WO2013047471A1 - Store information search system - Google Patents

Store information search system Download PDF

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Publication number
WO2013047471A1
WO2013047471A1 PCT/JP2012/074476 JP2012074476W WO2013047471A1 WO 2013047471 A1 WO2013047471 A1 WO 2013047471A1 JP 2012074476 W JP2012074476 W JP 2012074476W WO 2013047471 A1 WO2013047471 A1 WO 2013047471A1
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WO
WIPO (PCT)
Prior art keywords
information
feature data
store
user terminal
search
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PCT/JP2012/074476
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French (fr)
Japanese (ja)
Inventor
靖弘 鍋嶋
純也 半田
宗高 池田
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株式会社ぐるなび
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Publication of WO2013047471A1 publication Critical patent/WO2013047471A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0641—Shopping interfaces
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/242—Query formulation
    • G06F16/243—Natural language query formulation

Definitions

  • the present invention relates to a store information search system that provides store information to a user terminal via a network.
  • search system that provides an information search service for restaurants and the like to user terminals such as personal computers and mobile phones via a communication network.
  • This search system generally provides a Web site having a search window for inputting a word or phrase (or a logical combination thereof) to a user terminal, and the word input from the user terminal to the search window And phrases are accepted as search criteria.
  • the search system searches for information corresponding to the received search condition and provides the searched information to the user terminal.
  • Patent Document 1 discloses a store search technique using the above-described search system.
  • the search system (information search display server) described in Patent Document 1 is connected to a user terminal via a communication network.
  • the search system accepts “keyword” and “region designation” input from the user terminal as search conditions, searches for stores corresponding to the search conditions, and on the map of the area specified by the user terminal, Display data in which the location of the store is arranged is transmitted.
  • information retrieval by the above-described conventional retrieval system has a technical problem that information that cannot be specifically specified by words or phrases or information corresponding to vague needs cannot be retrieved.
  • the search system of the prior art can search for information that can be specified by words or phrases, but cannot search for things that are unknown, unconscious, forgotten, and the like.
  • the present invention has been made in view of the above technical problem, and provides a store information search system capable of searching for information that cannot be specifically specified by words or phrases or information corresponding to vague needs. With the goal.
  • the present invention for solving the above technical problem is a store information search system, a store database storing store information, feature data indicating store features extracted from the store information, and a relationship between each feature data
  • An information update unit that calculates a degree and associates a plurality of feature data with a network structure based on the degree of association, a feature database that stores the plurality of associated feature data, and an area and a cooking genre from a user terminal The selection is accepted, the store information is searched for the range of the selected area and the cooking genre as a target range, and the frequency is high among the feature data included in the searched store information using the feature database.
  • Extracting a plurality of feature data associated with the feature data presenting the extracted plurality of feature data to the user terminal; and
  • the screen information for accepting the selection of the feature data shown is transmitted, the selection of one of the feature data designated on the screen information is accepted from the user terminal, the received feature data is set as a search condition, and the setting is performed.
  • the store information is searched according to the search conditions, store guide information for guiding the store is created based on the searched store information in the user terminal, and the received feature data using the feature database;
  • an information providing unit that transmits information.
  • the server group of the present invention shows a plurality of feature data indicating the features of the store on the user terminal, causes the user terminal to select feature data from the plurality of feature data, and stores the feature data based on the selected feature data.
  • Search for information Therefore, when a user does not come up with a word or phrase representing a desired store when searching (for example, even when the image of a store to be visited is vague), the user sees a plurality of feature data. As a result, you will be able to recognize your potential needs and their direction.
  • the server group presents feature data that is the keyword to be searched, the user may arrive at store information that was not imagined when searching. You can present information that was not available and suggest an unknown experience.
  • the store information includes, for example, contents introducing the restaurant (PR statement or information indicating the characteristics of the store), the location and telephone number of the restaurant, the menu provided by the restaurant, the restaurant, Information associated with event information, homepage address, etc.
  • the store information also includes store detailed information (store word-of-mouth information, etc.) showing details of the store, and store guide information created by extracting certain items from the store information.
  • the store information retrieved by the selected feature data.
  • each segment to be searched (for example, a region or a cooking genre) By analyzing the store information), it is possible to search with feature data corresponding to the segment.
  • the search information includes feature data set as the search condition, and includes a delete button for accepting deletion of the search condition.
  • the information providing unit receives information from the user terminal. When the selection of the delete button is accepted, it is desirable to delete the search condition that has already been set.
  • the search can be performed again with a simple operation.
  • the store information stored in the store database includes store detail information that presents the details of the store in detail
  • the store guide information includes a request button that accepts presentation of the store detail information.
  • the information update unit updates the feature database by performing a process of associating the feature data with a network structure every predetermined time.
  • This configuration is due to the fact that store information that introduces stores has a characteristic that it is frequently changed according to the season and time. For example, if the store information is restaurant information, menus and services provided by the season are often changed (even in the same restaurant, if the store is winter, the feature data of the store may be “nabe” etc. In summer, the characteristic data may be “cold noodles”). Therefore, by comprising in this way, the characteristic data of a shop can be provided as what respond
  • FIG. 1 is a block diagram showing the configuration of the information search system of this embodiment.
  • the information search system of this embodiment includes a server group 1 connected to a communication network NW such as the Internet and a user terminal 3 connected to the communication network NW.
  • the server group 1 can perform data communication with the user terminal 3 via the communication network NW, and searches for restaurant information in response to a request from the user terminal 3.
  • the server group 1 includes one or a plurality of server devices.
  • the user terminal 3 includes an information processing apparatus (a personal computer, a PDA, Information processing devices such as smartphones and mobile phones).
  • an information processing apparatus a personal computer, a PDA, Information processing devices such as smartphones and mobile phones.
  • the user terminal 3 can access the server group 1 via the communication network NW, receive the web page constituting the website transmitted from the server group 1, and display the web page on the display unit. ing. Further, the user terminal 3 receives an operation via the input unit, selects various data displayed on the Web page, transmits the selected data to the server group 1, and is formed on the Web page. A free word can be input to the search window and transmitted to the server group 1.
  • the server group 1 provides a web site (screen information (see FIGS. 4 and 5)) for restaurant search to the user terminal 3 in response to a request from the user terminal 3, and the user terminal 3 displays the screen. Data input on information is accepted as a search condition.
  • the server group 1 uses the store database 20 to search for restaurant information according to the received search conditions, and transmits the searched restaurant information to the user terminal 3.
  • the information search system of this embodiment has the characteristics in the server group 1, and the user terminal 3 is the same as that of a well-known technique. Therefore, in the following, the configuration of the server group 1 will be described in detail, and the description of other configurations will be simplified.
  • the server group 1 includes a control unit 10, an information providing unit 11, an information updating unit 12, and a storage unit 13.
  • the storage unit 13 stores a store database 20, a feature database 30, and web page data 40.
  • the store database 20 includes, for each restaurant, contents introducing the restaurant (PR text and information indicating the characteristics of the store), the location and telephone number of the restaurant, a menu provided by the restaurant, and a restaurant.
  • This is a database in which store information associated with event information, homepage address, and the like is registered.
  • Store information registered in the store database 20 includes store detail information (store word-of-mouth information, etc.) where the details of the store are shown in detail, and store guide information created by extracting certain items from the store information. include.
  • this store information is comprised so that it can change suitably according to the request
  • the feature database 30 extracts a plurality of feature data (keywords that become store cues) indicating the features of the store by text mining from the store information, and based on the relevance of each feature data calculated by the text mining.
  • the feature data extracted by text mining includes a keyword indicating the contents that can be experienced at a restaurant, a keyword indicating a merit when using the restaurant, and the like.
  • the PR statement for Store A is “Italian famous Ginza store, wine is delicious hot stone oven pizza”
  • the PR statement for Store B is “hot silver fluffy oyakodon”
  • “Ishigama pizza” Relevance of “Atsatsu” is high, relevance of “Ishigama Pizza” and “Reputable Store” is low. Areas and cuisine genres such as “Ginza” and “Italian”, exclamations and “Voice” are information.
  • the update unit 12 deletes it.
  • “rice” has a high degree of relevance. Note that whether the relevance is high or low depends on the distance between each word and phrase that is characteristic data (if the word and phrase are adjacent to each other, the relevance is high. The more words there are, the less relevant they are (if the words are far apart), or the more relevant they are when they are related to other words (as adjectives and adverbs) Otherwise, the degree of relevance is low).
  • the web page data 30 is a database in which various data such as images and icons necessary for generating a web page to be transmitted to the user terminal 3 are registered.
  • the hardware configuration of the server device configuring the server group 1 is not particularly limited.
  • the server group 1 includes a CPU, an auxiliary storage device, a main storage device, a network interface, and an input / output interface. Consists of.
  • the auxiliary storage device stores a program for realizing the functions of the control unit 10, the information providing unit 11, and the information updating unit 12.
  • the storage unit 13 described above is formed in a predetermined area of the auxiliary storage device. The functions of the control unit 10, the information providing unit 11, and the information updating unit 12 are realized when the CPU loads the program stored in the auxiliary storage device to the main storage device and executes it.
  • control unit 10 controls the operation of the entire server group 1 and accepts various settings of the server group 1.
  • the information providing unit 11 configures a restaurant search Web site (restaurant search site) provided to the user terminal 3 using the store database 20, the feature database 30, and the Web page data 40 stored in the storage unit 13. Web page (screen information) to be generated is generated. Further, the information providing unit 11 transmits the generated Web page to the user terminal 3 and causes the display unit of the user terminal 3 to display the Web page (see FIGS. 4 and 5). On this Web page, a plurality of feature data (specific details will be described later) registered in the feature database 30 (see FIG. 3) are shown to be selectable. And the information provision part 11 receives selection of the feature data which the user terminal 3 designates on a Web page, sets the received feature data as a search condition, and searches store information of the store database 20 by the search condition. . The information providing unit 11 transmits the searched store information to the user terminal 3 and causes the display unit of the user terminal 3 to display the searched store information.
  • the information update unit 12 extracts a plurality of feature data indicating the features of the store from the store information registered in the store database 20.
  • a plurality of feature data indicating the features of the store from the store information registered in the store database 20.
  • Each extracted feature data includes the relevance and frequency of the feature data.
  • automatic analysis, particularly taste mining is preferable.
  • the information updating unit 12 stores a plurality of feature data in the feature database 30 in association with the network structure based on the calculated relevance.
  • the information updating unit 12 performs processing for associating the feature data with the network structure at predetermined time intervals (for example, every 24 hours), and updates the registered contents of the feature database 30.
  • the information update unit 12 performs text mining on the store information registered in the store database 20 for each predetermined condition, extracts feature data, and generates a plurality of types of feature databases 30. Yes.
