JP2007193427A - Evaluation information management system, evaluation information management program and evaluation information management method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an evaluation information management system, an evaluation information management program and an evaluation information management method for providing information on which the features of each contributor are strongly reflected to a user. <P>SOLUTION: An information storage server 50 stores mouth-to-mouth information for a restaurant contributed by a contributor, and an information summarization server 60 generates information relating to evaluation ranking by ranking restaurants corresponding to a predetermined region (favorite region) registered by the contributor and/or a predetermined genre (favorite genre) of the restaurants registered by the contributor based on mouth-to-mouth information stored in the information storage server 50. Thus, the information, on which the feature of each contributor is strongly reflected, is provided to a user. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an evaluation information management system, an evaluation information management program, and an evaluation information management method for managing evaluation information posted by a contributor to an evaluation target, and in particular, the characteristics of each contributor are more strongly reflected. The present invention relates to an evaluation information management system, an evaluation information management program, and an evaluation information management method that can provide information to a user.

  2. Description of the Related Art Conventionally, an electronic bulletin board service that publishes information provided by users on the Internet has been used. For example, an electronic bulletin board service is provided in which various users evaluate restaurants and display the ranking of restaurants in descending order of evaluation.

  Furthermore, in such information exchange between users, an information providing system that ensures the accuracy, popularity, and freshness of information has been devised (see, for example, Patent Document 1). Specifically, in this information providing system, when the information posted by the user is incorrect, the information correction by the user is accepted.

  In addition, the user can vote for the evaluation on the posted information. This voting data is deleted after a predetermined period in order to keep information fresh. When there is an information browsing request from the user, the evaluations made on the posted information are totaled, and the rankings of the posted information are displayed in descending order of evaluation.

  Here, the user can register in advance the area of information to be obtained. And when ranking display of the posted information is performed, votes corresponding to the area are tabulated and ranking display of the posted information is performed in descending order of evaluation.

JP 2005-157495 A

  However, in the prior art represented by the above-mentioned Patent Document 1, information ranking is performed based on evaluations made by various users on information, so that the poster has absolute confidence in the information. Even if they had, there was a problem that their confidence was not easily reflected in the ranking.

  For example, some contributors may have very detailed information about restaurants in a certain region or a certain genre of dishes, but such a contributor is not always required when creating rankings based on other users ’ratings. The characteristics of may not be reflected in the ranking.

  Therefore, there is a problem of how to realize an information providing service that can provide information that more strongly reflects the characteristics of each poster.

  The present invention has been made in order to solve the above-described problems caused by the prior art, and an evaluation information management system and evaluation information management capable of providing a user with information that more strongly reflects the characteristics of each contributor. An object is to provide a program and an evaluation information management method.

  In order to solve the above-described problems and achieve the object, the present invention is an evaluation information management system for managing evaluation information posted by a contributor to an evaluation target, and the evaluation posted by the contributor Storage means for storing evaluation information for an object, and a predetermined region registered by the contributor and / or a predetermined genre of evaluation object registered by the contributor based on the evaluation information stored by the storage means And generating means for generating information related to the evaluation ranking in which the evaluation objects corresponding to the above are ranked.

  Further, the present invention, in the above invention, further comprises a post history information generating means for generating information related to a post history in which the contributor posted the evaluation information based on the evaluation information stored by the storage means. It is characterized by.

  Also, the present invention is characterized in that, in the above-mentioned invention, the information related to the posting history is information related to a distribution of a genre to be evaluated in which evaluation information is posted by a poster.

  Further, the present invention provides an evaluation object corresponding to an area for which designation is received by the area designation receiving unit based on the evaluation information stored in the storage unit and a region designation receiving unit for receiving the designation of the region in the above invention. It further comprises evaluation target ranking information generating means for generating information related to the evaluation ranking ranked.

  Further, the present invention provides the distribution information generation for generating information related to the distribution of each evaluation subject's age and / or gender based on the evaluation information stored in the storage means in the above invention. The apparatus further includes means.

  Further, according to the present invention, in the above-described invention, the evaluation receiving unit that receives the evaluation made on the evaluation information stored by the storage unit, and the posters are ranked based on the evaluation received by the evaluation receiving unit. Evaluation ranking information generating means for generating information related to the evaluation ranking is further provided.

  Further, the present invention provides the evaluation history information generating means for generating information related to a history of evaluations made to the poster within a predetermined period based on the evaluation received by the evaluation receiving means in the above invention. Is further provided.

  Further, according to the present invention, in the above invention, the number of evaluation information stored in the storage unit is calculated for each contributor, and the total number of evaluation information is calculated based on the totaled result obtained by the evaluation information number totaling unit. Evaluation information number ranking information generating means for generating information related to an evaluation ranking in which posters are ranked is further provided.

  Further, in the present invention, the present invention provides the post for generating information related to the history of the number of times the contributor posted the evaluation information within a predetermined period based on the aggregation result totaled by the evaluation information number aggregation unit. It further comprises number history information generating means.

  Further, according to the present invention, in the above invention, the number of browsing of the evaluation information stored in the storage unit is counted for each contributor who posted the evaluation information, and the number of totals counted by the number of browsing counts It is characterized by further comprising browsing number ranking information generating means for generating information related to the evaluation ranking in which the poster is ranked based on the result.

  Further, in the above invention, the present invention generates information related to the history of the number of evaluation information posted by the contributor viewed within a predetermined period based on the result obtained by the browsing number counting means. A browsing number history information generating means is further provided.

  The present invention also relates to an evaluation information management program for managing evaluation information posted by a contributor to an evaluation object, and a storage means for storing evaluation information for the evaluation object posted by the contributor. Based on the evaluation information stored by the storage means, the evaluation target ranked by the predetermined region registered by the contributor and / or the predetermined genre of the evaluation target registered by the contributor It is made to function as a production | generation means which produces | generates the information which concerns on ranking.

  Further, the present invention is the above-described invention, wherein the computer is further provided as posting history information generating means for generating information related to a posting history in which the contributor posted the evaluation information based on the evaluation information stored by the storage means. It is made to function.

  Also, the present invention is characterized in that, in the above-mentioned invention, the information related to the posting history is information related to a distribution of a genre to be evaluated in which evaluation information is posted by a poster.

  Further, according to the present invention, in the above-described invention, the computer corresponds to the area where the designation is accepted by the area designation accepting means based on the evaluation information stored in the area designation accepting means for accepting designation of the area. It is further made to function as an evaluation object ranking information generating means for generating information related to an evaluation ranking in which evaluation objects to be ranked are ranked.

