JP5516416B2 - Information search apparatus, information search method, and program - Google Patents

Description

  The present invention relates to an information search apparatus, an information search method, and a program for efficiently searching for content.

  Conventionally, there has been a problem that necessary content cannot be found when searching a content set such as FAQ, product information, and photo album. In order to solve this problem, a technique for displaying a narrowable keyword for each category classification in a content set has been proposed (see, for example, Patent Document 1 and Patent Document 2).

  Specifically, Patent Document 1 assigns a keyword as supplementary information to each acquired image, classifies the keyword, ranks the keyword for each classification, and assigns the keyword and the keyword based on the ranking. Disclosed is a technique for displaying a captured image. According to the technique of Patent Document 1, since the user can easily find the keyword to be obtained, it is considered that the problem that the necessary content cannot be found in the search is solved.

  Patent Document 2 discloses a technique for generating a classification keyword for classifying a content set composed of document sets into categories. In the technique described in Patent Literature 2, in a document set belonging to an arbitrary category N (referred to as “document set S”), a category suitability V is calculated for each word in the word set W included therein. . Specifically, the category matching level V is calculated by adding the number of appearance documents D of each word in the document set S and the number of appearance documents DF of each word in the document set SF of all categories to V = D / DF. Sought by.

  Thus, the category suitability V is obtained by dividing the number of contents in the category in which the word appears by the number of contents in all categories in which the word appears. Then, using the category suitability V, the category N category keyword is selected and the importance of the selected category keyword is calculated. Thereafter, using the obtained classification keyword, category classification is performed on the target content set. According to this category classification, it is considered that the user can easily find the necessary content.

JP, 2004-139401, A Information processing apparatus JP, 2003-99445, A Classification keyword generation method, classification keyword generation program, and recording medium which recorded the program

  By the way, in the technique disclosed in Patent Document 1, some keywords are used in a plurality of categories, and different classifications may be performed depending on the same keyword. In the technique disclosed in Patent Document 1, as described above, keywords are ranked for each category (classification). At this time, keywords appear only in one category and well represent the characteristics of the category. There is no distinction between keywords and general keywords that appear in multiple categories.

  For this reason, with the technique disclosed in Patent Document 1, it is difficult to specify keywords that frequently appear in one category, not keywords that appear uniformly in a plurality of categories, as keywords for narrowing down. That is, even if the technique disclosed in Patent Document 1 is used, it is difficult to completely solve the problem that a necessary content cannot be found in the search.

  In the technique disclosed in Patent Document 2, the category suitability V is obtained based on the number of contents of all categories in which words appear as described above, and the number of categories should be taken into consideration. It is sought after. Therefore, it is difficult to indicate how much this word appears in a plurality of categories or frequently appears in one category by the category suitability V.

  That is, even if the technique disclosed in Patent Document 2 is used, it is difficult to specify keywords that frequently appear in one category, as in the technique disclosed in Patent Document 1, and this case is also necessary for the search. It is difficult to completely eliminate the problem that the correct content cannot be found.

  An object of the present invention is to solve the above-mentioned problems, and when searching a content set classified into categories, an information search that can specify keywords that appear more frequently than other categories in a target category An apparatus, an information search method, and a storage medium storing a program are provided.

  In order to achieve the above object, an information search apparatus according to the present invention is an information search apparatus that searches a plurality of contents classified in a plurality of categories, and includes any of the plurality of contents and the plurality of contents. A plurality of keywords expressing such attributes and a content storage unit that stores the plurality of categories; and an input of a search keyword from the outside, and from the plurality of contents stored in the content storage unit, A keyword that expresses an attribute of the content searched by the search unit is extracted from the search unit that searches for content including the search keyword and the plurality of keywords stored in the content storage unit, and the extracted keyword A keyword survey section that investigates at least the category to which each belongs, and each category A keyword ranking unit for assigning a ranking to the extracted keywords, and the keyword ranking unit, for each of the extracted keywords, the number of categories to which each keyword belongs, The number of contents that each keyword represents an attribute is obtained, and the ranking is assigned based on the obtained number of categories and the number of contents.

  In order to achieve the above object, an information search method according to the present invention is an information search method for searching for a plurality of contents classified in a plurality of categories, wherein: (a) the plurality of contents; and A step of storing a plurality of keywords expressing attributes of any of a plurality of contents and the plurality of categories; and (b) receiving an input of a search keyword from the outside, and storing it in the step of (a). Searching the content including the search keyword from the plurality of contents; (c) from the plurality of keywords stored in the step (a) of the content searched in the step (b) Extracting a keyword expressing an attribute and investigating at least a category to which the extracted keyword belongs; ) From the result of the investigation in the step (c), for each of the extracted keywords, the number of categories to which each keyword belongs and the number of contents in which each keyword expresses an attribute are obtained. And assigning the ranking to the extracted keywords for each category based on the number of content and the number of content.

  Further, in order to achieve the above object, a program according to the present invention is a program for causing a computer to perform information search using a plurality of contents classified in a plurality of categories as a search target. Storing a plurality of contents, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories; (b) receiving an input of a search keyword from the outside; A step of searching for the content including the search keyword from the plurality of contents stored in the step; and (c) the step of (b) from the plurality of keywords stored in the step of (a). The keyword expressing the attribute of the content searched in is extracted, and the extracted keyword is And (d) the number of categories to which each keyword belongs and the content of the content that each keyword represents an attribute for each of the extracted keywords from the result of the investigation in step (c) And a step of assigning the ranking to the extracted keywords for each category based on the determined number of categories and the number of contents. .

  Due to the above characteristics, according to the information search apparatus, information search method, and storage medium storing the program of the present invention, when performing a search for a content set classified into categories, the other category is the target category. Keywords that appear more frequently than the category can be identified.

FIG. 1 is a block diagram showing a schematic configuration of an information search apparatus according to Embodiment 1 of the present invention. FIG. 2 is a block diagram showing a configuration of the information search apparatus according to Embodiment 1 of the present invention. FIG. 3 is a diagram illustrating an example of a content set to be searched. FIG. 4 is a diagram illustrating an example of a content set to be searched. FIG. 5 is a diagram showing an example of keyword extraction processing by the keyword extraction unit shown in FIG. FIG. 6 is a diagram illustrating an example of a search result of the keyword search unit illustrated in FIG. FIG. 7 is a diagram showing another example of keyword extraction processing by the keyword extraction unit shown in FIG. FIG. 8A is a diagram showing another example of the search result of the keyword search unit shown in FIG. FIG. 8B is a diagram showing another example of the search result of the keyword search unit shown in FIG. FIG. 9 is a diagram showing the number of contents and the number of categories obtained by the keyword ranking unit shown in FIG. FIG. 10A is a diagram showing rankings assigned to keywords for each category. FIG. 10B is a diagram illustrating rankings assigned to keywords for each category. FIG. 11 is a diagram illustrating an example of a display screen of a display device connected to the information search device illustrated in FIG. FIG. 12 is a flowchart showing an information search method according to Embodiment 1 of the present invention. FIG. 13 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 2 of the present invention. FIG. 14 is a diagram illustrating an example of the common keyword extracted by the common keyword extraction unit illustrated in FIG. FIG. 15 is a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG. FIG. 16 is a flowchart showing an information search method according to Embodiment 2 of the present invention. FIG. 17 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 3 of the present invention. FIG. 18A is a diagram illustrating an example of a common keyword in which duplicate keywords are specified. FIG. 18B is a diagram illustrating an example of a feature keyword in which duplicate keywords are specified. 19 is a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG. FIG. 20 is a flowchart showing processing in the keyword classification unit 35 shown in FIG. FIG. 21 is a flowchart showing processing performed by the keyword classification unit that constitutes the information search apparatus according to Embodiment 4 of the present invention. FIG. 22A is a diagram illustrating an example of a common keyword processed by the keyword classification unit. FIG. 22B is a diagram illustrating an example of a feature keyword processed by the keyword classification unit. FIG. 23 is a diagram showing an example of a display screen of a display device connected to the information search device in Embodiment 4 of the present invention. FIG. 24 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 5 of the present invention. 25A is a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG. FIG. 25B is also a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG.

(Embodiment 1)
Hereinafter, a storage medium storing an information search apparatus, an information search method, and a program according to Embodiment 1 of the present invention will be described with reference to FIGS. First, a schematic configuration of the information search apparatus according to the first embodiment will be described with reference to FIG.

  As shown in FIG. 1, the information search apparatus 1 according to the present embodiment uses a plurality of contents classified in a plurality of categories as search targets. The information search apparatus 1 includes a content storage unit 10, a search unit 20, a keyword survey unit 31, and a keyword ranking unit 32.