  • the information update unit 12 generates a feature database 30 for all store information by text mining for all store information registered in the store database 20. Further, the information updating unit 12 classifies the store information registered in the store database 20 for each predetermined area (area) (the areas include other nations such as Kanto, Tokyo, Ginza, Kansai, Osaka, Kyoto, etc.). Then, text mining is performed for each classified store information, and a feature database 30 for each region is generated. Further, the information updating unit 12 classifies the store information registered in the store database 20 for each predetermined cooking genre (the cooking genre includes non-genre in addition to Japanese food, Italian, etc.) and then stores the classified store. Text mining is performed for each information, and a feature database 30 for each cooking genre is generated. The information update unit 12 classifies the store information registered in the store database 20 for each predetermined region and each predetermined dish genre, performs text mining for each classified store information, and performs each region and each dish genre. The feature database 30 is generated.
  • area the areas include other nations such as Kanto, Tokyo, Gin
  • the text mining performed by the information updating unit 12 is the same as a technique realized by a well-known technique, and thus detailed description thereof is omitted.
  • feature data indicating the characteristics of a store is extracted from the store information registered in the store database 20 by text mining.
  • the present invention is not limited to this.
  • the data that is subject to text mining may include advertisements of the restaurant and information posted on a homepage (Web site).
  • the information update unit 12 can arbitrarily delete the words of area and cooking genre from the feature data.
  • FIG. 2 is a conceptual diagram of the data structure of the feature database of this embodiment.
  • FIG. 3 is a schematic diagram showing an example of the data structure of the feature database of this embodiment.
  • the description of the types of feature databases (types for each region, for each predetermined dish genre, etc.) is omitted for the sake of simplicity.
  • the feature database 30 classifies a plurality of feature data 112 extracted by text mining into four groups, and then sets each feature data 112 based on the relevance calculated by text mining. Are linked in parallel (the data structure is a mesh structure).
  • the plurality of feature data 112 are classified into four groups of “optimum scene”, “cooking / drink”, “facility / service”, and “atmosphere / location / reputation”.
  • the “optimum scene” indicates a group to which information relating to a scene suitable for a restaurant such as “entertainment” and “date” belongs (for example, “entertainment” as the feature data 112 is optimal for entertainment). Extracted from restaurant information).
  • “Cooking / Drink” indicates a group to which information about restaurant menus such as “Ishigama Pizza” and “All-you-can-drink” belong.
  • Equipment / service indicates a group to which information on services and facilities provided by restaurants such as “shows” and “sofa seats” belongs.
  • the “atmosphere / location / reputation” indicates a group to which information such as the atmosphere of a restaurant such as “lively” and “Nangoku Resort” belongs.
  • the classification of the feature data is performed by the information update unit 12.
  • the feature data is configured by associating (linking) the feature data 112 having similar relationships with each other in parallel regardless of the classified group. That is, if the feature data 112 have a high degree of association, the association is made regardless of whether or not they are in the same group. For example, “stone oven pizza” and “wine” are menus provided at Italian restaurants, and are associated with each other because they are highly related to each other.
  • the feature database 30 is configured as shown in FIG. 3, for example.
  • the feature database 30 includes a field 31 for registering feature data extracted by text mining, a field 32 for registering the frequency calculated by text mining, a field 33 for registering the relevance calculated by text mining, and a classification And a field 34 for registering a single record, and a plurality of records are registered.
  • the frequency “XXX”, the degree of association “XX”, and the classification “optimum scene” are registered in association with the “easy” feature data. ing.
  • the information provision part 11 By comprising in this way, it becomes possible for the information provision part 11 to produce
  • the feature data can be presented in different colors for each classification.
  • FIG. 4 and FIG. 5 are schematic diagrams illustrating an example of screen information for restaurant search provided to the user terminal by the server group of the present embodiment. It is assumed that the above-described feature data is registered in the feature database 30 of the server group 1 (the processing of the information updating unit 12 is completed).
  • the user terminal 3 accesses the server group 1 via the communication network NW, and requests the server group 1 to present a restaurant search site.
  • the information providing unit 11 of the server group 1 When receiving the presentation request, the information providing unit 11 of the server group 1 generates a Web page that configures the restaurant search site, and transmits the generated Web page to the user terminal 3.
  • the information providing unit 11 uses the store database 20, the feature database 30, and the web page data 40 to provide a restaurant search website (provided to the user terminal 3).
  • the screen information 100a constituting the restaurant search site is generated and transmitted to the user terminal 3.
  • the information providing unit 11 takes as an example a case where the user terminal 3 accepts designation of “national” as “region designation” and “non-genre” as a cooking genre.
  • the information providing unit 11 extracts feature data having a high frequency (for example, the highest frequency) among the feature data registered in the feature database 30, and also extracts the feature data and the degree of association. A predetermined number of feature data with high is extracted. Thereby, a plurality of feature data is extracted (in the example shown, 17 feature data are extracted). Further, the information providing unit 11 uses the extracted plurality of feature data as a search condition, and performs a search for the store database 20 in which “Region designation” is “Nationwide” and “Cooking genre” is “Non-genre”. Do. When the area designation is nationwide and the food genre is non-genre, all store information is searched.
  • a high frequency for example, the highest frequency
  • the information provision part 11 produces
  • the screen information 100 a is displayed on the display unit of the user terminal 3.
  • the screen information 100a illustrated in FIG. 4 includes a search designation area 110 for accepting a search condition and a store guidance area where shop guidance information for guiding a searched restaurant is presented. 120.
  • the search designation area 110 is provided with a feature data area 111 for displaying the plurality of extracted feature data 112 and receiving designation of the feature data.
  • the search designation area 110 includes an area designation window 113 for accepting area designation, a genre designation window 114 for receiving a dish genre, a feature data display area 115 in which feature data selected by the user is presented, and a user A delete button 116 for accepting batch deletion of selected feature data is provided.
  • the feature data 112 presented in the feature data area 111 is presented after being color-coded according to its classification (see FIGS. 2 and 3).
  • the store information area 120 store description information including a simple explanation for introducing each restaurant and the location and telephone number of the restaurant is presented.
  • the store guidance area 120 includes request buttons 121 and 122 for accepting presentation of store detailed information, and a request for presenting detailed information of each restaurant can be accepted from the user terminal 3. .
  • the information provision part 11 transmits the shop detailed information, such as word-of-mouth information, with respect to the user terminal 3 by accepting selection of the request buttons 121 and 122 from the user terminal 3.
  • the user terminal 3 displaying the screen information 100a selects any of the feature data 112 presented in the screen information 100a, inputs a desired area in the area designation window 113, or the genre designation window 114. You can enter the genre in
  • the user terminal 3 selects one feature data on the screen information 100 a
  • the selected information is transmitted to the information providing unit 11 of the server group 3.
  • the information provision part 11 receives selection of the feature data which the user terminal 3 designated on the screen information 100a.
  • a case where the user terminal 3 selects “freely” as the feature data is taken as an example.
  • the information providing unit 11 sets the received feature data (referred to as “first feature data” for convenience of explanation) as a search condition, and stores the store according to the set search condition. Search for information. Further, the information providing unit 11 extracts a plurality of feature data having a high degree of association with the “first feature data” using the feature database 30, and guides the store of the searched store information to the user terminal 3. Screen information (search information) 100b (see FIG. 5) including “store guide information” and “a plurality of feature data highly related to the first feature data” is generated and transmitted to the user terminal 3. Thereby, the screen information 100 b is displayed on the display unit of the user terminal 3.
  • the feature data 112 displayed in the feature data area 111 is related to the first feature data ("feel free"). It has been changed to a higher one.
  • first feature data (“feel free”) is presented as a search condition.
  • store guide information for guiding the searched store is presented using the first feature data (“feel free”) as a search condition.
  • any one of the feature data 112 presented in the screen information 100b is selected, a desired area is input to the area designation window 113, and a genre designation window is displayed.
  • the search can be continued by inputting a genre in 114.
  • the user terminal 3 selects the next feature data (referred to as “second feature data” for convenience of explanation) from the feature data 112 on the screen information 100b, the selected information is the information of the server group 3. It is transmitted to the providing unit 11. Thereby, the information provision part 11 receives selection of the 2nd feature data which the user terminal 3 designated on the screen information 100a.
  • the information providing unit 11 When the information providing unit 11 receives the selection of the second feature data, the information providing unit 11 sets “first feature data” and “second feature data” as search conditions, and searches store information based on the set search conditions. Further, the information providing unit 11 extracts a plurality of feature data having a high degree of relevance with the “second feature data” using the feature database 30, and sends the “store guide information for guiding the searched store” to the user terminal 3. ”And“ a plurality of feature data highly related to the second feature data ”are generated and transmitted to the user terminal 3. As a result, new screen information is displayed on the display unit of the user terminal 3. In addition, when the user continues to search further, the same operation as described above may be performed on the new screen information to select the feature data.
  • N feature data 112 (N is an integer of 1 or more) can be selected, and restaurant search is performed using the selected N feature data 112 as a search condition. Configured to do.
  • a delete button 116 that accepts batch deletion of feature data selected by the user is provided. Specifically, when receiving the selection of the delete button 116 from the user terminal 3, the information providing unit 11 collectively deletes all feature data set as a search condition. According to this configuration, when the user designates a plurality of feature data and searches for store information, when the user wants to search under different conditions, the search can be performed again with a simple operation. it can.
  • screen information 100a and 100b when an input of a desired area is received in the area specifying window 113 or an input of a desired genre is received in the genre specifying window 114 on the above-described screen information 100a and 100b, for each area or each cooking genre.
  • Screen information is generated using the feature database 30. That is, restaurant information that narrows down the area and genre can be searched.
  • the user of the user terminal 3 selects feature data from the plurality of feature data provided by the server group 1, together with the store information retrieved by the selected feature data.
  • feature data that is similar (highly related) to the selected feature data. That is, according to the present embodiment, even if the user does not come up with a store search keyword specifically, feature data for searching for a store is presented to be selectable. Can fulfill the needs.
  • the store information can be searched with a plurality of feature data that the user is interested in, the possibility of searching for the store that the user is seeking in the subconsciousness is increased.
  • the server group 1 that can search for information that cannot be specifically specified by words or phrases or information that corresponds to vague needs.
  • this invention is not limited to embodiment mentioned above, A various deformation
  • the store information is a restaurant
  • the present invention is also applied to store information other than restaurants. Can be provided in a unified form.

Abstract

Provided is a store information search system that searches for information that cannot be specified in words or phrases and information corresponding to vague needs. The store information search system is provided with a store database (20) for registering store information, an information update unit (12) that extracts a plurality of feature data indicating the store features by text mining the store information and assigning the relationships among the feature data in a mesh structure based on the relevance of each feature data calculated by text mining, a feature database (30) for storing a plurality of related feature data, and an information provider (11) that uses the feature database (30) to extract feature data frequently having a high degree of relevance to frequent feature data, transmits image information that accepts the selection of extracted feature data to a user terminal (3), receives the selection of the feature data specified by user terminal (3) in the image information, and searches for store information with the accepted feature data as the search conditions.