  Further, according to the present invention, in the above-described invention, the computer generates information related to the distribution of each age and / or sex of the poster of the evaluation information for each evaluation object based on the evaluation information stored by the storage unit. It further functions as distribution information generation means.

  Further, according to the present invention, in the above invention, the computer ranks the poster based on the evaluation received by the evaluation receiving means, the evaluation receiving means for receiving the evaluation made on the evaluation information stored by the storage means. It is further made to function as an evaluation ranking information generating means for generating information related to the attached evaluation ranking.

  Further, the present invention provides the evaluation history in which the computer generates information related to the history of evaluation made to the poster within a predetermined period based on the evaluation received by the evaluation receiving means in the above invention. It further functions as an information generating means.

  Further, the present invention provides the computer according to the above-mentioned invention, in which the computer counts the number of evaluation information stored by the storage unit for each poster, and the total result obtained by the evaluation information number totaling unit. It is further characterized by functioning as evaluation information number ranking information generating means for generating information related to an evaluation ranking in which posters are ranked.

  Further, according to the present invention, in the above invention, the computer is configured to obtain information relating to a history of the number of postings of the evaluation information by the contributor within a predetermined period based on the counting results totaled by the evaluation information number counting means. It functions as a post number history information generating means for generating.

  Further, according to the present invention, in the above invention, the computer counts the browsing number of the evaluation information stored in the storage unit for each contributor who posted the evaluation information, and the browsing number counting unit It is further made to function as browsing number ranking information generation means for generating information related to the evaluation ranking obtained by ranking the posters based on the tabulated results.

  Further, according to the present invention, in the above-described invention, information relating to a history of the number of times the evaluation information posted by the contributor has been viewed within a predetermined period of time based on a result obtained by counting the computer by the browsing number counting means It is further characterized by functioning as browsing number history information generating means for generating.

  Further, the present invention is an evaluation information management method for managing evaluation information posted by a contributor to an evaluation object, the storage step storing the evaluation information for the evaluation object posted by the contributor, Based on the evaluation information stored in the storing step, the evaluation ranking is based on the evaluation target corresponding to the predetermined region registered by the contributor and / or the predetermined genre of the evaluation target registered by the contributor. And a generating step for generating such information.

  Moreover, the present invention is characterized in that, in the above-mentioned invention, the information related to the evaluation of the evaluation object includes at least information related to the evaluation ranking in which the evaluation object is ranked.

  In the present invention, the attribute common to the contributor includes at least a region registered by the contributor and / or an evaluation target genre registered by the contributor.

  Further, according to the present invention, in the above invention, in addition to generating the evaluation ranking, the generation step includes a posting history in which the contributor posts evaluation information based on the evaluation information stored in the storage step. Such information is generated.

  Also, the present invention is characterized in that, in the above-mentioned invention, the information related to the posting history is information related to a distribution of a genre to be evaluated in which evaluation information is posted by a poster.

  Further, the present invention is the above invention, wherein the generating step accepts designation of a region in addition to generating the evaluation ranking, and accepts designation based on the evaluation information stored in the storing step. And generating information related to the evaluation ranking in which the evaluation objects corresponding to are ranked.

  Further, the present invention is the above invention, wherein in the generation step, in addition to generating the evaluation ranking, based on the evaluation information stored in the storage step, the age of the poster of the evaluation information for each evaluation object And / or generating information on the distribution for each gender.

  Further, in the present invention, in the above invention, in addition to generating the evaluation ranking, the generation step receives an evaluation made on the evaluation information stored by the storage step, and based on the received evaluation And generating information related to the evaluation ranking of the poster.

  Also, in the present invention according to the present invention, the generation step generates information related to a history of evaluations made to the poster within a predetermined period based on evaluations made on the evaluation information. It is characterized by that.

  Further, in the present invention, in the above invention, in addition to generating the evaluation ranking, the generation step totals the number of evaluation information stored by the storage step for each contributor, and based on the totalization result It is characterized by generating information related to an evaluation ranking in which a poster is ranked.

  Moreover, the present invention is characterized in that, in the above invention, the generating step generates information related to a history of the number of postings of the evaluation information by the contributor within a predetermined period based on the aggregation result. .

  Further, in the present invention, in the above invention, in addition to generating the evaluation ranking, the generation step totals the number of browsing of the evaluation information stored in the storage step for each contributor who posted the evaluation information. And generating information related to the evaluation ranking in which the posters are ranked based on the counting result.

  Moreover, the present invention is the above invention, wherein the generating step generates information related to the number of histories of the evaluation information posted by the contributor viewed within a predetermined period based on the aggregation result. Features.

  According to the present invention, evaluation information for an evaluation object posted by a contributor is stored, and based on the stored evaluation information, a predetermined region registered by the contributor and / or an evaluation object registered by the contributor is stored. Since the information related to the evaluation ranking that ranks the evaluation target corresponding to the predetermined genre is generated, it corresponds to the region and genre that each poster is good at, and the characteristics of each poster are reflected more strongly. The information can be provided to the user in a ranking format that is easy for the user to view, and the reliability of the information can be improved.

  In addition, according to the present invention, based on the stored evaluation information, since it is decided to generate information related to the posting history that the poster posted the evaluation information, the past posting tendency of the poster can be examined, There is an effect that the reliability of the information posted by the poster can be easily confirmed.

  Further, according to the present invention, the information related to the posting history is information related to the distribution of the genre of the evaluation target for which the evaluation information is posted by the poster. It is possible to check whether the information has been posted to the genre, and the reliability of the information posted by the poster can be easily confirmed.

  In addition, according to the present invention, since the designation of the area is accepted and the information related to the evaluation ranking in which the evaluation object corresponding to the area for which the designation is accepted is ranked is generated based on the stored evaluation information, It has the effect that it is possible to easily examine evaluation objects with high evaluation in an area where it is desired to obtain the evaluation.

  In addition, according to the present invention, based on the stored evaluation information, information related to the age and / or distribution of each gender of the evaluation information for each evaluation object is generated. It is possible to easily check whether the contributor of sex has posted the evaluation information and analyze the evaluation result.

  In addition, according to the present invention, since the evaluation made for the stored evaluation information is accepted and the information related to the evaluation ranking in which the poster is ranked based on the received evaluation is generated, the author can be trusted. There is an effect that can be easily checked.

  In addition, according to the present invention, based on the received evaluation, information related to the history of evaluation made for the poster within a predetermined period is generated, so that the transition of the evaluation for the poster can be easily performed. It is possible to check, and there is an effect that a reliable poster can be checked accurately.

  Further, according to the present invention, the number of stored evaluation information is aggregated for each contributor, and information related to the evaluation ranking in which the contributors are ranked based on the aggregated aggregated result is generated. There is a large number of posts, and it is possible to easily check a reliable poster.