  The content storage unit 10 stores a plurality of contents, a plurality of keywords expressing attributes of any of the plurality of contents, and a plurality of categories. The search unit 20 receives an input of a search keyword from the outside, and searches the content including the search keyword from a plurality of contents stored in the content storage unit 10. The keyword survey unit 31 extracts keywords expressing the attributes of the content searched for by the search unit from a plurality of keywords stored in the content storage unit 10, and searches at least the category to which the extracted keyword belongs. The keyword ranking unit 31 gives a ranking to the extracted keywords for each category. Then, the keyword ranking unit 32 obtains, for each extracted keyword, the number of categories to which each keyword belongs and the number of contents for which each keyword expresses an attribute from the result of the survey by the keyword survey unit 31. Ranking is given based on the determined number of categories and content.

  In the information search apparatus 1 configured in this way, when searching for a content set classified into categories, keywords that appear more frequently than other categories in the target category can be specified.

  Hereinafter, this embodiment will be described in more detail. First, the configuration of the information search apparatus according to the first embodiment will be described with reference to FIGS. FIG. 2 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 1 of the present invention. 3 and 4 are diagrams illustrating an example of a content set to be searched.

  As described above, the information search device 1 according to the first embodiment of the present invention shown in FIG. 2 is a device that performs information search using a plurality of contents (content sets) classified in a plurality of categories as search targets. . As shown in FIG. 2, the information search device 1 according to the first embodiment includes a content storage unit 10, a search unit 20, and a feature keyword generation unit 30. In the first embodiment, as a content set to be searched, for example, a content set classified by a plurality of categories shown in FIG. 3 or a plurality of hierarchical categories shown in FIG. Content set.

  The content storage unit 10 stores a plurality of contents, a plurality of keywords, and a plurality of categories. Each of the plurality of keywords expresses any attribute of the plurality of contents. That is, each keyword corresponds to any content. The content storage unit 10 includes, for example, the content set shown in FIG. 3 or FIG. 4, the category classification of the content set (category classification and its hierarchical structure in the example of FIG. 4), and a set of keywords corresponding to each content. Is remembered.

  The search unit 20 receives an input of a search keyword from the outside, and searches the content including the search keyword from a plurality of contents stored in the content storage unit 10. In addition, the search unit 20 inputs the search result to the feature keyword generation unit 30. For example, when the content set shown in FIG. 3 is stored in the content storage unit 10, when “EPG” is input as a search keyword, the search unit 20 searches the content 10 and 11. Further, when the content set shown in FIG. 4 is stored in the content storage unit 10, when “DVD recorder” is input as a search keyword, the search unit 20 searches the content C <b> 1 to C <b> 6.

  The feature keyword generation unit 30 includes a keyword survey unit 31 and a keyword ranking unit 32. Among these, the keyword research part 31 extracts the keyword expressing the attribute of the content searched by the search part 20 from the plurality of keywords stored in the content storage part 10. Further, the keyword survey unit 31 surveys at least the category to which the extracted keyword belongs, and inputs the survey result to the keyword ranking unit 32.

  The keyword ranking unit 32 obtains, for each extracted keyword, the number of categories to which each keyword belongs and the number of contents for which each keyword expresses an attribute from the result of the survey by the keyword survey unit 31. Further, the keyword ranking unit 32 assigns rankings to the extracted keywords for each category based on the obtained number of categories and the number of contents.

  As described above, the information search apparatus 1 according to the first embodiment gives rankings to the extracted keywords for each category. This ranking is given so that each keyword appears higher in the category where ranking is given, so that it frequently appears in that category. Therefore, according to the information search device 1, it is possible to specify a keyword that appears more frequently in a target category than other categories from among a plurality of contents (target content sets) searched by the search unit 20. .

  Further, the specified keyword, that is, the keyword having the above ranking, is a keyword that can be narrowed down for each category. Therefore, the user can easily find the desired content by performing a search using this keyword. Furthermore, since this keyword represents the characteristics of each category, the user can grasp what kind of content is included in the category simply by looking at this keyword. The search is also made easier.

  Here, the information search device 1 according to the first embodiment will be specifically described with reference to FIGS. FIG. 5 is a diagram showing an example of keyword extraction processing by the keyword extraction unit shown in FIG. FIG. 6 is a diagram illustrating an example of a search result of the keyword search unit illustrated in FIG. FIG. 7 is a diagram showing another example of keyword extraction processing by the keyword extraction unit shown in FIG. 8A and 8B are diagrams illustrating another example of the search result of the keyword search unit illustrated in FIG.

  FIG. 9 is a diagram showing the number of contents and the number of categories obtained by the keyword ranking unit shown in FIG. FIG. 10 is a diagram showing rankings assigned to keywords for each category, and FIGS. 10A and 10B show different categories. FIG. 11 is a diagram illustrating an example of a display screen of a display device connected to the information search device illustrated in FIG.

  In the first embodiment, as shown in FIG. 2, the information search device 1 further includes a keyword extraction unit 40. The keyword extraction unit 40 is connected to the database 70, and the search unit 20 is connected to the input device 50 and the display device 60. Note that the keyword ranking unit 32 is also connected to the display device 60.

  The database 70 is a database in which a plurality of contents (content sets) to be searched are stored in a state of being classified into a plurality of categories. Examples of content sets stored in the database 70 include FAQs, product catalogs, and various document sets. Examples of the various document sets include a set of documents created inside the company and a large amount of e-mail managed by e-mail software. Other content sets include an image set managed by photo management software, a music data set managed by music management software, and the like.

  Specifically, the content set shown in FIG. 3 or 4 is stored in the database. Further, at this time, the content set may adopt a one-level category classification as shown in FIG. 3, or may adopt a multi-level category classification as shown in FIG.

  The keyword extraction unit 40 extracts keywords that need to be stored in the content storage unit 10 from the external database 70 and stores the extracted keywords in the content storage unit 10. The keyword that needs to be stored is a keyword that expresses the attributes of each of the plurality of contents and belongs to one of a plurality of categories.

  The keyword extraction unit 40 also stores, in the content storage unit 10, a plurality of contents themselves and a plurality of categories (category classifications) originally stored in the database 70, in addition to the keywords expressing the content attributes. When the category classifications stored in the database 70 are hierarchized as shown in FIG. 4, the keyword extraction unit 40 stores the hierarchized category classification (category classification and hierarchical structure of category classifications) as content. Store in the storage unit 10. In the first embodiment, the storage of information in the content storage unit 10 is performed by the keyword extraction unit 40, but can be performed manually by the user.

  Further, the keyword extraction method executed by the keyword extraction unit 40 is not particularly limited. For example, a method of extracting a word from content to obtain a keyword, or a hierarchy and category stored in the data base 70 There are methods that use classification.

  In the former case, for each content stored in the database 70, the keyword extraction unit 40 divides a sentence included in each content into words, and each word obtained by the division represents a keyword representing an attribute of each content. Can be extracted as For example, as shown in FIG. 5, if the content 20 includes “Can you dubb from HDD to DVD?”, The keyword extraction unit 40 divides this sentence into words and is prepared in advance. Extract only nouns using part of speech information. Specifically, the keyword extraction unit 40 extracts “HDD”, “DVD”, and “dubbing” from the content 20 as keywords.

  Similarly, the keyword extraction unit 40 extracts “disc” and “backup” as keywords from “Can you back up to disc?” Included in the content 21. Furthermore, the keyword extraction unit 40 extracts “HDD”, “DVD”, and “recording” from “Can you record to HDD and DVD?” Of the content 22, and “How long is the DVD recording time of the content 23? “DVD” and “recording time” are extracted from “??”. The keyword extraction unit 40 can also extract verbs and the like other than nouns, and FIG. 5 shows an example only. Further, the process shown in FIG. 5 is effective as long as each content is associated with one of the categories, even if the category classification layer is one layer or two or more layers.

  In the latter case, the keyword extracting unit 40 obtains the lowest category to which each content is directly associated from the content set having a hierarchical structure stored in the database 70, and expresses these attributes of the content. Can be extracted as a keyword. Specifically, in the case of a content set having a hierarchical structure shown in FIG. 4, the lowermost component category is extracted as a keyword.

  In this case, as shown in FIG. 4, the keyword “HDD” is extracted for the content C1, and the keyword “tuner” is extracted for the content C2. For the content C3, the keyword “HDD” and the keyword “DVD-R” are extracted. Further, the keyword “DVD-R” is extracted for the content C4, the keyword “tuner” is extracted for the content C5, and the keyword “HDD” is extracted for the content C6. Then, as illustrated in FIG. 7, the keyword extraction unit 40 stores the extracted keywords in the content storage unit 10 in a state in which the extracted keywords are associated with the contents C1 to C6.