Description

店舗情報検索システムStore information search system
　本発明は、ネットワークを介してユーザ端末に店舗情報を提供する店舗情報検索システムに関する。 The present invention relates to a store information search system that provides store information to a user terminal via a network.
　従来から、通信ネットワークを介して、パソコンや携帯電話等のユーザ端末に飲食店等の情報検索サービスを提供する検索システムが知られている。この検索システムは、一般的に、ユーザ端末に対して、単語やフレーズ（或いはそれらの論理的組み合わせ）を入力する検索窓を有するＷｅｂサイトを提供し、ユーザ端末から前記検索窓に入力される単語やフレーズを検索条件として受け付けるようになっている。そして、検索システムは、受け付けた検索条件に該当する情報を検索し、ユーザ端末に検索した情報を提供している。 2. Description of the Related Art Conventionally, a search system that provides an information search service for restaurants and the like to user terminals such as personal computers and mobile phones via a communication network is known. This search system generally provides a Web site having a search window for inputting a word or phrase (or a logical combination thereof) to a user terminal, and the word input from the user terminal to the search window And phrases are accepted as search criteria. The search system searches for information corresponding to the received search condition and provides the searched information to the user terminal.
　そして、上記のような検索システムによる店舗検索の技術が特許文献１に開示されている。特許文献１に記載された検索システム（情報検索表示サーバ）は、通信ネットワークを介してユーザ端末に接続されている。また、前記検索システムは、ユーザ端末から入力される「キーワード」及び「地域指定」を検索条件として受け付け、当該検索条件に該当する店舗を検索し、ユーザ端末に指定されたエリアの地図上に、店舗の位置を配置した表示データを送信するようになっている。 Further, Patent Document 1 discloses a store search technique using the above-described search system. The search system (information search display server) described in Patent Document 1 is connected to a user terminal via a communication network. In addition, the search system accepts “keyword” and “region designation” input from the user terminal as search conditions, searches for stores corresponding to the search conditions, and on the map of the area specified by the user terminal, Display data in which the location of the store is arranged is transmitted.
特開２００２－８２９５８号公報JP 2002-82958 A
　ところで、情報検索において、言葉やフレーズなどで具体的に特定できない情報や漠然としたニーズに対応する情報を検索ができれば、様々な分野において非常に有用である。例えば、外食目的の飲食店を探すときに、「何か（未知の）美味しいものが食べたい」、「何か（未知の）面白い店へ行きたい」等の漠然としたニーズや潜在ニーズを持っているものの、飲食店を特定するための具体的なキーワードやフレーズが思い付かないことが多くある。このような場合に、漠然としたニーズや潜在ニーズを満たす飲食店を検索することができれば便利である。 By the way, in information retrieval, if information that cannot be specifically specified by words or phrases or information that corresponds to vague needs can be retrieved, it is very useful in various fields. For example, when searching for restaurants for eating out, there are vague and potential needs such as "I want to eat something (unknown) and delicious", "I want to go to something (unknown) and interesting" However, there are many cases where a specific keyword or phrase for identifying a restaurant cannot be conceived. In such a case, it would be convenient if a restaurant satisfying vague needs and potential needs could be searched.
　しかしながら、上述した従来技術の検索システムによる情報検索は、言葉やフレーズなどで具体的に特定できない情報や漠然としたニーズに対応する情報を検索できないという技術的課題を有している。具体的には、従来技術の検索システムにより所望の情報を検索して見付けるためには、検索するときに、所望の情報を表す言葉やフレーズを知っている必要がある。すなわち、従来技術の検索システムでは、言葉やフレーズなどで特定できる情報の検索はできるものの、知らないこと、無意識であること、忘れていること等を検索することができなかった。 However, information retrieval by the above-described conventional retrieval system has a technical problem that information that cannot be specifically specified by words or phrases or information corresponding to vague needs cannot be retrieved. Specifically, in order to search for and find desired information using a conventional search system, it is necessary to know words and phrases representing the desired information when searching. That is, the search system of the prior art can search for information that can be specified by words or phrases, but cannot search for things that are unknown, unconscious, forgotten, and the like.
　また，特徴データの選定の際に，登場回数だけで判定する方法もあるが，その場合，当該セグメントには存在しない語句となり，妥当ではない問題点がある。また，従来は，関係のない特徴データを単純一致させていた場合もあるが，その場合，意味としてつながりのある特徴データで検索することができない問題点もあった。 In addition, there is a method of judging only by the number of appearances when selecting feature data, but in that case, there is a problem that is not appropriate because it is a phrase that does not exist in the segment. Conventionally, there is a case where unrelated feature data is simply matched, but in that case, there is a problem that it is not possible to search with feature data having a meaning as a connection.
　本発明は上記技術的課題に鑑みてなされたものであって、言葉やフレーズなどで具体的に特定できない情報や漠然としたニーズに対応する情報を検索することができる店舗情報検索システムを提供することを目的とする。 The present invention has been made in view of the above technical problem, and provides a store information search system capable of searching for information that cannot be specifically specified by words or phrases or information corresponding to vague needs. With the goal.
　上記技術的課題を解決するための本発明は、店舗情報検索システムであって、店舗情報を格納した店舗データベースと、前記店舗情報から店舗の特徴を示す特徴データを抽出し、各特徴データの関連度を算出し該関連度に基づいて、複数の特徴データを網の目構造に関連付ける情報更新部と、前記関連付けられた複数の特徴データを格納する特徴データベースと、ユーザ端末からエリアと料理ジャンルの選択を受付け、該選択されたエリアと料理ジャンルとのかけ合わせを対象範囲として前記店舗情報を検索し、前記特徴データベースを用いて、該検索された店舗情報に含まれる特徴データのうち頻度が高い特徴データに関連付けられた複数の特徴データを抽出し、前記ユーザ端末に対して、前記抽出した複数の特徴データを提示し且つ該提示した特徴データの選択を受付ける画面情報を送信すると共に、該ユーザ端末から該画面情報上で指定した特徴データのうち１の選択を受付け、該受付けた特徴データを検索条件として設定し、該設定した検索条件により前記店舗情報を検索し、該ユーザ端末に該検索された店舗情報に基づいて、店舗を案内する店舗案内情報を作成し、さらに、前記特徴データベースを用いて該受け付けた特徴データと関連度が高い特徴データを複数新たに抽出し、該店舗案内情報と該新たに抽出した特徴データとを含む検索情報と、前記ユーザ端末から該検索情報上で新たに特徴データの選択を受け付ける画面情報とを送信する情報提供部とを有することを特徴とする。 The present invention for solving the above technical problem is a store information search system, a store database storing store information, feature data indicating store features extracted from the store information, and a relationship between each feature data An information update unit that calculates a degree and associates a plurality of feature data with a network structure based on the degree of association, a feature database that stores the plurality of associated feature data, and an area and a cooking genre from a user terminal The selection is accepted, the store information is searched for the range of the selected area and the cooking genre as a target range, and the frequency is high among the feature data included in the searched store information using the feature database. Extracting a plurality of feature data associated with the feature data, presenting the extracted plurality of feature data to the user terminal; and The screen information for accepting the selection of the feature data shown is transmitted, the selection of one of the feature data designated on the screen information is accepted from the user terminal, the received feature data is set as a search condition, and the setting is performed. The store information is searched according to the search conditions, store guide information for guiding the store is created based on the searched store information in the user terminal, and the received feature data using the feature database; A screen for newly extracting a plurality of feature data having a high degree of relevance and receiving selection of feature data on the search information from the user terminal, and search information including the store guide information and the newly extracted feature data And an information providing unit that transmits information.
　このように、本発明のサーバ群は、ユーザ端末に、店舗の特徴を示す複数の特徴データを示すとともに、ユーザ端末に、複数の特徴データから特徴データを選択させ、選択させた特徴データにより店舗情報を検索するようになっている。そのため、ユーザは、検索する際に、所望する店舗を表す言葉やフレーズを思い付かなくても（例えば、訪問したい店舗のイメージが漠然としているような場合であっても）、複数の特徴データを見ることにより、自分の潜在ニーズやその方向性を認識することができるようになる。また、サーバ群が、検索するキーワードとなる特徴データを提示してくれるため、ユーザが検索する際にイメージしていなかった店舗情報にたどり着くこともあり、ユーザに対して、従来技術の検索では得られなかった情報を提示し、未知の体験を提案することができる。 As described above, the server group of the present invention shows a plurality of feature data indicating the features of the store on the user terminal, causes the user terminal to select feature data from the plurality of feature data, and stores the feature data based on the selected feature data. Search for information. Therefore, when a user does not come up with a word or phrase representing a desired store when searching (for example, even when the image of a store to be visited is vague), the user sees a plurality of feature data. As a result, you will be able to recognize your potential needs and their direction. In addition, because the server group presents feature data that is the keyword to be searched, the user may arrive at store information that was not imagined when searching. You can present information that was not available and suggest an unknown experience.
　また、店舗情報には、例えば、飲食店毎に、その飲食店を紹介する内容（ＰＲ文や店舗の特徴を示す情報）、飲食店の所在地や電話番号、飲食店が提供するメニュー、飲食店が行うイベント情報、ホームページアドレス等を関連付けた情報が挙げられる。また、店舗情報には、店舗の内容が詳細に示されている店舗詳細情報（店舗の口コミ情報等）、店舗情報から一定事項を抽出して作成される店舗案内情報も含まれている。 In addition, the store information includes, for example, contents introducing the restaurant (PR statement or information indicating the characteristics of the store), the location and telephone number of the restaurant, the menu provided by the restaurant, the restaurant, Information associated with event information, homepage address, etc. The store information also includes store detailed information (store word-of-mouth information, etc.) showing details of the store, and store guide information created by extracting certain items from the store information.
　このように本発明によれば、ユーザ（ユーザ端末のユーザ）は、サーバ群により提供された複数の特徴データから、一の特徴データを選択した場合、選択した特徴データにより検索された店舗の情報と共に、選択した特徴データに関連する特徴データを参照することができるようになる。すなわち、本発明によれば、ユーザが提示された特徴データのうちから、興味があると思った特徴データを選択すると、その特徴データにより店舗情報が検索されると共に、その特徴データと関連度が高い、特徴データが複数提供されるようになる。その結果、本発明によれば、ユーザの漠然としたニーズを具体化させていくことができる。また、ユーザが興味を持った複数の特徴データにより、店舗情報を検索することができるため、潜在意識のなかでユーザの求めている店舗を検索する可能性が高められる。 As described above, according to the present invention, when the user (user of the user terminal) selects one feature data from the plurality of feature data provided by the server group, the store information retrieved by the selected feature data. At the same time, it becomes possible to refer to feature data related to the selected feature data. That is, according to the present invention, when feature data that the user thinks is interesting is selected from the feature data presented by the user, the store information is searched based on the feature data, and the degree of association with the feature data is determined. A plurality of high feature data will be provided. As a result, according to the present invention, the vague needs of users can be realized. In addition, since the store information can be searched by using a plurality of feature data that the user is interested in, the possibility of searching for the store that the user is seeking in the subconscious is increased.