  Further, according to the present invention, based on the totaled results, the information related to the history of the number of contribution information posted by the contributor within a predetermined period is generated. It is possible to easily check the transition of the information, and it is possible to accurately check a reliable poster.

  Further, according to the present invention, the number of views of the stored evaluation information is aggregated for each contributor who posted the evaluation information, and information related to the evaluation ranking in which the contributors are ranked based on the aggregated result is generated. As a result, the number of evaluation information viewed is large, and it is possible to easily check reliable posters.

  According to the present invention, since the evaluation information posted by the poster is generated based on the counting result, the information related to the number of histories browsed within a predetermined period is generated. It is possible to easily check the transition of the number of browsing, and it is possible to accurately check a reliable poster.

  Exemplary embodiments of an evaluation information management system, an evaluation information management program, and an evaluation information management method according to the present invention will be described below in detail with reference to the accompanying drawings. Here, the case where the evaluation target of the evaluation information to be managed is a restaurant will be described as an example. However, the evaluation target is not limited to this, and the present invention is similarly applied to other evaluation targets. Can be applied.

  First, the configuration of the information providing system according to the present embodiment will be described. FIG. 1 is a diagram illustrating the configuration of the information providing system 20 according to the present embodiment. The information providing system 20 shown in FIG. 1 is a system that accepts restaurant evaluation information from a user as word-of-mouth information and opens the accepted word-of-mouth information to other users.

  This posting information aggregation system 20 not only discloses word-of-mouth information, but also accepts registration of specialty areas and genres from each poster, and each poster submits to restaurants corresponding to his / her favorite areas and genres. By collecting the word-of-mouth information posted for each good region and good genre common to each contributor, information related to an evaluation ranking for each region and genre ranking restaurants is generated.

  For example, if there are a plurality of contributors whose specialty area is “Roppongi”, the word-of-mouth information posted to restaurants in the “Roppongi” area by such posters is aggregated, and based on the aggregation results Information related to an evaluation ranking in which restaurants in the “Roppongi” area are ranked is generated.

  Thereby, highly reliable restaurant information corresponding to each poster's specialty area and specialty genre can be provided in a ranking format that is easy for the user to view, and the convenience of the information providing service can be enhanced.

  As shown in FIG. 1, the information providing system 20 is connected to user terminals 10a to 10c via a network 30 (Internet, public line network, etc.). The user terminals 10a to 10c are information terminals such as personal computers and mobile phones.

  The user operates the user terminals 10a to 10c to connect to the information providing system 20, and browses word-of-mouth information and various ranking information, posts word-of-mouth information, and evaluates word-of-mouth information posted by other users.

  Further, the user terminals 10a to 10c are provided with a GPS (Global Positioning System) function for detecting the current position of the user. The user terminals 10a to 10c receive the restaurant information of the area corresponding to the current position from the information providing system 20 by transmitting information on the current position of the user detected using the GPS function to the information providing system 20. .

  The information providing system 20 is configured by connecting an information providing server 40, an information storage server 50, and an information totaling server 60 via a network 70 (LAN or the like).

  The information providing server 40 is a server that outputs requested information to the user terminals 10a to 10c when receiving output requests for various information such as word-of-mouth information from the user terminals 10a to 10c. The information providing server 40 includes a communication processing unit 41, a storage unit 42, an information providing processing unit 43, and a control unit 44.

  The communication processing unit 41 is a network interface that communicates with the user terminals 10 a to 10 c via the network 30 or with the information storage server 50 and the information totaling server 60 via the network 70.

  The storage unit 42 is a storage device such as a hard disk device. The storage unit 42 stores content data 42a and user data 42b.

  The content data 42a is information acquired from the information storage server 50 when the information providing server 40 acquires information from the information storage server 50 and provides the user terminals 10a to 10c with various screens to be output to the user terminals 10a to 10c. Is content data for embedding and configuring. The user data 42b is data that stores a user ID, a password, and the like of a user who logs in to the information providing service.

  The information provision processing unit 43 performs login management of a user who uses this information provision service, and when receiving an output request for information such as word-of-mouth information from the user terminals 10a to 10c, the information provision processing unit 43 sends the requested information to the user terminal 10a. To 10c.

  Specifically, the information provision processing unit 43 corresponds to the region input by the user using the user terminals 10a to 10c or the current position of the user detected by the GPS function provided in the user terminals 10a to 10c. The output request of the restaurant information of the area to receive is received.

  FIG. 2 is a diagram illustrating an example of a top screen 100 that receives a restaurant information output request. The top screen 100 includes a search reception area 101, a region designation reception area 102, and a poster ranking display request reception area 103.

  The search reception area 101 is a reception area for receiving search conditions for narrowing down restaurants such as keywords and regions, genres, budgets, atmospheres, and coupons. The keyword is a keyword when a search is performed on restaurant information. The area is an area where restaurants are located. The genre is a genre of cuisine of restaurants such as Japanese, Western and Chinese. The budget is the budget amount for cooking. The atmosphere is suitable for shops such as dates and banquets. A coupon designates the presence or absence of a coupon.

  The user can search for restaurant information by specifying such information and clicking search button 104 with a mouse or the like. In addition, when detecting a user's present location using the GPS function of user terminal 10a-10c, the search of the restaurant information of the area corresponding to a current position is performed without designation | designated of an area.

  The area designation receiving area 102 is a receiving area for receiving area designation by clicking with a mouse or the like when narrowing down shops. The contributor ranking display request receiving area 103 is a receiving area for receiving a contributor ranking display request described later from the user. The user can display the poster ranking on the user terminals 10a to 10c by clicking the display button 105 with a mouse or the like.

  Here, the contributor ranking is a ranking in which the evaluation results evaluated by other users with respect to the word-of-mouth information posted by the contributor are aggregated and the contributors are ranked in descending order of evaluation.

  When such a top screen 100 receives a restaurant information search request including a region and other narrowing conditions, the information provision processing unit 43 is transmitted to the information storage server 50 by the user terminals 10a to 10c. The restaurant information corresponding to the narrowing-down condition is requested to be transmitted.

  And the information provision process part 43 receives the restaurant information transmitted by the information storage server 50, and outputs the received restaurant information to the user terminals 10a-10c. This restaurant information includes information on restaurant rankings in which the restaurant information is arranged in the order of restaurants with the highest evaluation in the word-of-mouth information posted by each contributor on the area he / she is good at.