  The input device 50 is a device used by a user to input a search keyword for searching for content. Specifically, the input device 50 is realized by an input device such as a keyboard or a mouse. In the first embodiment, the search keyword can be input by the user freely inputting text data from the keyboard. The search keyword can also be input by the user selecting a search keyword using a mouse from search keyword candidates such as categories and keywords displayed on the display screen of the display device 60.

  The display device 60 is a device for displaying information on a display screen. Specifically, the display device 60 is realized by a display device having a display screen such as a liquid crystal display device or a printing device for printing information on a medium. it can. In the first embodiment, a display device is used as the display device 60. On the display screen of the display device 60, for example, keywords ranked by the keyword ranking unit 32, content searched by the search unit 20, and the like are displayed.

  In the first embodiment, the search unit 20 accepts input of a search keyword or searches for content including the search keyword, and then inputs a search result to the display device 60, and the searched content is displayed on the display device 60. On the display screen. Thereby, the convenience for the user is improved. Further, the search unit 20 also inputs the search result to the common keyword generation unit 30.

  In the present embodiment, the keyword research unit 31 stores the category classification of the content set (or the category classification and the hierarchical structure of the category classification) stored in the content storage unit 10 and the keyword corresponding to each content. Consider. Then, the keyword survey unit 31 extracts keywords expressing the attributes of each searched content by this consideration, and at this time, it investigates which category the extracted keyword relates to. Further, the keyword survey unit 31 inputs the survey result to the keyword ranking unit 32.

  For example, the case where the content set (contents 20, 21, 22, and 23) shown in FIG. In the contents 20 to 23 shown in FIG. 3, as shown in FIG. 5, “HDD”, “DVD”, “dubbing”, “disc”, “recording”, “recording time”, and “backup” are used as keywords expressing attributes. Existing. Therefore, the keyword research unit 31 extracts these keywords.

  Then, the keyword survey unit 31 considers the relationship between the category and the content shown in FIG. 3, investigates the category related to the extracted keyword (see FIG. 5), and creates the survey result shown in FIG. . As shown in FIG. 6, the keywords “HDD” and “DVD” relate to the categories “dubbing function” and “recording function”. The keywords “dubbing”, “disc”, and “backup” are related to the category “dubbing function”, and the keywords “recording” and “recording function” are related to the category “recording function”. The keyword survey unit 31 creates a survey result indicating these relationships, and inputs this into the keyword ranking unit 32.

  As another example, let us consider a case in which the content set shown in FIG. 4 is stored by the content storage unit 10, “DVD recorder” is input as a search keyword, and the contents C 1 to C 6 are searched. In this case, the keyword research unit 31 uses the relationship between the content and the keyword shown in FIG. 7 stored in the content storage unit 10 as keywords included in the contents C1 to C6 as “HDD” and “tuner”. And “DVD-R” are extracted.

  Further, the keyword search unit 31 refers to the category classification stored in the content storage unit 10 and the hierarchical structure of the category classification (see FIG. 4), and extracts the extracted “HDD”, “tuner”, and “DVD-R”. Is related to which category of which hierarchy. In the example of FIG. 4, in this case, the category of the fourth hierarchy, which is the lowest layer, is a keyword. Therefore, the keyword survey unit 31 creates a survey result using the category of the third hierarchy or the category of the second hierarchy.

  Specifically, as shown in FIG. 8A, for the third layer, “HDD” is “recording” “EPG” “dubbing”, “tuner” is category “EPG” “dubbing”, and the keyword “DVD- A survey result indicating that “R” relates to “dubbing” is created. As for the second layer, as shown in FIG. 8B, “HDD” is “model α” “model β”, “tuner” is “model β”, and “DVD-R” is “model β”. A survey result showing that it is related is created. Also in this case, the keyword survey unit 31 inputs the survey result to the keyword ranking unit 32.

  In the first embodiment, for example, as shown in FIG. 9, the keyword ranking unit 32 determines the number of categories to which each keyword belongs and the attribute of each keyword for each keyword extracted by the keyword survey unit 31. Find the number of content to be expressed. In FIG. 9, a column 60 indicates a keyword, a column 61 indicates the number of categories (the number of categories), and a column 62 indicates the number of contents (the number of contents). In the example of FIG. 9, keywords “HDD”, “DVD”, “dubbing”, and the like included in the target content set are extracted.

  Then, for example, the keyword ranking unit 32 obtains the number of contents that each keyword expresses an attribute for all categories from the relationship between the keyword and the content shown in FIG. In the example of FIG. 9, the keyword ranking unit 32 associates, for each keyword, the number of contents associated with category A (dubbing function), the number of contents associated with category B (recording function), and category C (playback function). Find the number of content received.

  Specifically, in category A (dubbing function), the keyword “HDD” is associated with 20 contents, the keyword “DVD” is associated with 20 contents, and the keyword “dubbing” is 25 pieces. Associated with content. In category B (recording function), the keyword “HDD” is associated with 30 contents, and the keyword “DVD” is associated with one content. On the other hand, the keyword “dubbing” is not associated with any content in category B (recording function), and the number of content is “0”.

  Further, the keyword ranking unit 32 can obtain the number of categories to which each keyword belongs based on the survey result created by the keyword survey unit 31 (see FIG. 6). In the example of FIG. 9, the number of categories to which the keyword “HDD” belongs is 10 and the number of categories to which the keyword “DVD” belongs is 2.

  Further, when the target content set is classified into a plurality of hierarchized categories as shown in FIG. 4, the hierarchy used when the keyword ranking unit 32 obtains the number of categories is particularly limited. Is not to be done. The hierarchy used in this case may be set in advance or may be set by the user. Moreover, the hierarchy to be used may be set according to a preset rule.

  For example, when the category shown in FIG. 4 is displayed as a selection menu, and the user selects one of the categories from the selection menu, the keyword ranking unit 32 uses the hierarchy one level below the selected hierarchy, It can be set as the aspect which calculates | requires the number of categories. According to this aspect, since the ranking is performed based on the category selected by the user, the user can easily grasp what content is included in the category selected by the user. For this reason, the user can easily determine which category should be selected next.

  Specifically, for example, in FIG. 4, when the user selects “DVD recorder” as a search keyword, first, the search unit 20 searches the contents C1 to C6. Then, the keyword survey unit 31 extracts keywords that express the attributes of the contents C1 to C6, and then investigates the category to which the extracted keyword belongs. At this time, the second hierarchy immediately below the selected category. Will be investigated. Then, the keyword ranking unit 32 obtains the number of categories to which each keyword belongs for the category of the second hierarchy such as “model α” and “model β”. When “model α” is selected, the number of categories to which each keyword belongs is obtained for the category of the third hierarchy.

  In the first embodiment, the keyword ranking unit 32 is obtained by dividing the number of contents by the number of categories or the value calculated from the number of categories, as shown in FIGS. 10A and 10B. Ranking is given based on the division value.

  Specifically, when the value obtained by division is “importance”, the number of contents is Y, and the number of categories is X, the importance can be obtained by importance = Y / (logX + 1). The importance can also be obtained by directly dividing the number of contents by the number of categories (Y / X). However, when “logX + 1” is used, the influence of the variation in the number of categories X on the importance can be reduced, and the variation in the importance can be prevented from becoming too large.

  For example, as shown in FIG. 10A, in category A, the importance of the keyword “HDD” is “10” from 20 / (log10 + 1) because the number of contents is 20 and the number of categories is 10. Similarly, the importance of the keyword “DVD” is 20 / (log2 + 1) = 15.37 because the number of contents is 20 and the number of categories is 2. Further, the importance of the keyword “dubbing” is 25 / (log1 + 1) = 25 because the number of contents is 25 and the number of categories is 1. In the category B shown in FIG. 10B, the importance is similarly obtained.

  Furthermore, in the first embodiment, as shown in FIG. 11, the keyword ranking unit 32 sets, as characteristic keywords, keywords that have been given rankings among ranking keywords. Set and generate a ranking table with the set feature keywords.

  For example, in category A shown in FIG. 10A, the keyword ranking is 1st place “dubbing”, 2nd place “DVD”, 3rd place “disc”, 4th place “HDD”, 5th place “backup”, 6th place “VTR”. It becomes. And the keyword ranking part 32 sets the 1st to 4th among these as characteristic keywords, and produces | generates a ranking table | surface by these (refer FIG. 11). Further, as shown in FIG. 10B, the keyword ranking unit 32 also assigns a ranking to each keyword in the category B, and further sets the keyword as a feature keyword.

  Further, the keyword ranking unit 32 sends the generated ranking table to the display device 60, and displays the ranking table on the display screen as shown in FIG. In the example of FIG. 11, the feature keyword and the content (for example, FAQ) searched by the search unit 20 are also displayed together with the ranking table. The keyword ranking unit 32 can display the feature keywords by switching the display screen or scrolling the display screen when the number of feature keywords is large and cannot be displayed on the display screen at one time.