　また、登場回数だけで表示する特徴データを選定すると、当該セグメントには存在しない語句になってしまうこととなるが、本発明のように、検索対象となるセグメント単位で（たとえば地域や料理ジャンルなどのなかで）店舗情報が解析されることで、そのセグメントに対応した特徴データで検索を行える。 In addition, if feature data to be displayed only by the number of appearances is selected, a word or phrase that does not exist in the segment is generated. However, as in the present invention, each segment to be searched (for example, a region or a cooking genre) By analyzing the store information), it is possible to search with feature data corresponding to the segment.
　さらに、特徴データとなるそれぞれの語句の間での掛かり受けを解析することで、意味としてつながりのある特徴データを検索の対象とすることができる。すなわち、特徴データとなるそれぞれの語句の距離を判定することで、その関連度を判定し、つながりを判定するので、関係のない特徴データの単純一致ではなく、意味としてつながりのある特徴データでの検索が可能となる。 Furthermore, by analyzing the dependency between each word that becomes the feature data, it is possible to search for feature data that is meaningfully connected. In other words, by determining the distance between each word or phrase that becomes feature data, the degree of association is determined, and connection is determined. Search is possible.
　また、前記検索情報には、前記検索条件として設定された特徴データが含まれていると共に、該検索条件の削除を受け付ける削除ボタンが含まれており、前記情報提供部は、前記ユーザ端末からの前記削除ボタンの選択を受け付けると、既に設定されている検索条件を削除することが望ましい。 Further, the search information includes feature data set as the search condition, and includes a delete button for accepting deletion of the search condition. The information providing unit receives information from the user terminal. When the selection of the delete button is accepted, it is desirable to delete the search condition that has already been set.
　この構成によれば、ユーザが特徴データを指定して、店舗情報を検索した後で、別の条件で検索しようと考えた場合に、簡単な操作で、検索をやり直すことができる。 According to this configuration, when the user specifies feature data and searches for store information, and then intends to search under different conditions, the search can be performed again with a simple operation.
　また、前記店舗データベースに格納された店舗情報には、店舗の内容を詳細に提示している店舗詳細情報が含まれ、前記店舗案内情報には、店舗詳細情報の提示を受け付ける要求ボタンが含まれており、前記情報提供部は、前記ユーザ端末からの前記要求ボタンの選択を受け付けると、前記ユーザ端末に対して、前記店舗詳細情報を送信することが望ましい。 Further, the store information stored in the store database includes store detail information that presents the details of the store in detail, and the store guide information includes a request button that accepts presentation of the store detail information. When the information providing unit receives selection of the request button from the user terminal, the information providing unit preferably transmits the store detailed information to the user terminal.
　この構成によれば、ユーザが店舗案内情報を見て、その店舗案内情報により示されている店舗に興味を持った場合に、そのユーザに対して、より詳細な情報（例えば、お店の口コミ情報等の）を提供することができる。 According to this configuration, when the user looks at the store guide information and is interested in the store indicated by the store guide information, more detailed information (for example, a review of the store) is given to the user. Information, etc.).
　また、前記情報更新部は、所定時間毎に、前記特徴データを網の目構造に関連付ける処理を行い、前記特徴データベースを更新することが望ましい。 In addition, it is preferable that the information update unit updates the feature database by performing a process of associating the feature data with a network structure every predetermined time.
　このように構成したのは、店舗を紹介する店舗情報が、季節や時期に応じて頻繁に変更されるという特性を有していることによる。例えば、店舗情報が飲食店情報の場合、季節により提供するメニューやサービスが変更されることが多い（同じ飲食店でも、冬であれば、店舗の特徴データが「鍋物」等になることがあり、夏であれば、特徴データが「冷麺」等になることがある）。したがって、このように構成することにより、店舗の特徴データを現状の店舗の特徴に対応するものとして提供することができる。その結果、現状の店舗の状況に適応する店舗検索を行うことができる。 This configuration is due to the fact that store information that introduces stores has a characteristic that it is frequently changed according to the season and time. For example, if the store information is restaurant information, menus and services provided by the season are often changed (even in the same restaurant, if the store is winter, the feature data of the store may be “nabe” etc. In summer, the characteristic data may be “cold noodles”). Therefore, by comprising in this way, the characteristic data of a shop can be provided as what respond | corresponds to the characteristic of the present shop. As a result, a store search adapted to the current store situation can be performed.
　本発明によれば、言葉やフレーズなどで具体的に特定できない情報や漠然としたニーズに対応する情報を検索することができるサーバ群を提供することができる。 According to the present invention, it is possible to provide a server group that can search for information that cannot be specifically specified by words or phrases or information that corresponds to vague needs.
本発明の実施形態の情報検索システムの構成を示したブロック図である。It is the block diagram which showed the structure of the information search system of embodiment of this invention. 本発明の実施形態の特徴データベースのデータ構造の概念図である。It is a conceptual diagram of the data structure of the feature database of the embodiment of the present invention. 本発明の実施形態の特徴データベースのデータ構造の一例を示した模式図である。It is the schematic diagram which showed an example of the data structure of the characteristic database of embodiment of this invention. 本発明の実施形態のサーバ群がユーザ端末に提供する飲食店検索のための画面情報の一例を示した模式図である。It is the schematic diagram which showed an example of the screen information for the restaurant search which the server group of embodiment of this invention provides to a user terminal. 本発明の実施形態のサーバ群がユーザ端末に提供する飲食店検索のための画面情報の一例を示した模式図である。It is the schematic diagram which showed an example of the screen information for the restaurant search which the server group of embodiment of this invention provides to a user terminal.
　１…サーバ群、３…ユーザ端末、１０…制御部、１１…情報提供部、１２…情報更新部、１３…記憶部、２０…店舗データベース、３０…特徴データベース、４０…Ｗｅｂページデータ DESCRIPTION OF SYMBOLS 1 ... Server group, 3 ... User terminal, 10 ... Control part, 11 ... Information provision part, 12 ... Information update part, 13 ... Memory | storage part, 20 ... Store database, 30 ... Feature database, 40 ... Web page data
　以下、本発明の実施形態について図面を用いて説明する。先ず、本実施形態の情報検索システムの構成について図１に基づいて説明する。なお、図１は、本実施形態の情報検索システムの構成を示したブロック図である。 Hereinafter, embodiments of the present invention will be described with reference to the drawings. First, the structure of the information search system of this embodiment is demonstrated based on FIG. FIG. 1 is a block diagram showing the configuration of the information search system of this embodiment.
　図示するように、本実施形態の情報検索システムは、インターネット等の通信ネットサークＮＷに接続されたサーバ群１と、通信ネットワークＮＷに接続されたユーザ端末３とを備えている。また、サーバ群１は、通信ネットワークＮＷを介して、ユーザ端末３との間でデータ通信が行えるようになっており、ユーザ端末３からの要求に応じて、飲食店情報を検索する。尚、サーバ群１は、１又は複数のサーバ装置により構成されている。 As shown in the figure, the information search system of this embodiment includes a server group 1 connected to a communication network NW such as the Internet and a user terminal 3 connected to the communication network NW. The server group 1 can perform data communication with the user terminal 3 via the communication network NW, and searches for restaurant information in response to a request from the user terminal 3. The server group 1 includes one or a plurality of server devices.
　また、ユーザ端末３は、Ｗｅｂブラウザ機能を有する制御部と、液晶ディスプレイ等で構成される表示部と、キーボードや操作ボタン等で構成される入力部とを備えた情報処理装置（パソコン、ＰＤＡ、スマートフォン、携帯電話等の情報処理装置）により構成されている。 In addition, the user terminal 3 includes an information processing apparatus (a personal computer, a PDA, Information processing devices such as smartphones and mobile phones).
　そして、ユーザ端末３は、通信ネットワークＮＷを介してサーバ群１にアクセスし、サーバ群１から送信されるＷｅｂサイトを構成するＷｅｂページを受信し、前記表示部にＷｅｂページを表示できるようになっている。また、ユーザ端末３は、入力部を介して操作を受け付け、Ｗｅｂページ上に表示された各種のデータを選択し、サーバ群１に当該選択したデータを送信したり、Ｗｅｂページ上に形成された検索窓にフリーワードを入力してサーバ群１に送信したりできるようになっている。 Then, the user terminal 3 can access the server group 1 via the communication network NW, receive the web page constituting the website transmitted from the server group 1, and display the web page on the display unit. ing. Further, the user terminal 3 receives an operation via the input unit, selects various data displayed on the Web page, transmits the selected data to the server group 1, and is formed on the Web page. A free word can be input to the search window and transmitted to the server group 1.
　また、サーバ群１は、ユーザ端末３からの要求に応じて、ユーザ端末３に、飲食店検索のためのＷｅｂサイト（画面情報（図４、５参照））を提供し、ユーザ端末３が画面情報上で入力するデータを検索条件として受け付ける。また、サーバ群１は、店舗データベース２０を用いて、前記受け付けた検索条件により飲食店情報を検索し、ユーザ端末３に検索された飲食店情報を送信するようになっている。なお、本実施形態の情報検索システムは、サーバ群１に特徴があり、ユーザ端末３は周知技術のものと同じである。そのため、以下では、サーバ群１の構成を詳細に説明し、それ以外の構成の説明を簡略化する。 Moreover, the server group 1 provides a web site (screen information (see FIGS. 4 and 5)) for restaurant search to the user terminal 3 in response to a request from the user terminal 3, and the user terminal 3 displays the screen. Data input on information is accepted as a search condition. The server group 1 uses the store database 20 to search for restaurant information according to the received search conditions, and transmits the searched restaurant information to the user terminal 3. In addition, the information search system of this embodiment has the characteristics in the server group 1, and the user terminal 3 is the same as that of a well-known technique. Therefore, in the following, the configuration of the server group 1 will be described in detail, and the description of other configurations will be simplified.
　サーバ群１は、制御部１０と、情報提供部１１と、情報更新部１２と、記憶部１３とを有している。また、記憶部１３には、店舗データベース２０、特徴データベース３０及びＷｅｂページデータ４０が格納されている。 The server group 1 includes a control unit 10, an information providing unit 11, an information updating unit 12, and a storage unit 13. The storage unit 13 stores a store database 20, a feature database 30, and web page data 40.
　また、店舗データベース２０は、飲食店毎に、その飲食店を紹介する内容（ＰＲ文や店舗の特徴を示す情報）、飲食店の所在地や電話番号、飲食店が提供するメニュー、飲食店が行うイベント情報、ホームページアドレス等を関連付けた店舗情報が登録されたデータベースである。この店舗データベース２０に登録された店舗情報には、店舗の内容が詳細に示されている店舗詳細情報（店舗の口コミ情報等）、店舗情報から一定事項を抽出して作成される店舗案内情報も含まれている。尚、この店舗情報は、飲食店等からの要求に応じて、適宜変更できるように構成されている。 In addition, the store database 20 includes, for each restaurant, contents introducing the restaurant (PR text and information indicating the characteristics of the store), the location and telephone number of the restaurant, a menu provided by the restaurant, and a restaurant. This is a database in which store information associated with event information, homepage address, and the like is registered. Store information registered in the store database 20 includes store detail information (store word-of-mouth information, etc.) where the details of the store are shown in detail, and store guide information created by extracting certain items from the store information. include. In addition, this store information is comprised so that it can change suitably according to the request | requirement from a restaurant or the like.