  In addition, here, in the review information posted by each contributor about the area he is good at, the restaurant ranking information in which the restaurant information is arranged in the order of the restaurant with the highest evaluation is output. It is good also as outputting the information of the restaurant ranking in which the restaurant information was arranged in the order of the restaurant with the highest evaluation in the review information posted by the poster about the genre of the restaurant that he is good at.

  FIG. 3 is a diagram illustrating an example of the regional restaurant ranking output screen 110. In the example of FIG. 3, the restaurant ranking 111 corresponding to the area “Roppongi” designated from the user terminals 10a to 10c is shown. This restaurant ranking 111 includes store name [genre], region, point, and evaluation information.

  The store name [genre] is information on the restaurant name and genre of the restaurant. A hyperlink is set in this item, and detailed word-of-mouth information of the store can be output by clicking the store name [genre] with a mouse or the like. This word-of-mouth information will be described in detail later.

  The region is information on a region corresponding to each restaurant, and is information on a region designated by the user terminals 10a to 10c. The point is word-of-mouth information most supported by the user among the word-of-mouth information posted. Evaluation is information of the average value of the evaluation of the restaurant evaluated in five steps by the contributor of the word-of-mouth information. Information of each restaurant is arranged in order of increasing average value.

  Moreover, the information provision process part 43 performs the process which further narrows down the restaurant information output to the restaurant ranking 111 as well as the area. In the example of FIG. 3, a narrowing condition 112 (genre, budget, atmosphere, coupon) for narrowing down restaurant information is output.

  In this case, when the information provision processing unit 43 receives the information of the narrowing-down condition 112 specified by the user clicking with the mouse or the like from the user terminals 10 a to 10 c, the information providing processing unit 43 sends the user terminals 10 a to 10 c to the information storage server 50. In addition to the information on the area transmitted by, the information on the restaurant ranking 111 corresponding to the filtering condition 112 is further requested.

  And the information provision process part 43 receives the information of the restaurant ranking 111 transmitted by the information storage server 50, and outputs the received information to user terminal 10a-10c.

  As described with reference to FIG. 3, when a store name [genre] in which a hyperlink is set is clicked with a mouse or the like, detailed word-of-mouth information about the restaurant is output. FIG. 4 is a diagram illustrating an example of the word-of-mouth information output screen 120.

  This review information output screen 120 includes basic information 121, latest review information 122, useful review information 123, evaluation distribution 124, budget distribution 125, atmosphere distribution 126, and gender / generation information 127.

  The basic information 121 is basic information on restaurants. Specifically, the basic information 121 includes information on word-of-mouth, average budget, transportation, address, telephone, and atmosphere. The word-of-mouth communication is information on the average value of restaurants evaluated in five stages by the word-of-mouth information contributor and the number of word-of-mouth information posted (number of reviews).

  The average budget is information on the average value of the budget amount of the restaurant registered by the reviewer. The transportation means is information on transportation means that is most convenient for going to restaurants. The address and telephone are information on the restaurant address and telephone number. The atmosphere is information on the atmosphere of the restaurant most frequently registered by the poster.

  The latest review information 122 is the latest review information among the review information posted by the contributor. Moreover, the useful word-of-mouth information 123 is information (for example, top ten word-of-mouth information etc.) with high evaluation among word-of-mouth information evaluated as useful by users other than the poster.

  In addition, when viewing all the word-of-mouth information regarding this restaurant, all the word-of-mouth information is displayed by clicking on a character string with a hyperlink “view all word of mouth” set with a mouse or the like.

  The evaluation of the review information is the latest review information 122, the helpful review information 123, or the evaluation buttons 128a to 128d provided in the display area of each review information when all the review information is displayed (“Is this review helpful?” This is done by counting the number of times the “Yes” button or “No” button) corresponding to “?” Is clicked with the mouse or the like.

  Specifically, when the evaluation buttons 128 a to 128 d are clicked with a mouse or the like, the information provision processing unit 43 transmits the information to the information storage server 50. The information storage server 50 that has received this information counts the number of times the evaluation buttons 128a to 128d ("Yes" button or "No" button) are clicked with a mouse or the like in association with each piece of word-of-mouth information. Store information.

  The evaluation distribution 124 is information on the distribution of evaluation for this restaurant registered by the contributor of the word-of-mouth information. The budget distribution 125 is information on the budget amount distribution of the restaurant registered by the contributor of the review information. The atmosphere distribution 125 is information on the distribution of the atmosphere of this restaurant registered by the contributor of the review information. The gender / generation information 127 is information on the distribution of the gender / generation of the poster who posted the word-of-mouth information to this restaurant.

  By the way, the restaurant ranking 111 on the regional restaurant ranking output screen 110 shown in FIG. 3 and the basic information 121 on the word-of-mouth information output screen 120 are hyperlinks for shifting to a posting acceptance screen that accepts posting of word-of-mouth information. A character string “register word-of-mouth information” is set.

  A user who posts word-of-mouth information can click the character string with a mouse or the like to output a posting acceptance screen and make a posting. FIG. 5 is a diagram illustrating an example of the posting acceptance screen 130.

  This posting acceptance screen 130 includes basic information 131, an evaluation distribution 132, and a posting acceptance area 133. The basic information 131 is basic information on restaurants. Specifically, the basic information 131 includes information on the number of reviews, five stars, reviews, addresses, telephones, and atmosphere.

  The word-of-mouth ranking is the ranking of restaurants counted from the number of reviews when each restaurant is arranged in descending order of the number of reviews. The five-star ranking is a ranking of restaurants counted from the one with the largest number of five stars when the restaurants are arranged in the order of the number of five stars.

  The word-of-mouth communication is information on the average value of restaurants evaluated in five stages by the word-of-mouth information contributor and the number of word-of-mouth information posted (number of reviews). The address and telephone are information on the restaurant address and telephone number. The atmosphere is information on the atmosphere of the restaurant most frequently registered by the poster.

  The evaluation distribution 132 is information on a five-level evaluation distribution made by a contributor to the word-of-mouth information for this restaurant.

  The posting reception area 133 is a reception area for receiving word-of-mouth information from the user. As word-of-mouth information, scoring (stars: 5, 4, 3, 2, 1), scene (dinner, lunch, etc.), amount per person (Less than 1,000 yen, 1,000-2,999 yen, 3,000-4,999 yen, 5,000-6,999 yen, 7,000-9,999 yen, 10,000 yen or more ), Store atmosphere (dates, entertainment, banquets, parties, joint parties, families, even one person, small groups), word of mouth, and word of mouth content.

  When the posting button 134 is clicked with a mouse or the like, the input information is transmitted to the information storage server 50, and the information storage server 50 stores the information.