  Next, the information search method in Embodiment 1 of this invention is demonstrated using FIG. FIG. 12 is a flowchart showing an information search method according to Embodiment 1 of the present invention. The information retrieval method according to the first embodiment is implemented by operating the information retrieval apparatus 1 according to the first embodiment shown in FIG. For this reason, the information search method according to the first embodiment will be described together with the operation of the information search apparatus 1 shown in FIG. 2 with appropriate reference to FIGS.

  As shown in FIG. 12, first, the keyword extraction unit 40 extracts a keyword that expresses the attribute of each content (corresponding to each content) from the content set stored in the database 70, and extracts this from the content storage unit. 10 (step S201).

  Next, the keyword extraction unit 40 extracts a plurality of contents themselves and a plurality of categories (only category classification or a hierarchical structure of category classification and category classification) originally stored in the database 70, and these are also contents. It memorize | stores in the memory | storage part 10 (step S202).

  Next, the search unit 20 searches the content including the search keyword input by the user via the input device 50 from the plurality of contents stored in the content storage unit 10, and displays the search result on the display device 60. It is displayed (step S203). In step S203, the search result is presented to the user. Further, the search unit 20 inputs the content set (target content set) searched in step S203 to the keyword research unit 31 (step S204).

  Specifically, for example, when the user inputs “DVD recorder” as a search keyword in the example shown in FIG. 4, in step S203, the search unit 20 searches the content C1 from the content C1. In step S <b> 204, the search unit 20 inputs information specifying the contents C <b> 1 to C <b> 6 to the keyword survey unit 31.

  Next, the keyword search unit 31 extracts keywords expressing the attributes of the content searched in step S204 from the plurality of keywords stored in the content storage unit 10, and further checks the category to which the extracted keyword belongs. (Step S205). In step S205, the keyword research unit 31 refers to the relationship between the category and the content shown in FIG. 3, for example. Further, the keyword research unit 31 creates a survey result (see FIG. 6). The keyword survey unit 31 inputs the extracted keyword and the survey result to the keyword ranking unit 32.

  Next, for each keyword extracted by the keyword research unit 31, the keyword ranking unit 32 includes the number of categories to which each keyword belongs (see the column 61 shown in FIG. 7) and the content of the content in which each keyword represents an attribute. The number is obtained (step S206).

  When step S206 ends, the keyword ranking unit 32 uses the results of these steps to determine the importance for each keyword in each category and assigns a ranking (step S207). In step S207, as shown in FIG. 11, the keyword ranking unit 32 sets a keyword to which a preset ranking is assigned as a feature keyword, and generates a ranking table using the set feature keyword.

  Next, the keyword ranking unit 32 sends the generated ranking table to the display device 60, and displays the ranking table on the display screen as shown in FIG. 11 (step S208). In step S208, as shown in FIG. 11, the keyword ranking unit 32 causes the display device 60 to display the content searched by the search unit 20 in addition to the ranking table based on the characteristic keywords. Furthermore, in the first embodiment, the feature keyword and content displayed on the display screen can be selected by the user using the input device 50.

  Next, after executing step S208, the search unit 20 determines whether one of the feature keywords displayed on the display screen of the display device 60 has been selected (step S209). If one of the feature keywords is selected as a result of the determination in step S209, the search unit 20 accepts the input using the selected feature keyword as a search keyword. And the search part 20 searches the content corresponding to the characteristic keyword which received the input from the some content memorize | stored in the content memory | storage part 10 (step S211). After executing step S211, the search unit 20 executes step S204 again.

  On the other hand, if one of the characteristic keywords is not selected as a result of the determination in step S209, the search unit 20 determines whether an instruction to end the process is given (step S210). If the end of the process is not instructed as a result of the determination in step S210, the search unit 20 executes step S203 again. On the other hand, if the end of the process is instructed as a result of the determination in step S210, the process in the information search apparatus 1 ends.

  As described above, in the first embodiment, after the ranking table based on the feature keyword is generated, a new process is performed using the feature keyword as a search keyword. Each time such processing is repeated, the possibility that the feature keyword can search for the content desired by the user is increased.

  Also, when the information search method according to the first embodiment is performed, keywords that can be narrowed down for each category are specified as in the case where the information search apparatus 1 according to the first embodiment is operated. Therefore, the user can easily find the desired content by performing a search using this keyword. Furthermore, since this keyword represents the characteristics of each category, the user can grasp what kind of content is included in the category simply by looking at this keyword. The search is also made easier.

  In the information search method according to the first embodiment, among the steps described above, steps S201 and S202 do not have to be performed continuously with other steps, and are executed anytime before the execution of other steps. it can.

  The storage medium storing the program in the first embodiment may be a storage medium storing a program that causes a computer to execute steps S201 to S211 shown in FIG. Moreover, if the program in this Embodiment 1 is installed in a computer and this is run, the information processing apparatus 1 in this Embodiment 1 will be implement | achieved.

  In this case, a central processing unit (CPU) of the computer functions as the search unit 20, the keyword search unit 31, the keyword ranking unit 32, and the keyword extraction unit 40, and performs processing. A storage device such as a hard disk or a memory device provided in the computer functions as the content storage unit 10.

(Embodiment 2)
Next, an information search device, an information search method, and a storage medium storing a program according to Embodiment 2 of the present invention will be described with reference to FIGS. First, a schematic configuration of the information search apparatus according to the second embodiment will be described with reference to FIGS.

  FIG. 13 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 2 of the present invention. FIG. 14 is a diagram illustrating an example of the common keyword extracted by the common keyword extraction unit illustrated in FIG. FIG. 15 is a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG.

  As shown in FIG. 12, the information processing apparatus 2 according to the second embodiment includes a common keyword extraction unit 33 and a common keyword ranking unit 34. In this regard, the information processing apparatus 1 according to the first embodiment. (See FIG. 2). The information processing apparatus 2 in the second embodiment is configured in the same manner as the information processing apparatus 1 in the first embodiment except that the common keyword extraction unit 33 and the common keyword ranking unit 34 are provided. ing. In addition, in FIG. 12, the same reference numerals as those used in FIG. 2 are given to components common between the first embodiment and the second embodiment. Hereinafter, differences will be described.

  In the second embodiment, the feature keyword generation unit 30 further includes a common keyword extraction unit 33 and a common keyword ranking unit 34 in addition to the keyword survey unit 31 and the keyword ranking unit 32. In addition, when the category classification is hierarchized, the keyword research unit 31 can also investigate which category of which hierarchy the keyword belongs to.

  The common keyword extraction unit 33 extracts keywords belonging to a plurality of categories in the same hierarchy as the common keywords from the keywords extracted by the keyword search unit 31 based on the result of the search by the keyword search unit 31 ( (See FIG. 14). In addition, the common keyword extraction unit 33 inputs the extracted common keyword to the common keyword ranking unit 34.

  For example, when the result of the keyword search unit 31 is the example shown in FIG. 6, the common keyword extraction unit 33 uses the keywords “HDD” and “DVD” as belonging to a plurality of categories. Extract.

  Further, when the search result of the keyword search unit 31 is the example shown in FIG. 8A, the common keyword extraction unit 33 uses the keywords “HDD” and “tuner” to belong to a plurality of categories. Extract as Furthermore, when the result of the keyword search unit 31 is the example shown in FIG. 8B, the common keyword extraction unit 33 extracts only the keyword “HDD” as a common keyword because it belongs to a plurality of categories.

  When a plurality of common keywords are extracted by the common keyword extraction unit 33, the common keyword ranking unit 34 assigns a ranking to each of the extracted plurality of common keywords according to the degree of commonality. Here, “giving a ranking according to the degree of commonality” means that a common keyword linked to more categories has higher ranking.

  For example, if the content set to be searched is classified by a plurality of hierarchized categories, the common keyword ranking unit 34 displays a hierarchy of a plurality of categories to which the common keyword belongs for each of the plurality of common keywords. Ask. And the common keyword ranking part 34 can provide a ranking according to the calculated | required hierarchy.

  Specifically, the common keyword ranking unit 34 determines that a keyword that is duplicated in a shallow category (upper layer) has a higher importance (ranking) than a keyword that is duplicated in a deep category (lower layer). Can be determined. 8A and 8B, as shown in FIGS. 8A and 8B, the common keyword “HDD” is duplicated in the second and third hierarchies. On the other hand, the common keyword “tuner” is duplicated only in the third hierarchy.

  In this case, the importance of the common keyword “HDD” is set higher than the importance of the common keyword “tuner”, and the ranking of “HDD” is set higher than the ranking of “tuner”.

  The common keyword ranking unit 34 can also determine the importance (ranking) of the common keyword according to the number of categories to which the common keyword belongs. Specifically, the common keyword ranking unit 34 can determine that a keyword having a large number of overlapping categories is higher in importance than a keyword having a small number of overlapping categories.