　また、特徴データベース３０は、前記店舗情報からテキストマイニングにより店舗の特徴を示す特徴データ（お店のウリとなるキーワード）を複数抽出し、当該テキストマイニングにより算出される各特徴データの関連度に基づいて、複数の特徴データを網の目構造に関連付けて登録したデータベースである。このように、テキストマイニングにより抽出する特徴データには、飲食店で体験できる内容を示したキーワードや飲食店を利用した場合のメリットを示したキーワード等も含まれるようになる。例えば、店ＡのＰＲ文が「銀座のイタリアンの名店で、ワインがおいしいあつあつ石窯ピザ」、店ＢのＰＲ文が「あつあつの銀のふわとろ親子丼」であったとき、「石窯ピザ」と「あつあつ」の関連度は高く、「石窯ピザ」と「名店」の関連度は低くし、「銀座」、「イタリアン」といったエリアや料理ジャンル、感嘆詞や「いらっしゃいませ」などのかけ声は、情報更新部１２が削除する。「あつあつ」には「石窯ピザ」の他、「ご飯」も関連度が高く関連付けられる。なお、関連度が高いか低いかは、特徴データとなるそれぞれの語句と語句との間の距離（語句と語句とが隣接していれば関連度が高く、語句と語句との間にあるほかの語句が多ければ多いほど（語句と語句とが離れていれば）関連度が低い、あるいは、ある語句が、他の語句にかかる（形容詞や副詞として掛かっている）場合には関連度が高く、そうでない場合には関連度が低いとする）に基づいて判定することもできる。 Further, the feature database 30 extracts a plurality of feature data (keywords that become store cues) indicating the features of the store by text mining from the store information, and based on the relevance of each feature data calculated by the text mining. A database in which a plurality of feature data is registered in association with the network structure. As described above, the feature data extracted by text mining includes a keyword indicating the contents that can be experienced at a restaurant, a keyword indicating a merit when using the restaurant, and the like. For example, if the PR statement for Store A is “Italian famous Ginza store, wine is delicious hot stone oven pizza”, and the PR statement for Store B is “hot silver fluffy oyakodon”, “Ishigama pizza” Relevance of “Atsatsu” is high, relevance of “Ishigama Pizza” and “Reputable Store” is low. Areas and cuisine genres such as “Ginza” and “Italian”, exclamations and “Voice” are information. The update unit 12 deletes it. In addition to “stone kiln pizza”, “rice” has a high degree of relevance. Note that whether the relevance is high or low depends on the distance between each word and phrase that is characteristic data (if the word and phrase are adjacent to each other, the relevance is high. The more words there are, the less relevant they are (if the words are far apart), or the more relevant they are when they are related to other words (as adjectives and adverbs) Otherwise, the degree of relevance is low).
　また、Ｗｅｂページデータ３０は、ユーザ端末３に送信するＷｅｂページの生成に必要な画像、アイコン等の各種データが登録されたデータベースである。 The web page data 30 is a database in which various data such as images and icons necessary for generating a web page to be transmitted to the user terminal 3 are registered.
　また、サーバ群１を構成するサーバ装置のハードウェア構成は特に限定されるものではないが、例えば、サーバ群１は、ＣＰＵ、補助記憶装置、主記憶装置、ネットワークインターフェース及び入出力インターフェースを備えるコンピュータにより構成される。この場合、前記補助記憶装置には、制御部１０、情報提供部１１及び情報更新部１２の機能を実現するためのプログラムが格納されている。また、前記補助記憶装置の所定領域には、上述した記憶部１３が形成されている。そして、制御部１０、情報提供部１１及び情報更新部１２の機能は、前記ＣＰＵが補助記憶装置に格納された前記プログラムを前記主記憶装置にロードして実行することにより実現される。 In addition, the hardware configuration of the server device configuring the server group 1 is not particularly limited. For example, the server group 1 includes a CPU, an auxiliary storage device, a main storage device, a network interface, and an input / output interface. Consists of. In this case, the auxiliary storage device stores a program for realizing the functions of the control unit 10, the information providing unit 11, and the information updating unit 12. In addition, the storage unit 13 described above is formed in a predetermined area of the auxiliary storage device. The functions of the control unit 10, the information providing unit 11, and the information updating unit 12 are realized when the CPU loads the program stored in the auxiliary storage device to the main storage device and executes it.
　具体的には、制御部１０は、サーバ群１全体の動作を制御すると共に、サーバ群１の各種設定を受け付ける。 Specifically, the control unit 10 controls the operation of the entire server group 1 and accepts various settings of the server group 1.
　情報提供部１１は、記憶部１３が記憶している店舗データベース２０、特徴データベース３０及びＷｅｂページデータ４０を用いて、ユーザ端末３に提供する飲食店検索のＷｅｂサイト（飲食店検索サイト）を構成するＷｅｂページ（画面情報）を生成する。また、情報提供部１１は、ユーザ端末３に、前記生成したＷｅｂページを送信し、ユーザ端末３の前記表示部に、Ｗｅｂページ（図４、５参照）を表示させる。このＷｅｂページには、特徴データベース３０（図３参照）に登録された複数の特徴データ（具体的な内容は後述する）が選択可能に示されている。そして、情報提供部１１は、ユーザ端末３がＷｅｂページ上で指定する特徴データの選択を受け付け、当該受け付けた特徴データを検索条件として設定し、その検索条件により店舗データベース２０の店舗情報を検索する。また、情報提供部１１は、ユーザ端末３に、検索した店舗情報を送信し、ユーザ端末３の表示部に、検索した店舗情報を表示させる。 The information providing unit 11 configures a restaurant search Web site (restaurant search site) provided to the user terminal 3 using the store database 20, the feature database 30, and the Web page data 40 stored in the storage unit 13. Web page (screen information) to be generated is generated. Further, the information providing unit 11 transmits the generated Web page to the user terminal 3 and causes the display unit of the user terminal 3 to display the Web page (see FIGS. 4 and 5). On this Web page, a plurality of feature data (specific details will be described later) registered in the feature database 30 (see FIG. 3) are shown to be selectable. And the information provision part 11 receives selection of the feature data which the user terminal 3 designates on a Web page, sets the received feature data as a search condition, and searches store information of the store database 20 by the search condition. . The information providing unit 11 transmits the searched store information to the user terminal 3 and causes the display unit of the user terminal 3 to display the searched store information.
　また、情報更新部１２は、店舗データベース２０に登録された店舗情報から店舗の特徴を示す特徴データを複数抽出する。抽出方法としては、自動解析、特に、テキストマイニングが好ましい。この抽出された各特徴データには、特徴データの関連度及び頻度が含まれている。関連度や頻度の算出方法としては、自動解析、特にテイストマイニングが好ましい。また、情報更新部１２は、前記算出された関連度に基づいて、複数の特徴データを網の目構造に関連付けて、特徴データベース３０に格納する。尚、情報更新部１２は、所定時間毎（例えば、２４時間毎）に、前記特徴データを網の目構造に関連付ける処理を行い、特徴データベース３０の登録内容を更新する。 Further, the information update unit 12 extracts a plurality of feature data indicating the features of the store from the store information registered in the store database 20. As an extraction method, automatic analysis, particularly text mining is preferable. Each extracted feature data includes the relevance and frequency of the feature data. As a method of calculating the degree of association and frequency, automatic analysis, particularly taste mining is preferable. The information updating unit 12 stores a plurality of feature data in the feature database 30 in association with the network structure based on the calculated relevance. The information updating unit 12 performs processing for associating the feature data with the network structure at predetermined time intervals (for example, every 24 hours), and updates the registered contents of the feature database 30.
　また、情報更新部１２は、店舗データベース２０に登録された店舗情報に対して、所定条件毎にテキストマイニングを行い、特徴データを抽出して、複数種類の特徴データベース３０を生成するようになっている。 In addition, the information update unit 12 performs text mining on the store information registered in the store database 20 for each predetermined condition, extracts feature data, and generates a plurality of types of feature databases 30. Yes.
　具体的には、情報更新部１２は、店舗データベース２０に登録された全ての店舗情報を対象にしたテキストマイニングにより、全ての店舗情報を対象にした特徴データベース３０を生成する。また、情報更新部１２は、店舗データベース２０に登録された店舗情報を所定の地域（エリア）毎（エリアには、関東、東京、銀座、関西、大阪、京都等の他全国がある）に分類した上で、分類した店舗情報毎にテキストマイニングを行い、地域毎の特徴データベース３０を生成する。また、情報更新部１２は、店舗データベース２０に登録された店舗情報を所定の料理ジャンル毎（料理ジャンルには、和食、イタリアンなどのほか、ノンジャンルがある）に分類した上で、分類した店舗情報毎にテキストマイニングを行い、料理ジャンル毎の特徴データベース３０を生成する。また、情報更新部１２は、店舗データベース２０に登録された店舗情報を所定の地域毎且つ所定料理ジャンル毎に分類した上で、分類した店舗情報毎にテキストマイニングを行い、地域毎且つ料理ジャンル毎の特徴データベース３０を生成する。 Specifically, the information update unit 12 generates a feature database 30 for all store information by text mining for all store information registered in the store database 20. Further, the information updating unit 12 classifies the store information registered in the store database 20 for each predetermined area (area) (the areas include other nations such as Kanto, Tokyo, Ginza, Kansai, Osaka, Kyoto, etc.). Then, text mining is performed for each classified store information, and a feature database 30 for each region is generated. Further, the information updating unit 12 classifies the store information registered in the store database 20 for each predetermined cooking genre (the cooking genre includes non-genre in addition to Japanese food, Italian, etc.) and then stores the classified store. Text mining is performed for each information, and a feature database 30 for each cooking genre is generated. The information update unit 12 classifies the store information registered in the store database 20 for each predetermined region and each predetermined dish genre, performs text mining for each classified store information, and performs each region and each dish genre. The feature database 30 is generated.