  In addition, the user's nicknames (“Mr. XXXX” and “Mr. YYYY”) of the latest review information 122 and useful review information 123 on the review information output screen 120 shown in FIG. A hyperlink to the information is set.

  Then, when those nicknames are clicked with the mouse or the like in the user terminals 10a to 10c, the information provision processing unit 43 requests the information storage server 50 to transmit the information of the posting history of the poster, and has received the result. Posting history information is output to the user terminals 10a to 10c.

  FIG. 6 is a diagram showing an example of the contributor review post history output screen 140 output in this way. The contributor's word-of-mouth contribution log output screen 140 includes information on the number of word-of-mouth contributions, the number of support points, and the tendency of word-of-mouth.

  The number of review posts is information on the total number of review information posted by the contributor and the ranking of the contributors counted from the largest number of review posts when each contributor is arranged in descending order of the number of review posts. The support score is an index serving as a measure for measuring the degree of support of the poster by other users, and is a number obtained by subtracting the non-support number from the support number.

  Here, the number of support is the number that the reviewer's word-of-mouth information has been evaluated as useful by other users using the evaluation buttons 128a and 128c as shown in FIG. The number of disapprovals is the number that the word-of-mouth information of the contributor is evaluated as being useless by other users using the evaluation buttons 128b and 128d as shown in FIG.

  The word-of-mouth tendency includes evaluation distribution, budget, and genre information. The distribution of evaluation is information on the distribution of the evaluation of restaurants in five stages in the word-of-mouth information posted by the poster in the past. The budget is information on the distribution of restaurant budget amounts in the word-of-mouth information posted by the poster in the past. The genre is information on the distribution of genres of restaurants in the review information posted by the poster in the past.

  Further, when the display button 105 of the poster ranking display request reception area 103 is clicked with the mouse or the like on the top screen 100 shown in FIG. It requests to send information on contributor ranking.

  And the information provision process part 43 receives the information of the contributor ranking transmitted by the information storage server 50, and outputs the received information to the user terminals 10a to 10c. FIG. 7 is a diagram showing an example of the poster ranking output screen 150 output in this way. The contributor ranking output screen 150 includes information on rank, nickname, number of reviews posted, number of support points, and support rate.

  The ranking is the ranking when the posters are ranked in descending order of evaluation. Specifically, the ranking is made in descending order of the numerical value obtained by multiplying the number of contributions of the word-of-mouth information by the support rate. When these numbers are the same, a poster who has a large number of support points is regarded as a top poster. Further, when the support points are also the same, those contributors are assigned the same rank, and the contributors are displayed in alphabetical order using a contributor ID described later.

  In this example, the ranking is based on the number of reviews posted by the number of contributions multiplied by the support rate. However, the ranking of posters is ranked in descending order of the total number of reviews posted by the poster. Also good. Further, the ranking of the posters may be performed in descending order of the number of times the review information posted by the poster is viewed.

  The nickname is a nickname used when a poster posts word-of-mouth information. The number of reviews posted is the number of reviews posted by the poster in the past. The support score is an index serving as a measure for measuring the degree of support of the poster by other users, and is a number obtained by subtracting the non-support number from the support number. Like the support score, the support rate is an index that measures the degree to which each contributor is supported by other users, and the support number accounts for the total number of support and non-support. It is a ratio.

  In addition, in addition to the nickname of the poster, status icons 151a to 151d are output in the area for displaying the nickname. The status icons 151a to 151d are symbols (icons) expressed so that the evaluation content of the contributor of the word-of-mouth information can be understood at a glance.

  Specifically, the colors of the status icons 151a to 151d change depending on the support rate, and the numerical values shown in the status icons 151a to 151d change depending on the number of reviews posted. The color of the status icons 151a to 151d and the method of determining the numerical values shown in the status icons 151a to 151d will be described in detail later using FIG.

  In addition to numerical values, upward, horizontal, and downward arrows are displayed in the status icons 151a to 151d. The direction of this arrow indicates whether the current support rate has increased by more than a predetermined value (for example, 1% or more) compared to the support rate at a predetermined time in the past (for example, one week ago), or Indicates whether the increase or decrease in the support rate is within a predetermined range (for example, within a range of plus or minus 1%), or whether the current support rate has decreased by a predetermined value or more (for example, 1% or more) Yes.

  FIG. 8 is a diagram illustrating arrows indicating the change in the support rate of the status icons 160a to 160c.

  The status icon 160a is an example in which the current support rate has increased by a predetermined value or more compared to the support rate at a predetermined time in the past, and the arrow is pointing upward. The status icon 160b is an example in the case where the increase or decrease amount of the support rate at the present time from the support rate at a predetermined time in the past is within a predetermined range, and the arrow is horizontally oriented. The status icon 160c is an example of a case where the current support rate has dropped by a predetermined value or more compared to the support rate at a predetermined past time point, and the arrow is pointing downward.

  In addition, when the status icons 151a to 151d illustrated in FIG. 7 are clicked with a mouse or the like, the information provision processing unit 43 outputs the history information of the poster's support rate. Specifically, when the status icons 151a to 151d are clicked with a mouse or the like, the information provision processing unit 43 requests the information storage server 50 to transmit the history information of the poster support rate.

  And the information provision process part 43 receives the historical information transmitted by the information storage server 50, and outputs the received historical information to user terminal 10a-10c. FIG. 9 is a diagram illustrating an example of the support rate history output screen 160.

  As shown in FIG. 9, the information provision processing unit 43 outputs history information representing a temporal change in the poster's support rate in a graph with the support rate on the vertical axis and the time axis on the horizontal axis.

  In the case where the ranking of the contributors is performed in descending order of the total number of word-of-mouth information posted by the contributor, when the status icons 151a to 151d are clicked with a mouse or the like, the total number of word-of-mouth information is represented as a temporal change. History information is output as a graph.

  In addition, when ranking the posters in the descending order of the number of times the review information posted by the contributor is viewed, when the status icons 151a to 151d are clicked with a mouse or the like, the number of times the contributor is viewed History information representing changes is output as a graph.

  Further, the information provision processing unit 43 displays the status icons 151a to 151d of a certain poster on the status icons 151a to 151d of other posters by operating the mouse or the like on the poster ranking output screen 150 shown in FIG. In addition, the word-of-mouth information of both contributors is output to the user terminals 10a to 10c when they are overlapped by a drag-and-drop operation.

  Specifically, when the two status icons 151a to 151d are overlapped by a drag-and-drop operation, the information providing processing unit 43 corresponds to the status icons 151a to 151d corresponding to the status icons 151a to 151d. It requests | requires to search whether there exists what was posted about the same restaurant among word-of-mouth information of a person's contributor.