  As shown in FIGS. 8A and 8B, a case where the common keyword extraction unit 33 extracts “HDD” and “tuner” as common keywords will be described. As shown in FIG. 8A, the common keyword “HDD” belongs to the third hierarchy and belongs to three categories of “recording”, “EPG”, and “dubbing”. On the other hand, the common keyword “tuner” belongs to two categories of “EPG” and “dubbing” in the third layer. In this case, the common keyword ranking unit 33 sets the importance of the common keyword “HDD” to be higher than the importance of the common keyword “tuner”.

  Further, the common keyword ranking unit 34 obtains the number of corresponding contents for each common keyword based on the plurality of contents and the plurality of keywords stored in the content storage unit 10, and ranks according to the number of contents. Can also be given. For example, the common keyword ranking unit 34 determines that a common keyword having a large number of extracted contents has higher importance (ranking) than a common keyword having a small number of extracted contents.

  An example in which the content set shown in FIG. 4 is a search target and the user inputs “DVD recorder” as a search keyword will be described. In this case, the search unit 20 searches the contents C1 to C6 shown in FIG. The keyword research unit 31 uses the relationship between the content and the keyword shown in FIG. 7 stored in the content storage unit 10, and uses the keywords “HDD”, “tuner”, and “DVD-” included in the content C1 to C6. R "is extracted.

  Then, the common keyword ranking unit 34 refers to the relationship between the content and the keyword shown in FIG. 7 stored in the content storage unit 10 and extracts “HDD”, “tuner”, and “DVD-R”, respectively. Calculate the number of contents. Specifically, in this case, the common keyword “HDD” corresponds to three cases of contents “C1”, “C3”, and “C6”, and the common keyword “tuner” includes two cases of contents “C2” and “C5”. Correspond. Therefore, the common keyword ranking unit 34 determines that the importance level of “HDD” is higher than the importance level of the common keyword “tuner”.

  The common keyword ranking unit 34 can also give a ranking to the common keywords based on the number of times the search keyword is input. Specifically, the common keyword ranking unit 34 determines whether or not each of the plurality of common keywords matches a past search keyword (see FIG. 15). Is calculated (number of inputs).

  Then, the common keyword ranking unit 34 determines the ranking of each common keyword based on the obtained number of inputs. For example, the common keyword ranking unit 34 determines that a common keyword that is frequently input as a search keyword is higher in importance than a keyword that is input as a search keyword.

  The common keyword ranking unit 34 inputs a plurality of common keywords to which rankings are given (ranked) to the display device 60, and displays them on the display screen together with the ranking as shown in a column 181 in FIG. Note that a column 182 in FIG. 15 indicates characteristic keywords displayed on the display screen. The characteristic keyword is set in the same manner as that in the first embodiment.

  Further, the common keyword ranking unit 34 can determine whether or not the common keyword is also displayed as a feature keyword (whether or not it is duplicated) when the common keyword is displayed on the display device 60. Further, if there is an overlap as a result of the determination, the common keyword ranking unit 34 displays the feature keyword in a state where the display mode of the overlapping feature keyword is different from the display mode of other feature keywords. Can be displayed.

  Specifically, the common keyword ranking unit 34 can perform display by changing the color of the overlapping feature keyword and the surrounding color from those of other feature keywords. In the example of FIG. 15, “HDD” appearing in both category A (dubbing function) and category B (recording function) is also extracted as a common keyword. Therefore, the common keyword ranking unit 34 makes the color of “HDD” different from the color of other characteristic keywords. A keyword spanning a plurality of categories can be searched at once by selecting from a common keyword rather than searching from a feature keyword displayed for each category. In this case, the user is likely to notice the common keyword whose display color has been changed, and is considered to use it.

  Next, the information search method in Embodiment 2 of this invention is demonstrated using FIG. FIG. 16 is a flowchart showing an information search method according to Embodiment 2 of the present invention. The information search method according to the second embodiment is performed by operating the information search device 2 according to the first embodiment shown in FIG. For this reason, the information search method according to the second embodiment will be described together with the operation of the information search apparatus 1 shown in FIG. 13 with appropriate reference to FIGS.

  As shown in FIG. 16, first, steps S201 to S207 are executed to set feature keywords. Steps S201 to S207 are the same as steps S201 to S207 shown in FIG. 12 in the first embodiment.

  Next, the common keyword extraction unit 33 extracts keywords belonging to a plurality of categories as common keywords from the survey results by the keyword survey unit 31 (step S212). Subsequently, the common keyword ranking unit 33 assigns rankings to a plurality of common keywords (step S213).

  Next, after the execution of step S213, the keyword ranking unit 32 displays the characteristic keywords (ranking table) on the display screen, and the common keyword extraction unit 33 displays the common keywords on the display screen (step S214). In the second embodiment, in addition to the common keyword displayed on the display screen, the feature keyword can be selected by the user using the input device 50.

  Next, after executing step S214, the search unit 20 determines whether one of the feature keyword or the common keyword displayed on the display screen of the display device 60 is selected (step S215). Step S215 is the same as step S209 shown in FIG. 12 in the first embodiment.

  As a result of the determination in step S215, when one of the feature keyword or the common keyword is selected, the search unit 20 receives the input using the selected feature keyword or common keyword as the search keyword. Then, the search unit 20 searches the content corresponding to the feature keyword or the common keyword for which the input has been received from the plurality of contents stored in the content storage unit 10 (step S217). After executing step S217, the search unit 20 executes step S204 again.

  On the other hand, as a result of the determination in step S215, if one of the feature keyword or the common keyword is not selected, the search unit 20 determines whether an instruction to end the process is given (step S216). If the end of the process is not instructed as a result of the determination in step S216, the search unit 20 executes step S203 again. On the other hand, if the end of the process is instructed as a result of the determination in step S216, the process in the information search device 1 ends.

  Step S216 is the same as S210 shown in FIG. 12 in the first embodiment. Also in the second embodiment, steps S201 and S202 do not have to be performed continuously with other steps, and can be performed at any time before the execution of other steps.

  As described above, in the second embodiment, two types of keywords, that is, a common keyword appearing redundantly in a plurality of categories and a feature keyword indicating characteristics for each category are extracted and displayed to the user. For this reason, users can use common keywords when they want to search for content based on a general concept, and can use feature keywords when they want to search for content with typical content in each category, and narrow down the content according to the purpose. be able to.

  The common keyword is particularly effective when a plurality of categories are hierarchized, and the user has to go back up the hierarchy many times due to the category selection or wrong category selection. The common keyword can reduce the labor of the user.

  In the second embodiment, after the feature keyword and the common keyword are generated, a new process is performed using the selected feature keyword or the common keyword as a search keyword. Also in the second embodiment, the possibility of searching for the content desired by the user is increased by repeating the processing.

  The storage medium storing the program in the second embodiment may be any storage medium storing a program that causes a computer to execute steps S201 to S207 and S212 to S217 shown in FIG. Further, if the program according to the second embodiment is installed in a computer and executed, the information processing apparatus 1 according to the second embodiment is realized.

  In this case, the CPU (central processing unit) of the computer functions as the search unit 20, the keyword survey unit 31, the keyword ranking unit 32, the common keyword extraction unit 33, the common keyword ranking unit 33, and the keyword extraction unit 40, and performs processing. . A storage device such as a hard disk or a memory device provided in the computer functions as the content storage unit 10.

(Embodiment 3)
Next, an information search device, an information search method, and a storage medium storing a program according to Embodiment 3 of the present invention will be described with reference to FIGS. FIG. 17 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 3 of the present invention. FIG. 18A is a diagram illustrating an example of a common keyword in which duplicate keywords are identified, and FIG. 18B is a diagram illustrating an example of a feature keyword in which duplicate keywords are identified. 19 is a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG. FIG. 20 is a flowchart showing processing in the keyword classification unit 35 shown in FIG.

  As shown in FIG. 17, the information processing apparatus 3 according to the third embodiment includes a keyword classification unit 35, and this is different from the information processing apparatus according to the second embodiment (see FIG. 13). The information processing device 3 in the third embodiment is configured in the same manner as the information processing device 2 in the second embodiment except that the keyword classification unit 35 is provided. In addition, in FIG. 17, the same reference numerals as those used in FIG. 12 are given to components common between the second embodiment and the third embodiment. Hereinafter, differences will be described.

  In the third embodiment, the feature keyword generation unit 30 further includes a keyword classification unit 35 in addition to the keyword survey unit 31, the keyword ranking unit 32, the common keyword extraction unit 33, and the common keyword ranking unit 34. ing.