　尚、情報更新部１２が行うテキストマイニングは、周知技術により実現される手法と同じであるため、詳細な説明を省略する。また、本実施形態では、店舗データベース２０に登録された店舗情報からテキストマイニングにより店舗の特徴を示す特徴データを抽出しているが、特にこれに限定されるものではない。例えば、テキストマイニングの対象とするデータは、前記店舗情報に加えて、その飲食店の広告やホームページ（Ｗｅｂサイト）に掲載されている情報を含めるようにしてもよい。情報更新部１２が任意にエリアや、料理ジャンルの言葉は特徴データから削除できる。 Note that the text mining performed by the information updating unit 12 is the same as a technique realized by a well-known technique, and thus detailed description thereof is omitted. In the present embodiment, feature data indicating the characteristics of a store is extracted from the store information registered in the store database 20 by text mining. However, the present invention is not limited to this. For example, in addition to the store information, the data that is subject to text mining may include advertisements of the restaurant and information posted on a homepage (Web site). The information update unit 12 can arbitrarily delete the words of area and cooking genre from the feature data.
　次に、特徴データベース３０のデータ構造を図２及び図３に基づいて説明する。図２は、本実施形態の特徴データベースのデータ構造の概念図である。また、図３は、本実施形態の特徴データベースのデータ構造の一例を示した模式図である。尚、図２及び図３では、説明を簡単にするために、特徴データベースの種類（地域毎、所定料理ジャンル毎等の種類）についての説明を省略している。 Next, the data structure of the feature database 30 will be described with reference to FIGS. FIG. 2 is a conceptual diagram of the data structure of the feature database of this embodiment. FIG. 3 is a schematic diagram showing an example of the data structure of the feature database of this embodiment. In FIG. 2 and FIG. 3, the description of the types of feature databases (types for each region, for each predetermined dish genre, etc.) is omitted for the sake of simplicity.
　図２に示すように、特徴データベース３０は、テキストマイニングにより抽出された複数の特徴データ１１２を、４つのグループに分類した上で、テキストマイニングにより算出された関連度に基づいて、各特徴データ１１２を並列的に関連付けた構造となっている（網の目構造のデータ構成になっている）。 As shown in FIG. 2, the feature database 30 classifies a plurality of feature data 112 extracted by text mining into four groups, and then sets each feature data 112 based on the relevance calculated by text mining. Are linked in parallel (the data structure is a mesh structure).
　また、本実施形態では、複数の特徴データ１１２が「最適なシーン」、「料理・ドリンク」、「設備・サービス」及び「雰囲気・ロケーション・評判」の４つのグループに分類されている。尚、「最適なシーン」とは、「接待」や「デート」などの飲食店に適するシーンに関する情報が属するグループを示している（例えば、特徴データ１１２である「接待」は、接待に最適な飲食店の店舗情報から抽出される）。また、「料理・ドリンク」とは、「石窯ピザ」や「飲み放題」などの飲食店のメニューに関する情報が属するグループを示している。また、「設備・サービス」とは、「ショー」や「ソファ席」などの飲食店が提供するサービスや設備に関する情報が属するグループを示している。また、「雰囲気・ロケーション・評判」とは、「にぎやか」や「南国リゾート」等の飲食店の雰囲気等の情報が属するグループを示している。尚、特徴データの分類は、情報更新部１２により行われる。 In this embodiment, the plurality of feature data 112 are classified into four groups of “optimum scene”, “cooking / drink”, “facility / service”, and “atmosphere / location / reputation”. The “optimum scene” indicates a group to which information relating to a scene suitable for a restaurant such as “entertainment” and “date” belongs (for example, “entertainment” as the feature data 112 is optimal for entertainment). Extracted from restaurant information). “Cooking / Drink” indicates a group to which information about restaurant menus such as “Ishigama Pizza” and “All-you-can-drink” belong. “Equipment / service” indicates a group to which information on services and facilities provided by restaurants such as “shows” and “sofa seats” belongs. The “atmosphere / location / reputation” indicates a group to which information such as the atmosphere of a restaurant such as “lively” and “Nangoku Resort” belongs. The classification of the feature data is performed by the information update unit 12.
　また、特徴データは、分類されたグループに関係なく、互いに類似する関係がある特徴データ１１２同士が並列的に関連付け（紐付け）されて構成されている。すなわち、関連度が高い特徴データ１１２同士であれば、同じグループであるか否かに関係なく、関連付けがなされている。例えば、「石窯ピザ」と「ワイン」とはイタリア料理店で提供されるメニューであり、互いの関連度が高いため、関連付けされている。 Also, the feature data is configured by associating (linking) the feature data 112 having similar relationships with each other in parallel regardless of the classified group. That is, if the feature data 112 have a high degree of association, the association is made regardless of whether or not they are in the same group. For example, “stone oven pizza” and “wine” are menus provided at Italian restaurants, and are associated with each other because they are highly related to each other.
　そして、特徴データベース３０は、例えば、図３に示すように構成される。特徴データベース３０は、テキストマイニングにより抽出された特徴データを登録するフィールド３１と、テキストマイニングにより算出された頻度を登録するフィールド３２と、テキストマイニングにより算出された関連度を登録するフィールド３３と、分類を登録するフィールド３４とを備えて１つのレコードが構成され、複数のレコードが登録されるようになっている。例えば、図中で例示する最上位のレコードでは、特徴データである「気軽に」に、頻度「○○○」、関連度「○△×」、分類「最適なシーン」が関連付けられて登録されている。このように構成することにより、情報提供部１１が飲食店検索のＷｅｂサイト（飲食店検索サイト）を構成するＷｅｂページ（画面情報）を生成することが可能になる。また、各特徴データに分類を関連付けることで、特徴データがどの分類に属するかを提示することができる。例えば、特徴データを分類毎に色分けして提示することができる。 The feature database 30 is configured as shown in FIG. 3, for example. The feature database 30 includes a field 31 for registering feature data extracted by text mining, a field 32 for registering the frequency calculated by text mining, a field 33 for registering the relevance calculated by text mining, and a classification And a field 34 for registering a single record, and a plurality of records are registered. For example, in the highest-level record illustrated in the figure, the frequency “XXX”, the degree of association “XX”, and the classification “optimum scene” are registered in association with the “easy” feature data. ing. By comprising in this way, it becomes possible for the information provision part 11 to produce | generate the web page (screen information) which comprises the web site (restaurant search site) of a restaurant search. Further, by associating a classification with each feature data, it is possible to present to which classification the feature data belongs. For example, the feature data can be presented in different colors for each classification.
　次に、本実施形態の情報検索システムが行う飲食店情報検索処理について図４、図５を参照しながら説明する。ここで、図４、図５は、本実施形態のサーバ群がユーザ端末に提供する飲食店検索のための画面情報の一例を示した模式図である。尚、サーバ群１の特徴データベース３０には、上述した特徴データが登録されているものとする（情報更新部１２の処理は完了しているものとする）。 Next, restaurant information search processing performed by the information search system of this embodiment will be described with reference to FIGS. Here, FIG. 4 and FIG. 5 are schematic diagrams illustrating an example of screen information for restaurant search provided to the user terminal by the server group of the present embodiment. It is assumed that the above-described feature data is registered in the feature database 30 of the server group 1 (the processing of the information updating unit 12 is completed).
　先ず、ユーザ端末３は、通信ネットワークＮＷを介してサーバ群１にアクセスし、サーバ群１に対して飲食店検索サイトの提示要求をする。サーバ群１の情報提供部１１は、前記提示要求を受けると、飲食店検索サイトを構成するＷｅｂページを生成し、ユーザ端末３に生成したＷｅｂページを送信する。 First, the user terminal 3 accesses the server group 1 via the communication network NW, and requests the server group 1 to present a restaurant search site. When receiving the presentation request, the information providing unit 11 of the server group 1 generates a Web page that configures the restaurant search site, and transmits the generated Web page to the user terminal 3.
　具体的には、情報提供部１１は、前記提示要求を受けると、店舗データべース２０、特徴データベース３０及びＷｅｂページデータ４０を用いて、ユーザ端末３に提供する飲食店検索のＷｅｂサイト（飲食店検索サイト）を構成する画面情報１００ａ（図４参照）を生成し、ユーザ端末３に送信する。尚、以下では、情報提供部１１は、ユーザ端末３から「地域指定」として「全国」、料理ジャンルとして「ノンジャンル」の指定を受け付けている場合を例にする。 Specifically, when receiving the presentation request, the information providing unit 11 uses the store database 20, the feature database 30, and the web page data 40 to provide a restaurant search website (provided to the user terminal 3). The screen information 100a (see FIG. 4) constituting the restaurant search site is generated and transmitted to the user terminal 3. In the following, the information providing unit 11 takes as an example a case where the user terminal 3 accepts designation of “national” as “region designation” and “non-genre” as a cooking genre.
　より具体的には、情報提供部１１は、特徴データベース３０に登録された特徴データのなかで頻度が高い（例えば、一番頻度が高い）特徴データを抽出すると共に、抽出した特徴データと関連度が高い所定数の特徴データを抽出する。これにより、複数の特徴データが抽出される（図示する例では１７個の特徴データが抽出される）。また、情報提供部１１は、抽出した複数の特徴データを検索条件にし、「地域指定」が「全国」で「料理ジャンル」が「ノンジャンル」の店舗データべース２０を対象にした検索を行う。地域指定が全国で料理ジャンルがノンジャンルの場合は、全ての店舗情報を検索するが、例えば、地域指定が東京で料理ジャンルがイタリアンの場合は、掛け合わせた範囲の店舗情報のみ対象とする。そして、情報提供部１１は、前記抽出された「特徴データ」及び検索により得られた店舗を案内する店舗案内情報が提示された画面情報１００ａを生成し、ユーザ端末３に、その画面情報１００ａを送信する。これにより、ユーザ端末３の表示部には、画面情報１００ａが表示される。 More specifically, the information providing unit 11 extracts feature data having a high frequency (for example, the highest frequency) among the feature data registered in the feature database 30, and also extracts the feature data and the degree of association. A predetermined number of feature data with high is extracted. Thereby, a plurality of feature data is extracted (in the example shown, 17 feature data are extracted). Further, the information providing unit 11 uses the extracted plurality of feature data as a search condition, and performs a search for the store database 20 in which “Region designation” is “Nationwide” and “Cooking genre” is “Non-genre”. Do. When the area designation is nationwide and the food genre is non-genre, all store information is searched. For example, when the area designation is Tokyo and the food genre is Italian, only the store information in the multiplied range is targeted. And the information provision part 11 produces | generates the screen information 100a by which the said "characteristic data" and the shop guidance information which guides the shop obtained by the search were shown, and the screen information 100a is shown to the user terminal 3. Send. Thereby, the screen information 100 a is displayed on the display unit of the user terminal 3.