  And the information provision process part 43 receives the information of the search result transmitted by the information storage server 50, and when there is the review information posted about the same restaurant, the review information for two persons is shown in FIG. Are output to the user terminals 10a to 10c in the format of the word-of-mouth information output screen 120 as shown in FIG.

  FIG. 10 is a diagram for explaining a drag-and-drop operation of the status icons 151a to 151d. As shown in FIG. 10, by dragging the status icon 151b of a certain contributor with the pointer 152 and dropping the status icon 151b on the status icon 151a with another contributor, the word-of-mouth information for two users is displayed. It is output to the terminals 10a to 10c.

  In addition, although it is supposed here that the word-of-mouth information posted about the same restaurant is output among the word-of-mouth information of two contributors corresponding to the status icons 151a to 151d overlapped by the drag and drop operation, the same It is good also as outputting the word-of-mouth information which satisfies other conditions, such as a genre.

  Returning to the description of FIG. 1, the control unit 44 is a control unit that totally controls the information providing server 40, and controls data exchange between the functional units.

  The information storage server 50 is a server that stores various information to be provided to the user. The information storage server 50 includes a communication processing unit 51, a storage unit 52, an information management unit 53, and a control unit 54.

  The communication processing unit 51 is a network interface that performs communication with the information providing server 40 or the information totaling server 60 via the network 70.

  The storage unit 52 is a storage device such as a hard disk device. The storage unit 52 stores store data 52a, contributor data 52b, post data 52c, specialty area store evaluation data 52d, store evaluation data 52e, contributor evaluation data 52f, support rate history data 52g, and contributor ranking data 52h. is doing.

  The store data 52a is basic data of each restaurant. FIG. 11 is a diagram illustrating an example of the store data 52a illustrated in FIG. As shown in FIG. 11, the store data 52a stores store ID, store name, genre, address, region, telephone number, transportation means, and coupon information. These are pieces of information received by an input device (not shown) of the information storage server 50 from an administrator of the information providing service.

  The store ID is an ID uniquely assigned to each restaurant. The store name is the name of each restaurant. The genre is a genre of food provided by each restaurant. The address is the address of each restaurant. The area is information on the area corresponding to the address. The telephone number is the telephone number of each restaurant.

  The transportation means is information on transportation means that is most convenient for going to each restaurant. The coupon is information on a coupon that can be used at each restaurant. When there is a coupon, the content is stored, and when there is no coupon, information “none” is stored.

  Returning to the description of FIG. 1, the contributor data 52b is basic data of the user who posted the word-of-mouth information. FIG. 12 is a diagram showing an example of the poster data 52b shown in FIG. As shown in FIG. 12, this contributor data 52b stores information on contributor ID, password, nickname, e-mail address, gender, date of birth, region, and genre. These pieces of information are information registered by operations of the user terminals 10a to 10c by the respective posters.

  The contributor ID is an ID uniquely assigned to each contributor. The password is a password that is input when each contributor posts. The nickname is a nickname used by each poster for posting. The e-mail address is the e-mail address of each contributor. The gender is the gender of each contributor. The date of birth is the date of birth of each contributor.

  The region is information on a region that each poster is good at evaluating restaurants. In the example of FIG. 12, only one piece of region information is registered for each contributor, but a plurality of regions may be registered.

  The genre is genre information that each poster is good at evaluating restaurants. In the example of FIG. 12, only one genre information is registered for each contributor, but the contributor may register a plurality of genres.

  Returning to the description of FIG. 1, the post data 52c is data in which word-of-mouth information posted by a contributor on the post acceptance screen 130 as shown in FIG. 5 is stored. FIG. 13 is a diagram showing an example of post data 52c shown in FIG.

  As shown in FIG. 13, this posting data 52c includes a posting ID, a contributor ID, a posting date, a store ID, a star rating, a scene, an amount of money, an atmosphere, a word of mouth, a word of mouth, a support rate, a non-support rate, and the number of views. The information is memorized.

  The posting ID is an ID assigned to each piece of review information posted by the poster. The contributor ID is an ID assigned to the contributor who posted the word-of-mouth information. This poster ID corresponds to the poster ID shown in FIG. The posting date and time is the date and time when each review information is posted.

  The store ID is an ID uniquely assigned to each restaurant. This store ID corresponds to the store ID shown in FIG. The star rating is a restaurant rating made by the contributor. This rating is made in five stages, with five stars being the highest rating and one star being the lowest rating.

  The scene is a restaurant scene evaluated by the poster. Specifically, the scene is selected by the contributor from “dinner”, “lunch”, “others”, and the like. The amount is information on the budget amount of the restaurant registered by the contributor. The atmosphere is information on the atmosphere of the restaurant registered by the poster.

  The review title is the title of the review information registered by the contributor. The word of mouth content is the content of the word of mouth information registered by the contributor. The number of support is the number of users who have supported (determined to be useful) the review information posted by the poster. The number of disapprovals is the number of users who did not support the word-of-mouth information posted by the contributor (determined not useful).

  The information management unit 53 receives the information from the information providing server 40 each time the evaluation buttons 128a to 128d are clicked with a mouse or the like on the word-of-mouth information output screen 120 shown in FIG. Update rate information.

  The number of browsing is information on the number of times each review information is browsed by the user. The information management unit 53 updates the information on the number of views each time the word-of-mouth information is transmitted to the information providing server 40 for output to the user terminals 10a to 10c.

  Returning to the description of FIG. 1, the specialty area store evaluation data 52d is data in which information on evaluation of each restaurant made by the poster is stored. FIG. 14 is a diagram showing an example of the specialty area store evaluation data 52d shown in FIG.

  Here, this specialty area store evaluation data 52d is for each restaurant corresponding to each contributor's area registered in the poster data 52b among all the word-of-mouth information registered in the posting data 52c. The evaluation of restaurants included in the word-of-mouth information posted by the contributor is tabulated for each restaurant.

  As shown in FIG. 14, this specialty area store evaluation data 52d includes number, store ID, average rating, number of reviews, number of reviews, star rating, five star rating, budget, atmosphere, gender / generation, latest Each information of word-of-mouth information and useful word-of-mouth information is stored.

  The number is a serial number of each restaurant. The total number of restaurants registered in the specialty area evaluation data 52d can be known from this number. The store ID is an ID uniquely assigned to each restaurant. This store ID corresponds to the store ID shown in FIG. The evaluation average score is an average value of star evaluations calculated by calculating the star evaluations of the posted data 52c shown in FIG. 13 for each restaurant.