  The keyword classification unit 35 compares the feature keyword set by the keyword ranking unit 32 with the common keyword extracted by the common keyword extraction unit 33, and identifies a keyword that overlaps both as a duplicate keyword. In practice, the keyword classification unit 35 compares the output from the keyword ranking unit 32 with the output from the common keyword ranking unit 34.

  Further, in the third embodiment, the keyword classification unit 35 regards duplicate keywords as common keywords, and can delete keywords corresponding to the duplicate keywords from the feature keyword ranking table.

  For example, it is assumed that the common keyword ranking unit 34 outputs the ranking result shown in FIG. 18A and the keyword ranking unit 33 outputs the ranking result shown in FIG. 18B for category A and category B. In this case, when comparing the common keyword and the feature keyword of category A, the three keywords “HDD”, “DVD”, and “VTR” are duplicated. Further, when comparing the common keyword with the feature keyword of category B, the five keywords “HDD”, “DVD”, “VTR”, “recording”, and “recording time” overlap.

  Accordingly, the keyword classification unit 35 uses “HDD”, “DVD”, “VTR”, “recording”, and “recording time” as duplicate keywords as common keywords, and from the category A characteristic keywords, “HDD”, “DVD” And “VTR” are deleted. Further, the keyword classification unit 35 deletes “HDD”, “DVD”, “VTR”, “recording”, and “recording time” from the feature keyword of category B.

  Moreover, the keyword classification | category part 35 displays the ranking table of a characteristic keyword on the display screen of the display apparatus 60 in the state by which the duplicate keyword was deleted, as shown in FIG. As described above, the third embodiment differs from the second embodiment (see FIG. 15) in which keywords such as “HDD”, “DVD”, and “recording” are displayed in duplicate, and common keywords and features. The keyword that overlaps with the keyword is not displayed.

  For this reason, according to the third embodiment, two types of keywords, that is, a common keyword appearing redundantly in a plurality of categories and a characteristic keyword indicating a feature for each category are displayed without overlapping. As a result, the occurrence of a situation where the user is confused by which keyword should be selected is suppressed. Users can use common keywords when searching for content with a general concept, and can use feature keywords when searching for content with typical contents in each category, and can narrow down the content according to the purpose. .

  In the third embodiment, instead of deleting duplicate feature keywords, the keyword classification unit 35 displays the feature keywords on the display screen in a state where the display mode is different from the display mode of other feature keywords. Can be displayed. Specifically, the keyword classifying unit 35 can perform display by changing the color of the overlapping feature keyword and the surrounding color thereof from those of other feature keywords. Moreover, the keyword classification | category part 35 can also delete a duplicate keyword in a common keyword, or can change a display mode.

  Further, the information search method in the third embodiment is executed according to the flowchart shown in FIG. 16, similarly to the information search method in the second embodiment. However, in the third embodiment, since the display is performed by the keyword classification unit 35, step S214 in FIG. 16 is executed by the keyword classification unit 35. Specifically, the process shown in FIG. 20 is performed as step S214. The other steps are executed as in the second embodiment.

  Here, the process shown in FIG. 20 will be described. As shown in FIG. 20, first, the keyword classification unit 35 compares the output from the keyword ranking unit 32 with the output from the common keyword ranking unit 34, and identifies duplicate keywords (step S2101).

  Next, the keyword classification unit 35 regards the duplicate keyword as a common keyword, identifies the feature keyword corresponding to the duplicate keyword from the feature keyword ranking table (step S2102), and deletes the identified keyword (S2103).

  After that, the keyword classification unit 35 directs the common keyword extracted in step S212 shown in FIG. 16 and given the ranking in step S212 and the feature keyword from which the duplicate keyword is deleted in step S2103 to the display device 60. Output (S2104). Thereby, the result shown in FIG. 19 is displayed on the display screen of the display device 60.

  The storage medium storing the program according to the third embodiment stores a program for causing the computer to execute steps S201 to S207, S212 to S217 shown in FIG. 16, and steps S2101 to S2104 shown in FIG. Any storage medium may be used. In the third embodiment, a central processing unit (CPU) of a computer is different from the second embodiment and further functions as a keyword classification unit 35 to perform processing.

(Embodiment 4)
Next, an information search device, an information search method, and a storage medium storing a program according to Embodiment 4 of the present invention will be described with reference to FIGS. FIG. 21 is a diagram showing a process performed by the keyword classification unit that constitutes the information search apparatus according to Embodiment 4 of the present invention. FIG. 22A shows an example of a common keyword processed by the keyword classifying unit, and FIG. 22B shows an example of a feature keyword processed by the keyword classifying unit. FIG. 23 is a diagram showing an example of a display screen of a display device connected to the information search device in Embodiment 4 of the present invention.

  The information processing apparatus according to the fourth embodiment is different from the information processing apparatus 3 according to the third embodiment (see FIG. 17) in terms of processing in the keyword classification unit. In other respects, the information processing apparatus in the fourth embodiment is configured in the same manner as the information processing apparatus 3 in the third embodiment. The block diagram of the information processing apparatus in the fourth embodiment is also the same as the block diagram shown in FIG. 17 used in the third embodiment.

  Further, the information search method according to the fourth embodiment is also executed according to the flowchart shown in FIG. 16, similarly to the information search method according to the third embodiment. Note that step S214 in FIG. 16 is different from that in the third embodiment. Hereinafter, differences will be described.

  Also in the fourth embodiment, as in the third embodiment, the keyword classification unit 35 (see FIG. 17) identifies duplicate keywords. However, in the fourth embodiment, the keyword classification unit 35 deletes the duplicate keyword from one of the ranking tables according to the ranking of the feature keyword of the duplicate keyword and the ranking of the common keyword of the duplicate keyword.

  Specifically, as shown in FIG. 21, first, the keyword classification unit 35 compares the output from the keyword ranking unit 32 with the output from the common keyword ranking unit 34, and specifies duplicate keywords (step S2111). ). This step S2111 is the same as step S2101 shown in FIG.

  For example, it is assumed that the common keyword ranking unit 34 outputs the ranking results shown in FIG. 14 and the keyword ranking unit 33 outputs the ranking results shown in FIGS. 10A and 10B for the categories A and B. In this case, the duplicate keywords are “HDD”, “DVD”, “VTR”, “recording”, and “recording time”.

  Next, the keyword classification unit 35 determines, for each duplicate keyword, whether the ranking ranking of the common keyword is equal to or lower than a threshold value (whether it is higher than the set ranking) (S2112). Here, as the threshold value, for example, the number of common keywords that can be displayed on one screen can be used. In the present embodiment, for example, the threshold is set to “6”. In this case, the common keyword ranking for the duplicate keyword “HDD” is 1, and it is determined that the threshold is 6 or less (see FIG. 22A). Similarly, the ranking of the duplicate keywords “DVD”, “VTR”, and “recording” is also determined to be equal to or less than the threshold 6 (see FIG. 22A).

  If the result of the determination in step S2112 is that the rank of the overlapping keyword is equal to or less than the threshold, the keyword classification unit 35 sets this overlapping keyword as a common keyword and deletes the corresponding keyword from the ranking result of the feature keyword (S2113). For example, “HDD”, “DVD”, “VTR”, and “recording” for which the ranking ranking of the common keyword is equal to or less than the threshold in S2112 are common keywords. Then, “DVD”, “HDD”, and “VTR” are deleted from the ranking result of the feature keyword of category A (see FIG. 22B). Also, “HDD”, “recording”, “DVD”, and “VTR” are deleted from the ranking result of the category B feature keywords (see FIG. 22B).

  On the other hand, if the result of determination in step S2112 is that the rank of the overlapping keywords is not less than or equal to the threshold value, step S2114 is executed. In step S <b> 2114, the keyword classification unit 35 determines whether there is one or more categories for which the ranking ranking of the characteristic keywords is equal to or less than the threshold for the duplicate keywords.

  For example, for the overlapping keyword “recording time” in which the ranking ranking of the common keyword is larger than the threshold 6, the keyword classification unit 35 examines the ranking ranking of the feature keywords for category A and category B. For category A, there is no keyword corresponding to “recording time”, but for category B, the ranking ranking as the characteristic keyword of “recording time” is second. Here, as the threshold value, for example, the number of feature keywords of each category that can be displayed on one screen can be employed. In the fourth embodiment, the threshold value can be set to 4. In this case, the ranking ranking 2 in the characteristic keyword of the overlapping keyword “recording time” is equal to or less than the threshold value 4.

  As a result of the determination in step S2114, the keyword classification unit 35 sets the overlapping keyword as a feature keyword (step S2115). Further, the keyword classification unit 35 deletes the corresponding keyword from the ranking result of the common keyword. For example, the keyword classification unit 35 sets “recording time” in which the ranking ranking of the feature keyword is equal to or less than the threshold in S2114 as the feature keyword, and deletes it from the ranking result of the common keyword.