　ここで、図４に例示した画面情報１００ａを説明すると、画面情報１００ａは、検索条件を受け付けるための検索指定領域１１０と、検索された飲食店を案内する店舗案内情報が提示された店舗案内領域１２０とを備えている。そして、検索指定領域１１０には、前記抽出された複数の特徴データ１１２を表示すると共に、その特徴データの指定を受け付けるための特徴データエリア１１１が設けられている。各特徴データを表示させる場合には、図４のように、特徴データを上下、強弱、優劣等を付けることなく表示することで、ユーザの潜在ニーズを特徴データとして具体化させることができる。また、検索指定領域１１０には、地域指定を受け付ける地域指定窓１１３と、料理ジャンルを受けるためのジャンル指定窓１１４と、ユーザが選んだ特徴データが提示される特徴データ表示領域１１５と、ユーザが選んだ特徴データの一括削除を受け付ける削除ボタン１１６とが設けられている。尚、特徴データエリア１１１に提示される特徴データ１１２は、その分類（図２、３参照）により、色分けされた上で提示されている。 Here, the screen information 100a illustrated in FIG. 4 will be described. The screen information 100a includes a search designation area 110 for accepting a search condition and a store guidance area where shop guidance information for guiding a searched restaurant is presented. 120. The search designation area 110 is provided with a feature data area 111 for displaying the plurality of extracted feature data 112 and receiving designation of the feature data. When displaying each feature data, as shown in FIG. 4, by displaying the feature data without adding up, down, strength, superiority or inferiority, the potential needs of the user can be embodied as the feature data. The search designation area 110 includes an area designation window 113 for accepting area designation, a genre designation window 114 for receiving a dish genre, a feature data display area 115 in which feature data selected by the user is presented, and a user A delete button 116 for accepting batch deletion of selected feature data is provided. The feature data 112 presented in the feature data area 111 is presented after being color-coded according to its classification (see FIGS. 2 and 3).
　また、店舗案内領域１２０には、各飲食店を紹介する簡単な説明と、飲食店の所在地や電話番号とを含む店舗案内情報が提示されるようになっている。また、店舗案内領域１２０には、店舗詳細情報の提示を受け付ける要求ボタン１２１、１２２が含まれており、ユーザ端末３から各飲食店の詳細情報の提示要求を受け付けることができるようになっている。そして、情報提供部１１は、ユーザ端末３からの要求ボタン１２１、１２２の選択を受け付けることにより、ユーザ端末３に対して、口コミ情報等の店舗詳細情報を送信する。 Further, in the store information area 120, store description information including a simple explanation for introducing each restaurant and the location and telephone number of the restaurant is presented. In addition, the store guidance area 120 includes request buttons 121 and 122 for accepting presentation of store detailed information, and a request for presenting detailed information of each restaurant can be accepted from the user terminal 3. . And the information provision part 11 transmits the shop detailed information, such as word-of-mouth information, with respect to the user terminal 3 by accepting selection of the request buttons 121 and 122 from the user terminal 3.
　また、画面情報１００ａを表示したユーザ端末３は、画面情報１００ａに提示された特徴データ１１２のうちのいずれかを選択したり、地域指定窓１１３に所望するエリアを入力したり、ジャンル指定窓１１４にジャンルを入力したりできるようになっている。例えば、ユーザ端末３は、画面情報１００ａ上において一の特徴データを選択すると、その選択した情報はサーバ群３の情報提供部１１に送信される。これにより、情報提供部１１は、ユーザ端末３が画面情報１００ａ上で指定した特徴データの選択を受け付ける。尚、ここでは、ユーザ端末３が特徴データとして「気軽に」を選択した場合を例にする。 In addition, the user terminal 3 displaying the screen information 100a selects any of the feature data 112 presented in the screen information 100a, inputs a desired area in the area designation window 113, or the genre designation window 114. You can enter the genre in For example, when the user terminal 3 selects one feature data on the screen information 100 a, the selected information is transmitted to the information providing unit 11 of the server group 3. Thereby, the information provision part 11 receives selection of the feature data which the user terminal 3 designated on the screen information 100a. Here, a case where the user terminal 3 selects “freely” as the feature data is taken as an example.
　次に、情報提供部１１は、前記特徴データの選択を受け付けると、その受け付けた特徴データ（説明の便宜上、「第１特徴データ」という）を検索条件として設定し、その設定した検索条件により店舗情報を検索する。また、情報提供部１１は、特徴データベース３０を用いて「第１特徴データ」と関連度が高い特徴データを複数抽出し、ユーザ端末３に対して、検索された店舗情報の店舗を案内する「店舗案内情報」と「第１特徴データと関連度が高い複数の特徴データ」とが含まれる画面情報（検索情報）１００ｂ（図５参照）を生成し、ユーザ端末３に送信する。これにより、ユーザ端末３の表示部には、画面情報１００ｂが表示される。 Next, when receiving the selection of the feature data, the information providing unit 11 sets the received feature data (referred to as “first feature data” for convenience of explanation) as a search condition, and stores the store according to the set search condition. Search for information. Further, the information providing unit 11 extracts a plurality of feature data having a high degree of association with the “first feature data” using the feature database 30, and guides the store of the searched store information to the user terminal 3. Screen information (search information) 100b (see FIG. 5) including “store guide information” and “a plurality of feature data highly related to the first feature data” is generated and transmitted to the user terminal 3. Thereby, the screen information 100 b is displayed on the display unit of the user terminal 3.
　ここで、上述した画面情報１００ａと、図５に例示した画面情報１００ｂとを比較すると、特徴データエリア１１１に表示される特徴データ１１２が、第１特徴データ（「気軽に」）と関連度が高いものに変更されている。また、特徴データ表示領域１１５には、検索条件として第１特徴データ（「気軽に」）が提示されている。また、店舗案内領域１２０には、第１特徴データ（「気軽に」）を検索条件にして、検索された店舗を案内する店舗案内情報が提示されている。 Here, when the screen information 100a described above and the screen information 100b illustrated in FIG. 5 are compared, the feature data 112 displayed in the feature data area 111 is related to the first feature data ("feel free"). It has been changed to a higher one. In the feature data display area 115, first feature data (“feel free”) is presented as a search condition. In the store guidance area 120, store guide information for guiding the searched store is presented using the first feature data (“feel free”) as a search condition.
　また、ユーザ端末３のユーザが検索を続ける場合、上記同様、画面情報１００ｂに提示された特徴データ１１２のいずれかを選択したり、地域指定窓１１３に所望するエリアを入力したり、ジャンル指定窓１１４にジャンルを入力したりすることで検索を続行できるようになっている。例えば、ユーザ端末３が、画面情報１００ｂ上の特徴データ１１２のなかから次の特徴データ（説明の便宜上「第２特徴データ」という）を選択したとすると、その選択した情報がサーバ群３の情報提供部１１に送信される。これにより、情報提供部１１は、ユーザ端末３が画面情報１００ａ上で指定した第２特徴データの選択を受け付ける。 Further, when the user of the user terminal 3 continues the search, as described above, any one of the feature data 112 presented in the screen information 100b is selected, a desired area is input to the area designation window 113, and a genre designation window is displayed. The search can be continued by inputting a genre in 114. For example, if the user terminal 3 selects the next feature data (referred to as “second feature data” for convenience of explanation) from the feature data 112 on the screen information 100b, the selected information is the information of the server group 3. It is transmitted to the providing unit 11. Thereby, the information provision part 11 receives selection of the 2nd feature data which the user terminal 3 designated on the screen information 100a.
　そして、情報提供部１１は、第２特徴データの選択を受け付けると、「第１特徴データ」及び「第２特徴データ」を検索条件に設定し、該設定した検索条件により店舗情報を検索する。また、情報提供部１１は、特徴データベース３０を用いて「第２特徴データ」と関連度が高い特徴データを複数抽出し、ユーザ端末３に対して、「検索された店舗を案内する店舗案内情報」と「第２特徴データと関連度が高い複数の特徴データ」とが含まれる画面情報（図示せず）を生成し、ユーザ端末３に送信する。これにより、ユーザ端末３の表示部には、新たな画面情報が表示される。尚、ユーザが、さらに検索を続ける場合には、新たな画面情報上で、上記同様の操作を行い、特徴データを選択していけばよい。 When the information providing unit 11 receives the selection of the second feature data, the information providing unit 11 sets “first feature data” and “second feature data” as search conditions, and searches store information based on the set search conditions. Further, the information providing unit 11 extracts a plurality of feature data having a high degree of relevance with the “second feature data” using the feature database 30, and sends the “store guide information for guiding the searched store” to the user terminal 3. ”And“ a plurality of feature data highly related to the second feature data ”are generated and transmitted to the user terminal 3. As a result, new screen information is displayed on the display unit of the user terminal 3. In addition, when the user continues to search further, the same operation as described above may be performed on the new screen information to select the feature data.
　このように、本実施形態では、特徴データ１１２をＮ個（Ｎは１以上の整数）選択できるようになっており、その選択されたＮ個の特徴データ１１２を検索条件にして飲食店検索を行うように構成されている。 As described above, in this embodiment, N feature data 112 (N is an integer of 1 or more) can be selected, and restaurant search is performed using the selected N feature data 112 as a search condition. Configured to do.
　また、本実施形態では、検索条件として複数の特徴データを選択できる構成となっているため、ユーザが選んだ特徴データの一括削除を受け付ける削除ボタン１１６を設けている。具体的には、情報提供部１１は、ユーザ端末３からの削除ボタン１１６の選択を受け付けると、検索条件として設定されている全特徴データを一括削除するようになっている。この構成によれば、ユーザが複数の特徴データを指定して、店舗情報を検索させた場合において、別の条件で検索したくなったような場合に、簡単な操作で、検索をやり直すことができる。 Further, in the present embodiment, since a plurality of feature data can be selected as a search condition, a delete button 116 that accepts batch deletion of feature data selected by the user is provided. Specifically, when receiving the selection of the delete button 116 from the user terminal 3, the information providing unit 11 collectively deletes all feature data set as a search condition. According to this configuration, when the user designates a plurality of feature data and searches for store information, when the user wants to search under different conditions, the search can be performed again with a simple operation. it can.
　尚、本実施形態では、上述した画面情報１００ａ、１００ｂ上において、地域指定窓１１３に所望するエリアの入力や、ジャンル指定窓１１４に所望するジャンルの入力を受け付けた場合、エリア毎や料理ジャンル毎の特徴データベース３０を利用して画面情報が生成されるようになる。すなわち、エリアやジャンルを絞った飲食店情報の検索が可能になる。 In the present embodiment, when an input of a desired area is received in the area specifying window 113 or an input of a desired genre is received in the genre specifying window 114 on the above-described screen information 100a and 100b, for each area or each cooking genre. Screen information is generated using the feature database 30. That is, restaurant information that narrows down the area and genre can be searched.
　このように、本実施形態によれば、ユーザ端末３のユーザが、サーバ群１により提供された複数の特徴データから、特徴データを選択した場合、選択した特徴データにより検索された店舗の情報と共に、選択した特徴データに類似している（関連度が高い）特徴データを参照することができるようになる。すなわち、本実施形態によれば、ユーザが店舗検索のキーワードを具体的に思い付かないような場合であっても、店舗を検索するための特徴データが選択可能に提示されているので、ユーザの漠然としたニーズを具体化させていくことができる。また、ユーザが興味を持った複数の特徴データにより、店舗情報を検索することができるため、潜在意識のなかでユーザの求めている店舗を検索する可能性が高められる。 As described above, according to the present embodiment, when the user of the user terminal 3 selects feature data from the plurality of feature data provided by the server group 1, together with the store information retrieved by the selected feature data. , It becomes possible to refer to feature data that is similar (highly related) to the selected feature data. That is, according to the present embodiment, even if the user does not come up with a store search keyword specifically, feature data for searching for a store is presented to be selectable. Can fulfill the needs. In addition, since the store information can be searched with a plurality of feature data that the user is interested in, the possibility of searching for the store that the user is seeking in the subconsciousness is increased.