  The number of word-of-mouth communication is the total number of word-of-mouth information for each restaurant, where the number of word-of-mouth information in post data 52c shown in FIG. The word-of-mouth ranking is the ranking of restaurants counted from the number of reviews when each restaurant is arranged in descending order of the number of reviews.

  The star rating is information obtained by tabulating the star rating of the posted data 52c shown in FIG. 13 for each restaurant. The five-star ranking is a ranking of restaurants counted from the one with the largest number of five stars when the restaurants are arranged in the order of the number of five stars. The budget is information obtained by tabulating the amount of post data 52c shown in FIG. 13 for each restaurant.

  The atmosphere is information obtained by tabulating the atmosphere of the posting data 52c shown in FIG. 13 for each restaurant. The sex / generation is information obtained by tabulating the sex / generation of the poster specified by the poster ID of the posting data 52c shown in FIG. 13 for each restaurant. The gender / generation of each contributor is determined by examining the sex and date of birth from the contributor data 52b using the contributor ID.

  The latest review information is information for specifying the latest review information among the review information posted to each restaurant, and the post ID of the post data 52c shown in FIG. 13 corresponding to the latest review information is registered. It has been done.

  The useful word-of-mouth information is information for identifying word-of-mouth information determined to be useful by the user among the word-of-mouth information posted to each restaurant, and is shown in FIG. 13 corresponding to the word-of-mouth information determined to be useful. The posting ID of the posting data 52c is registered. Specifically, the useful word-of-mouth information is a post ID for identifying the selected word-of-mouth information when a predetermined number of word-of-mouth information having a high number of support points obtained by subtracting the number of unsupported items from the number of support items is selected.

  In addition, here, it is supposed that each contributor will summarize the word-of-mouth information posted about the area where he is good, but the word-of-mouth information posted by each contributor about the cuisine genre of the restaurant he is good at It is good also as creating the evaluation data of a restaurant.

  Returning to the description of FIG. 1, the store evaluation data 52e is a total of evaluations of restaurants included in all the word-of-mouth information registered in the post data 52c. This store evaluation data 52e is similar to the specialty area store evaluation data 52d shown in FIG. 14, and includes a number, a store ID, an evaluation average score, the number of reviews, the number of reviews, a star rating, a five star rank, a budget, and an atmosphere. , Gender / generation, latest word of mouth information, useful word of mouth information. However, this information differs from the specialty area store evaluation data 52d in that the information is a total result of restaurant evaluations included in all the word-of-mouth information registered in the posted data 52c.

  This store evaluation data 52e is calculated by summing up all the word-of-mouth information instead of outputting the restaurant ranking generated based on the word-of-mouth information posted by each contributor on the area he / she is good at as shown in FIG. When the information providing server 40 receives the restaurant ranking output request generated in this way from the user terminals 10a to 10c, it is used to output such a restaurant ranking.

  The contributor evaluation data 52f is data that stores information on the contributor's evaluation made by another user to the contributor who posted the word-of-mouth information. FIG. 15 is a diagram showing an example of the poster evaluation data 52f shown in FIG.

  As shown in FIG. 15, this contributor evaluation data 52f includes a number, a contributor ID, the number of reviews posted, the number of reviews posted, a star rating, a budget, a genre, a support count, a non-support count, a support score, a support rate, Stores information on the number of icons and word-of-mouth information viewed.

  The number is a serial number of each contributor. By this number, the total number of posters registered in the poster evaluation data 52f can be known. The contributor ID is an ID uniquely assigned to each contributor. This poster ID corresponds to the poster ID shown in FIG.

  The number of reviews posted is the total number of reviews posted by each poster. The word-of-mouth contribution ranking is the ranking of the number of contributors counted in descending order of the number of word-of-mouth contributions when the number of word-of-mouth contributions is arranged in descending order.

  The star rating is information obtained by tabulating the five-level ratings of restaurants evaluated by each poster. Specifically, this is information obtained by counting how many times the poster has evaluated each star. The budget is information obtained by tabulating the number of word-of-mouth information posted by each contributor for each amount. The genre is information obtained by tabulating the number of word-of-mouth information posted by each contributor for each genre of restaurants.

  The number of support is the total number of users who supported (determined to be useful) the word-of-mouth information posted by each contributor. The number of disapprovals is the total number of users who did not support the word-of-mouth information posted by each contributor (determined to be useless). The number of support points is an index that serves as a standard for measuring the degree to which each contributor is supported by other users, and is a number obtained by subtracting the number of non-supports from the number of support.

  Like the support score, the support rate is an index that measures the degree to which each contributor is supported by other users, and the support number accounts for the total number of support and non-support. It is a ratio.

  The icons are information indicating the types of status icons 151a to 151d output in association with each poster when the poster ranking output screen 150 as shown in FIG. 7 is output to the user terminals 10a to 10c. .

  The status icons 151a to 151d are configured so that the number of word-of-mouth contributions, the number of support points, and the change in the support rate can be seen at a glance. The method for determining the icon type will be described in detail when the information totaling server 60 is described.

  The number of word-of-mouth information browsing is information on the number of times word-of-mouth information posted by each contributor has been viewed by the user.

  Returning to the description of FIG. 1, the support rate history data 52 g is data that stores information on temporal changes in the support rate of each contributor. FIG. 16 is a diagram illustrating an example of the support history data 52g illustrated in FIG. The support rate history data 52g stores support rate data in association with a poster ID and a predetermined time in the past.

  The contributor ID is an ID uniquely assigned to each contributor. This poster ID corresponds to the poster ID of the poster data 52b shown in FIG. The support rate is the ratio of the support number to the total number of the total number of support and non-support. This support rate is a value in the past predetermined time of the support rate of the contributor evaluation data 52f shown in FIG.

  In the example of FIG. 16, the predetermined time in the past is set by dividing every week such as “one week ago”, “two weeks ago”, “three weeks ago”,. However, the present invention is not limited to this, and may be divided at an arbitrary time.

  Returning to the description of FIG. 1, the contributor ranking data 52h is ranking data in which the contributors are arranged in descending order of (number of reviews posted × supported points). The poster ranking output screen 150 shown in FIG. 7 is output based on the poster ranking data 52h.

  FIG. 17 is a diagram illustrating an example of the poster ranking data 52h illustrated in FIG. The contributor ranking data 52h stores information on rank, contributor ID, nickname, icon, number of reviews posted, number of support points, and support rate.

  The ranking is the ranking of the contributors counted in descending order of (number of reviews posted × number of supporting points) when the posters are arranged in order of increasing (number of reviews posted × number of supporting points). The contributor ID is an ID uniquely assigned to each contributor. This poster ID corresponds to the poster ID shown in FIG.