  On the other hand, as a result of the determination in step S2114, if the ranking ranking of the feature keyword of the duplicate keyword is larger than the threshold, the keyword classification unit 35 sets the duplicate keyword as a common keyword and deletes the corresponding keyword from the ranking result of the feature keyword. (Step S2116).

  Thereafter, the keyword classification unit 35 determines whether or not the processing has been completed for all the duplicate keywords (step S2117). If the result of determination is that processing has not been completed for all duplicate keywords, step S2112 and subsequent steps are executed again. On the other hand, if the processing has been completed for all duplicate keywords, the keyword classification unit 35 executes Step S2118.

  In step S2118, the keyword classification unit 35 outputs the processed common keyword and feature keyword to the display device 60, and then ends the process. Thereby, the result shown in FIG. 23 is displayed on the display screen of the display device 60.

  Thus, also in the fourth embodiment, unlike the second embodiment (see FIG. 19) in which keywords such as “HDD”, “DVD”, and “recording” are displayed in duplicate, the common keyword and the feature keyword The display of overlapping keywords is omitted. Further, according to the fourth embodiment, a keyword having a high commonness among keywords common to a plurality of categories is more likely to be displayed as a common keyword than in the third embodiment. Furthermore, according to the fourth embodiment, a keyword having a higher characteristic as a feature keyword of each category is more likely to be displayed as a feature keyword than in the third embodiment. For example, as shown in FIG. 22B, a keyword “recording time” having a high ranking as a feature keyword in category B (recording function) is displayed as a feature keyword of category B, not a common keyword.

  As described above, according to the fourth embodiment, as in the third embodiment, the two types of keywords, that is, the common keyword appearing redundantly in a plurality of categories and the feature keyword indicating the characteristics of each category are: Displayed without duplication. As a result, the occurrence of a situation where the user is confused by which keyword should be selected is suppressed. Users can use common keywords when searching for content with a general concept, and can use feature keywords when searching for content with typical contents in each category, and can narrow down the content according to the purpose .

(Embodiment 5)
Next, an information search device, an information search method, and a storage medium storing a program according to Embodiment 5 of the present invention will be described with reference to FIGS. FIG. 24 is a block diagram showing a schematic configuration of the information search apparatus according to Embodiment 5 of the present invention. 25 is a diagram showing an example of a display screen of a display device connected to the information search device shown in FIG. 24. In FIG. 25A, common keywords having higher rankings are displayed, and in FIG. 25B, rankings are lower. The common keyword of is displayed.

  As shown in FIG. 24, the information processing apparatus 4 in the fifth embodiment has a configuration in which the keyword ranking unit 32 is removed from the configuration of the information processing apparatus 2 shown in the second embodiment shown in FIG. . For this reason, in the fifth embodiment, the characteristic keyword is not set, and only the common keyword is displayed on the display screen of the display device 60 as shown in FIG. In addition to the above points, the information processing apparatus 4 in the fifth embodiment is configured in the same manner as the information processing apparatus 2 in the second embodiment.

  As described above, in the fifth embodiment, only common keywords for efficiently searching for contents included in a plurality of categories are displayed. This common keyword is effective when the user is at a loss in category selection or goes back up the hierarchy many times by mistake in category selection. The fifth embodiment is effective for the purpose of solving only the above problem.

  The information search apparatus according to the present invention described above supplies a storage medium storing a program for realizing the functions of the above-described embodiments to a system or apparatus, and a computer or CPU (Central Processing Unit) included in the system or apparatus. MPU (Micro Processing Unit) can be configured by executing this program.

  In addition, this program can be stored in various types of storage media and can be transmitted via a communication medium. Here, the storage medium includes, for example, a flexible disk, hard disk, magnetic disk, magneto-optical disk, CD-ROM (Compact Disc Read Only Memory), DVD (Digital Versatile Disc), BD (Blu-ray Disc), ROM ( A read only memory (RAM) cartridge, a battery-backed RAM (Random Access Memory) memory cartridge, a flash memory cartridge, and a nonvolatile RAM cartridge are included. The communication medium includes a telephone line wired communication medium and a microwave line wireless communication medium, and includes the Internet.

  Further, when the computer executes the program that realizes the functions of the above-described embodiment, not only the functions of the above-described embodiment are realized, but also the computer is operating on the basis of the instructions of this program. A case where the functions of the above-described embodiment are realized in cooperation with an OS (Operating System) or application software is also included in the embodiment of the invention.

  Further, when the functions of the above-described embodiment are realized by performing all or part of the processing of the program by a function expansion board inserted into the computer or a function expansion unit connected to the computer, the present invention may be implemented. It is included in the form.

  Although the present invention has been described with reference to the exemplary embodiments, the present invention is not limited to the above. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the invention.

  This application claims the priority on the basis of Japanese application Japanese Patent Application No. 2008-305552 for which it applied on November 28, 2008, and takes in those the indications of all here.

  As described above, according to the present invention, an efficient search can be performed in a portal site or a reception business department that manages a set of contents such as FAQ and product information classified in a plurality of categories. . The present invention is particularly applicable to a use such as search support and has industrial applicability.

DESCRIPTION OF SYMBOLS 10 Content memory | storage part 20 Search part 30 Common keyword production | generation part 31 Keyword search part 32 Keyword ranking part 33 Common keyword extraction part 34 Common keyword ranking part 35 Keyword classification part 40 Keyword extraction part 50 Input part 60 Display apparatus 70 Database

Claims (21)