　以上、説明したように本実施形態によれば、言葉やフレーズなどで具体的に特定できない情報や漠然としたニーズに対応する情報を検索することができるサーバ群１を提供することができる。なお、本発明は、上述した実施形態に限定されるものではなく、その要旨の範囲内において種々の変形が可能である。 As described above, according to the present embodiment, it is possible to provide the server group 1 that can search for information that cannot be specifically specified by words or phrases or information that corresponds to vague needs. In addition, this invention is not limited to embodiment mentioned above, A various deformation | transformation is possible within the range of the summary.
　例えば、上述した実施形態では、店舗情報が飲食店である場合を例にしているが、あくまでもこれは一例に過ぎない。飲食店以外の店舗情報にも本発明は適用される。
をまとまった形で提供することができる。 For example, in the above-described embodiment, the case where the store information is a restaurant is taken as an example, but this is only an example. The present invention is also applied to store information other than restaurants.
Can be provided in a unified form.

Claims (6)

  1. 　店舗情報を格納した店舗データベースと、
    　前記店舗情報から店舗の特徴を示す特徴データを抽出し、各特徴データの関連度を算出し該関連度に基づいて、複数の特徴データを網の目構造に関連付ける情報更新部と、
    　前記関連付けられた複数の特徴データを格納する特徴データベースと、
    　ユーザ端末からエリアと料理ジャンルの選択を受付け、該選択されたエリアと料理ジャンルとのかけ合わせを対象範囲として前記店舗情報を検索し、前記特徴データベースを用いて、該検索された店舗情報に含まれる特徴データのうち頻度が高い特徴データに関連付けられた複数の特徴データを抽出し、前記ユーザ端末に対して、前記抽出した複数の特徴データを提示し且つ該提示した特徴データの選択を受付ける画面情報を送信すると共に、該ユーザ端末から該画面情報上で指定した特徴データのうち１の選択を受付け、該受付けた特徴データを検索条件として設定し、該設定した検索条件により前記店舗情報を検索し、該ユーザ端末に該検索された店舗情報に基づいて、店舗を案内する店舗案内情報を作成し、
    さらに、前記特徴データベースを用いて該受け付けた特徴データと関連度が高い特徴データを複数新たに抽出し、該店舗案内情報と該新たに抽出した特徴データとを含む検索情報と、前記ユーザ端末から該検索情報上で新たに特徴データの選択を受け付ける画面情報とを送信する情報提供部とを有する
    　ことを特徴とする店舗情報検索システム。     A store database storing store information;
    Extracting feature data indicating the features of the store from the store information, calculating an association degree of each feature data, and based on the association degree, an information update unit associating a plurality of feature data with a network structure;
    A feature database storing a plurality of associated feature data;
    The selection of the area and the cooking genre is accepted from the user terminal, the store information is searched for the crossing of the selected area and the cooking genre, and included in the searched store information using the feature database. A plurality of feature data associated with high-frequency feature data among the feature data to be extracted, presenting the extracted plurality of feature data to the user terminal, and accepting selection of the presented feature data The information is transmitted, one of the feature data designated on the screen information is received from the user terminal, the received feature data is set as a search condition, and the store information is searched according to the set search condition. Then, based on the retrieved store information in the user terminal, create store guide information for guiding the store,
    Further, a plurality of feature data having a high degree of association with the received feature data are extracted using the feature database, search information including the store guidance information and the newly extracted feature data, and the user terminal A store information search system comprising: an information providing unit that transmits screen information for newly selecting feature data on the search information.
  2. 　前記検索情報には、前記検索条件として設定された特徴データが含まれていると共に、該検索条件の削除を受け付ける削除ボタンが含まれており、
    　前記情報提供部は、前記ユーザ端末からの前記削除ボタンの選択を受け付けると、既に設定されている検索条件を削除する
    　ことを特徴とする請求項１に記載の店舗情報検索システム。     The search information includes feature data set as the search condition, and includes a delete button for accepting deletion of the search condition,
    The store information search system according to claim 1, wherein the information providing unit deletes a search condition that has been set when receiving the selection of the delete button from the user terminal.
  3. 　前記店舗データベースに格納された店舗情報には、店舗の内容を詳細に提示している店舗詳細情報が含まれ、
    　前記店舗案内情報には、店舗詳細情報の提示を受け付ける要求ボタンが含まれており、
    　前記情報提供部は、前記ユーザ端末からの前記要求ボタンの選択を受け付けると、前記ユーザ端末に対して、前記店舗詳細情報を送信する
    　ことを特徴とする請求項１または請求項２に記載の店舗情報検索システム。     The store information stored in the store database includes store detail information presenting the details of the store in detail,
    The store guidance information includes a request button for accepting presentation of store detailed information,
    The store according to claim 1, wherein the information providing unit transmits the store detailed information to the user terminal when receiving the selection of the request button from the user terminal. Information retrieval system.
  4. 　前記情報更新部は、所定時間毎に、前記特徴データを網の目構造に関連付ける処理を行い、前記特徴データベースを更新する
    　ことを特徴とする請求項１から請求項３のいずれかに記載の店舗情報検索システム。     The store according to any one of claims 1 to 3, wherein the information update unit performs a process of associating the feature data with a network structure at predetermined time intervals and updates the feature database. Information retrieval system.
  5. 　店舗情報を格納した店舗データベースと、
    　前記店舗情報から店舗の特徴を示す特徴データを抽出し、各特徴データの関連度を算出し該関連度に基づいて、複数の特徴データを網の目構造に関連付ける情報更新部と、
    　前記関連付けられた複数の特徴データを格納する特徴データベースと、
    　ユーザ端末からエリアと料理ジャンルの選択を受付け、該選択されたエリアと料理ジャンルとのかけ合わせを対象範囲として前記店舗情報を検索し、前記特徴データベースを用いて、該検索された店舗情報に含まれる特徴データのうち頻度が高い特徴データに関連付けられた複数の特徴データを抽出し、前記ユーザ端末に対して、前記抽出した複数の特徴データを提示し且つ該提示した特徴データの選択を受付ける画面情報を送信すると共に、該ユーザ端末から該画面情報上で指定した特徴データのうち１の選択を受付け、該受付けた特徴データを検索条件として設定し、該設定した検索条件により前記店舗情報を検索し、該ユーザ端末に該検索された店舗情報に基づいて、店舗を案内する店舗案内情報を作成し、
    さらに、前記特徴データベースを用いて該受け付けた特徴データと関連度が高い特徴データを複数新たに抽出し、該店舗案内情報と該新たに抽出した特徴データとを含む検索情報と、前記ユーザ端末から該検索情報上で新たに特徴データの選択を受け付ける画面情報とを送信する情報提供部とを有する
    　ことを特徴とする店舗情報検索コンピュータ。     A store database storing store information;
    Extracting feature data indicating the features of the store from the store information, calculating an association degree of each feature data, and based on the association degree, an information update unit associating a plurality of feature data with a network structure;
    A feature database storing a plurality of associated feature data;
    The selection of the area and the cooking genre is accepted from the user terminal, the store information is searched for the crossing of the selected area and the cooking genre, and included in the searched store information using the feature database. A plurality of feature data associated with high-frequency feature data among the feature data to be extracted, presenting the extracted plurality of feature data to the user terminal, and accepting selection of the presented feature data The information is transmitted, one of the feature data designated on the screen information is received from the user terminal, the received feature data is set as a search condition, and the store information is searched according to the set search condition. Then, based on the retrieved store information in the user terminal, create store guide information for guiding the store,
    Further, a plurality of feature data having a high degree of association with the received feature data are extracted using the feature database, search information including the store guidance information and the newly extracted feature data, and the user terminal A store information search computer, comprising: an information providing unit that transmits screen information for newly selecting selection of feature data on the search information.
  6. 　コンピュータにおける店舗情報検索の処理方法であって、
    　前記コンピュータは、
    　店舗情報を格納した店舗データベースと、
    　関連づけられた複数の特徴データを格納する特徴データベースと、を備えており、
    　前記店舗情報から店舗の特徴を示す特徴データを抽出して各特徴データの関連度を算出し、
    　算出した関連度に基づいて、複数の特徴データを網の目構造に関連付けて前記特徴データベースに格納し、
    　ユーザ端末からエリアと料理ジャンルの選択を受付け、
    　該選択されたエリアと料理ジャンルとのかけ合わせを対象範囲として前記店舗情報を検索し、
    　前記特徴データベースを用いて、該検索された店舗情報に含まれる特徴データのうち頻度が高い特徴データに関連付けられた複数の特徴データを抽出し、
    　前記ユーザ端末に対して、前記抽出した複数の特徴データを提示し且つ該提示した特徴データの選択を受付ける画面情報を送信すると共に、該ユーザ端末から該画面情報上で指定した特徴データのうち１の選択を受付け、
    　該受付けた特徴データを検索条件として設定し、
    　該設定した検索条件により前記店舗情報を検索し、
    　該ユーザ端末に該検索された店舗情報に基づいて、店舗を案内する店舗案内情報を作成し、
    　前記特徴データベースを用いて該受け付けた特徴データと関連度が高い特徴データを複数新たに抽出し、
    　該店舗案内情報と該新たに抽出した特徴データとを含む検索情報と、前記ユーザ端末から該検索情報上で新たに特徴データの選択を受け付ける画面情報とを送信する、
    　ことを特徴とするコンピュータにおける店舗情報検索の処理方法。     A method of processing store information retrieval on a computer,
    The computer
    A store database storing store information;
    A feature database that stores a plurality of associated feature data;
    Extracting feature data indicating the features of the store from the store information and calculating the relevance of each feature data,
    Based on the calculated degree of association, a plurality of feature data is stored in the feature database in association with the network structure,
    Accept selection of area and food genre from user terminal,
    The store information is searched for the range of the selected area and the food genre as a target range,
    Using the feature database, extract a plurality of feature data associated with feature data having a high frequency among feature data included in the searched store information,
    Displaying the plurality of extracted feature data to the user terminal and transmitting screen information for accepting selection of the presented feature data, and one of the feature data designated on the screen information from the user terminal Accept the selection of
    The received feature data is set as a search condition,
    Search the store information according to the set search condition,
    Based on the searched store information in the user terminal, store information for guiding the store is created,
    A plurality of feature data having a high degree of association with the received feature data are extracted using the feature database,
    Search information including the store guidance information and the newly extracted feature data, and screen information for newly selecting feature data on the search information from the user terminal,
    A method for processing store information search in a computer.
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