or combination of words entered by a searcher;
From a plurality of viewpoints, a field indicating a range to which the technology is applied, a theme indicating a range of the technology belonging to the field, and a characteristic of the technology included in the technology range for each theme, stored in the technology classification database For the technical classification that defines the terms shown in association with each other, the term of the technical classification is collated with the input character string, all themes including the matching terms are extracted, and at least one theme is extracted from the extracted themes. Process to identify;
A process of extracting a plurality of term groups included in the identified theme;
A technical content database storing technical content indicating technical information is used to perform a text search using the extracted term group as a keyword, and the searched technical content is evaluated by a predetermined evaluation method. Process to get
A process for outputting display data for displaying the acquired technical content. An information search method comprising:

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