Content storage means for storing a plurality of contents classified by a plurality of categories, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories;
Search means for accepting an input of a search keyword from the outside and searching for content including the search keyword from the plurality of contents stored in the content storage means;
A keyword search means for extracting a keyword expressing an attribute of the content searched by the search means from the plurality of keywords stored in the content storage means, and for searching at least a category to which the extracted keyword belongs;
The results of investigations previous SL keyword checking means, the extracted each of the keywords, determined the number of categories each keyword belongs, and the number of contents each keyword representing an attribute, further, the number of the categories determined wherein based on the number of content and grant ranking among the keywords the ranking is granted, the keyword granted Index reaches a preset order, set to the feature keyword, furthermore, set Keyword ranking means for generating a ranking table according to the feature keywords that have been made,
When keywords belonging to a plurality of categories are extracted as common keywords from the keywords extracted by the keyword surveying unit based on the result of the survey by the keyword surveying unit, and a plurality of common keywords are extracted A common keyword extracting means for assigning a ranking to each of the extracted common keywords according to the degree of commonness, and generating a ranking table with the plurality of common keywords;
A keyword classification unit that compares the characteristic keyword with the common keyword, identifies a duplicate keyword in both as a duplicate keyword, and further deletes the keyword corresponding to the duplicate keyword from the feature keyword ranking table information retrieval apparatus comprising: a and. Content storage means for storing a plurality of contents classified by a plurality of categories, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories;
Search means for accepting an input of a search keyword from the outside and searching for content including the search keyword from the plurality of contents stored in the content storage means;
A keyword search means for extracting a keyword expressing an attribute of the content searched by the search means from the plurality of keywords stored in the content storage means, and for searching at least a category to which the extracted keyword belongs;
For each of the extracted keywords, the number of categories to which each keyword belongs and the number of contents in which each keyword expresses an attribute are obtained from the result of the investigation by the keyword investigation means, and the number of the obtained categories Based on the number of contents, ranking is assigned, and among the keywords assigned with the ranking, the keywords with the assigned ranking set in advance are set as feature keywords and further set. Keyword ranking means for generating a ranking table based on the characteristic keywords;
When keywords belonging to a plurality of categories are extracted as common keywords from the keywords extracted by the keyword surveying unit based on the result of the survey by the keyword surveying unit, and a plurality of common keywords are extracted A common keyword extracting means for assigning a ranking to each of the extracted common keywords according to the degree of commonness, and generating a ranking table with the plurality of common keywords;
The feature keyword and the common keyword are contrasted to identify a duplicate keyword in both as a duplicate keyword, and further, the ranking of the duplicate keyword in the feature keyword, the ranking of the duplicate keyword in the common keyword, And a keyword classifying means for deleting the duplicate keyword from the common keyword ranking table or the feature keyword ranking table . The keyword ranking means, the number of the content, divided by the number or numerical values calculated from the number of the categories of the category, based on a quotient obtained, imparts the ranking, according to claim 1 or 2 The information search device described in 1. A keyword extracting means;
The keyword extraction unit, from the database of the outer portion to which the plurality of contents to be searched is stored, representing the plurality of contents each attribute, and, extracts a keyword that belongs to one of the plurality of categories and, and stores the extracted the keywords in the content storage unit, the information retrieval apparatus according to any one of claims 1 to 3. The keyword extraction unit, said that for each of the plurality of contents respectively stored in the database, divides the text included in the content to the word, to extract each word obtained by the division as the keyword, claim 4 The information search device described in 1. When the plurality of contents to be searched are classified into a plurality of hierarchical categories and stored in the database,
The keyword extracting means, for each of the plurality of contents stored in the database, obtains the lowermost category associated with the content, extracting the category determined as the keyword, claim 4 Information retrieval device. The keyword classification means, in contrast with the feature keywords, and the common keywords, keywords that overlap in both identified as duplicate keywords, further wherein duplicate keywords is displayed on the display screen of the display device of the external The information search device according to any one of claims 1 to 6 , wherein a display mode of the duplicate keywords is different from a display mode of other keywords. (A) storing a plurality of contents classified in a plurality of categories, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories in a content storage unit ;
(B) The search means accepts an input of a search keyword from the outside, and searches the content including the search keyword from the plurality of contents stored in the process of (a),
(C) The keyword search means extracts a keyword expressing the attribute of the content searched in the process (b) from the plurality of keywords stored in the process (a), and the extracted keyword Investigate at least the category to which the keyword belongs,
(D) The keyword ranking means obtains, for each extracted keyword, the number of categories to which each keyword belongs and the number of contents for which each keyword expresses an attribute, based on the result of the investigation in the process (c). Further, based on the obtained number of categories and the number of contents, a ranking is given to the extracted keywords for each category, and among the keywords given the rankings, the rankings given are A keyword having a preset ranking is set as a feature keyword, and a ranking table is generated based on the set feature keyword.
(E) A keyword belonging to a plurality of categories is selected as a common keyword from the keywords extracted in the process (c) based on the result of the investigation in the process (c) by the common keyword extraction means. Extract and
(F) The keyword classification means compares the characteristic keyword set in the process (d) with the common keyword extracted in the process (e), and uses a keyword that overlaps as a duplicate keyword. An information search method for identifying and deleting a keyword corresponding to the duplicate keyword from the feature keyword ranking table. (A) storing a plurality of contents classified in a plurality of categories, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories in a content storage unit;
(B) The search unit accepts an input of a search keyword from the outside, and searches the content including the search keyword from the plurality of contents stored in the content storage unit;
(C) The keyword search means extracts a keyword expressing the attribute of the content searched in the process (b) from the plurality of keywords stored in the process (a), and the extracted keyword Investigate at least the category to which the keyword belongs,
(D) The keyword ranking means obtains, for each extracted keyword, the number of categories to which each keyword belongs and the number of contents for which each keyword expresses an attribute, based on the result of the investigation in the process (c). Further, based on the obtained number of categories and the number of contents, a ranking is given to the extracted keywords for each category, and among the keywords given the rankings, the rankings given are A keyword having a preset ranking is set as a feature keyword, and a ranking table is generated based on the set feature keyword.
(E) The common keyword extracting means extracts keywords belonging to a plurality of categories as common keywords from the keywords extracted by the keyword searching means based on the result of the investigation in the process (c). ,
When a plurality of common keywords are extracted by the process of (e), a ranking is given to each of the plurality of common keywords extracted by the process of (c) according to the degree of commonality. Generate a ranking table with multiple common keywords,
(F) The keyword classification means compares the feature keyword set in the process (d) with the common keyword extracted in the process (e), and determines a duplicate keyword in the duplicate keyword. Identified as
Further, according to the ranking of the duplicate keyword in the feature keyword and the ranking of the duplicate keyword in the common keyword by the keyword classification means, from the common keyword ranking table or the feature keyword ranking table, An information search method characterized by deleting duplicate keywords . In the process (d), the keyword ranking means divides the number of contents by the number of categories or a value calculated from the number of categories, and the ranking is calculated based on the obtained division value. The information search method according to claim 8 or 9, which is given. ( G ) The keyword extraction means expresses the attributes of each of the plurality of contents from an external database in which the plurality of contents to be searched are stored, and keywords belonging to any of the plurality of categories. The information search method according to any one of claims 8 to 10 , further comprising: an extraction process for storing in the process (a). In the processing of ( g ), the keyword extraction unit divides a sentence included in the content into words for each of the plurality of contents stored in the database, and each word obtained by the division is The information search method according to claim 11 , wherein the information search method is extracted as a keyword. When the plurality of contents to be searched are classified in a plurality of hierarchical categories and stored in the database,
In the process ( g ), for each of the plurality of contents stored in the database, the lowermost category associated with the content is obtained by the keyword extraction unit , and the obtained category is used as the keyword. The information search method according to claim 11 , wherein the information is extracted. Further, the keyword classification means compares the characteristic keyword set in the process (d) with the common keyword extracted in the process ( e ), and determines a duplicate keyword in both identified as, further wherein the display mode of the duplicate keywords in a state having different and other keywords display mode to display the said duplicate keywords and other keywords on a display screen of the display device, of claims 8 The information search method according to any one of 13 . (A) storing a plurality of contents classified by a plurality of categories, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories;
(B) Accepting an input of a search keyword from the outside, searching the content including the search keyword from the plurality of contents stored in the process of (a),
(C) From the plurality of keywords stored in the process (a), a keyword expressing the attribute of the content searched in the process (b) is extracted, and the category to which the extracted keyword belongs is extracted. At least investigate,
(D) For each extracted keyword, the number of categories to which each keyword belongs and the number of contents in which each keyword expresses an attribute are obtained from the results of the investigation in the process of (c), and further obtained. based on the number of number and the contents of the categories, for each of the categories, the ranking assigned to the extracted the keyword, among the keywords the ranking is assigned, granted ranking preset The keywords that have been ranked are set as feature keywords, and a ranking table is generated based on the set feature keywords.
(E) Based on the result of the investigation in the process (c), keywords belonging to a plurality of categories are extracted as common keywords from the keywords extracted in the process (c).
(F) The feature keyword set in the process (d) is compared with the common keyword extracted in the process (e), and a keyword that is duplicated in both is specified as a duplicate keyword, and A program for causing a computer to execute processing for deleting a keyword corresponding to the duplicate keyword from the feature keyword ranking table . (A) storing a plurality of contents classified by a plurality of categories, a plurality of keywords expressing attributes of any of the plurality of contents, and the plurality of categories;
(B) Accepting an input of a search keyword from the outside, searching the content including the search keyword from the plurality of contents stored in the process of (a),
(C) From the plurality of keywords stored in the process (a), a keyword expressing the attribute of the content searched in the process (b) is extracted, and the category to which the extracted keyword belongs is extracted. At least investigate,
(D) For each extracted keyword, the number of categories to which each keyword belongs and the number of contents in which each keyword expresses an attribute are obtained from the results of the investigation in the process of (c), and further obtained. Based on the number of categories and the number of contents, a ranking is assigned to the extracted keywords for each category, and among the keywords assigned the rankings, the rankings assigned are set in advance. Then, the keyword is set as a feature keyword, and a ranking table is generated based on the set feature keyword.
(E) Based on the result of the investigation in the process (c), keywords belonging to a plurality of categories are extracted as common keywords from the keywords extracted in the process (c).
When a plurality of common keywords are extracted in the process (e), a ranking is assigned to each of the extracted common keywords according to the degree of commonality, and the ranking is performed based on the plurality of common keywords. Generate a table,
(F) The feature keyword set in the process (d) is compared with the common keyword extracted in the process (e), and a keyword that is duplicated in both is specified as a duplicate keyword.
Furthermore, a process of deleting the duplicate keyword from the common keyword ranking table or the feature keyword ranking table according to the ranking of the duplicate keyword in the feature keyword and the ranking of the duplicate keyword in the common keyword. A program to be executed by a computer . In the process of the (d), the number of the content, divided by the number or numerical values calculated from the number of the categories of the category, based on a quotient obtained, imparts the ranking, claim 15 Or the program of 16 . ( G ) From the external database in which the plurality of contents to be searched are stored, keywords representing the attributes of the plurality of contents and belonging to any of the plurality of categories The program according to claim 15 or 17 , further causing the computer to execute an extraction process so as to be stored in the process. In the process ( g ), for each of the plurality of contents stored in the database, a sentence included in the contents is divided into words, and each word obtained by the division is extracted as the keyword. Item 19. The program according to item 16 or 18 . When the plurality of contents to be searched are classified in a plurality of hierarchical categories and stored in the database,
In the process of the (g), for each of the plurality of contents stored in the database, it obtains the lowermost category associated with the content, extracting the category determined as the keyword, claim 18 The program described in. And the feature keyword set in the process of pre-SL (d), the by comparing the common keywords extracted in the process of (e), a duplicate keywords in both identified as duplicate keywords, further, the 16. A process for causing a computer to execute a process of displaying the duplicate keyword and other keywords on a display screen of a display device in a state in which a duplicate keyword display mode is different from a display mode of other keywords. The program according to any one of 20 .

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