  The nickname is a nickname used by each poster for posting. This nickname corresponds to the nickname of the poster data 52b shown in FIG. The icons are information of the types of status icons 151a to 151d that are output in association with each poster and are output so that the number of word-of-mouth contributions, the number of support points, and the support rate can be understood at a glance. This icon corresponds to the icon of the contributor evaluation data 52f shown in FIG.

  The number of reviews posted is the total number of reviews posted by each poster. The number of reviews posted corresponds to the number of reviews posted in the contributor evaluation data 52f shown in FIG. The support score is an index that serves as a measure for measuring the degree to which each contributor is supported by other users. This support score corresponds to the support score of the contributor evaluation data 52f shown in FIG.

  The support rate is an index serving as a standard for measuring the degree to which each contributor is supported by other users in the same manner as the support score, and corresponds to the support rate of the contributor evaluation data 52f shown in FIG. .

  Returning to the description of FIG. 1, the information management unit 53 sends a data transmission request or search request stored in the storage unit 52 from the information providing server 40 or the information totaling server 60, and stores data in the storage unit 52. The management unit manages information by executing a requested process when a write request, an update request for data stored in the storage unit 52, or the like is received.

  The control unit 53 is a control unit that controls the information storage server 50 as a whole, and controls data exchange between the functional units.

  The information totaling server 60 is a server that totals word-of-mouth information on restaurants posted by contributors, evaluation information of contributors evaluated by other users with respect to word-of-mouth information posted by contributors, and the like. The information totaling server 60 includes a communication processing unit 61, a storage unit 62, a store evaluation information totaling unit 63, and a contributor evaluation information totaling unit 64.

  The communication processing unit 61 is a network interface that performs communication with the information providing server 40 and the information storage server 50 via the network 70.

  The storage unit 62 is a storage device such as a hard disk device. The storage unit 62 stores icon determination data 62a. The icon determination data 62a is a determination for determining the type of status icons 151a to 151d output in association with each poster when the poster ranking output screen 150 shown in FIG. 7 is output to the user terminals 10a to 10c. It is data that stores the reference.

  FIG. 18 is a diagram illustrating an example of the icon determination data 62a illustrated in FIG. The icon determination data 62a stores information on the types of status icons 151a to 151d in association with the support rate and the number of reviews posted.

  The support rate is the ratio of the support number to the total number of the total number of support and non-support. The number of reviews posted is the total number of reviews posted by each poster. For example, when the support rate is 67% and the number of reviews posted is 52, the types of status icons 151a to 151d are “blue 100”.

  In the example of FIG. 18, the difference in the support rate is expressed by the difference in the colors of the status icons 151a to 151d, and the difference in the number of word-of-mouth contributions is expressed by a number. However, this expression method is not limited to this, and the difference in the support rate is expressed by a difference in the numbers, and the difference in the number of reviews posted may be expressed by the colors of the status icons 151a to 151d. .

  Moreover, it is good also as expressing the difference, such as a support rate and the number of word-of-mouth contributions, in the form of status icons 151a-151d. Furthermore, the evaluation of the contributor expressed using the status icons 151a to 151d is not limited to the support rate and the number of word-of-mouth contributions, and may be other things such as the support score.

  Returning to the description of FIG. 1, the store evaluation information totaling unit 63 is a totaling unit that periodically totals word-of-mouth information on restaurants posted by contributors.

  Specifically, the store evaluation information totaling unit 63 acquires the post data 52c shown in FIG. 13 from the information storage server 50, and stores the specialty area store evaluation data 52d shown in FIG. The evaluation data 52e generates the evaluation average score, the number of reviews, the number of reviews, the star rating, the five star ranking, the budget, the atmosphere, the gender / generation, the latest review information, and the useful word of mouth information, and the information storage server 50 The process to memorize such information is performed.

  The contributor evaluation information totaling unit 64 is a totalizing unit that totals the evaluation information of contributors evaluated by other users with respect to the word-of-mouth information posted by contributors.

  Specifically, the poster evaluation information totaling unit 64 acquires the posting data 52c shown in FIG. 13 from the information storage server 50, and the number of reviews posted by the poster evaluation data 52f shown in FIG. The number of reviews posted, ranking, star rating, budget, genre, number of supports, number of unsupported, number of support points, support rate, icon information are generated, and the information storage server 50 stores the information.

  When generating icon information, the contributor evaluation information totaling unit 64 generates icon information based on the determination criteria stored in the icon determination data 62a. At that time, the poster evaluation information totaling unit 64 acquires the support rate history data 52g from the information storage server 50, and compares the current support rate value with the past support rate value, thereby the status icons 151a to 151a. In 151d, the direction of the arrow indicating the change in the support rate is determined.

  Further, when the information storage server 50 stores new support rate information, the contributor evaluation information totaling unit 64 stores the old support rate value as the support rate history data 52g shown in FIG. Furthermore, the contributor evaluation information totaling unit 64 arranges the contributors registered in the contributor evaluation data 52f in the descending order of the number of reviews posted (supported points × the number of support points), whereby the contributor ranking data 52h shown in FIG. It is generated and stored in the information storage server 50.

  The control unit 65 is a control unit that controls the information totaling server 60 as a whole, and controls data exchange between the functional units.

  Next, a processing procedure of word-of-mouth information aggregation processing according to the present embodiment will be described. FIG. 19 is a flowchart illustrating the processing procedure of the word-of-mouth information aggregation processing according to the present embodiment. As shown in FIG. 19, first, the store evaluation information totaling unit 63 of the information totaling server 60 performs time information acquisition processing for periodically acquiring time information from a clock (not shown) provided in the information totaling server 60. Perform (step S101).

  Then, the store evaluation information totaling unit 63 checks whether or not the current time is a preset time (step S102). If the current time is not a preset time (No at Step S102), the store evaluation information totaling unit 63 returns to Step S101 and continues the time information acquisition process.

  If the current time is a preset time (step S102, Yes), the store evaluation information totaling unit 63 sends the store data 52a, the poster data 52b, the posted data 52c, and the support rate history from the information storage server 50. A data reading process for reading the data 52g is performed (step S103).

  Thereafter, the store evaluation information totaling unit 63 totals restaurant evaluation information for each store based on the posted data 52c, and performs store evaluation information totaling processing for requesting that the totaled evaluation information be stored in the information storage server 50. (Step S104). The information management unit 52 of the information storage server 50 that has received this request stores the received evaluation information in the storage unit 52 as the specialty area store evaluation data 52d and the store evaluation data 52e.

  Subsequently, the contributor evaluation information totaling unit 64 totals the contributor evaluation information for each contributor based on the post data 52c, and requests the contributor evaluation information to store the totaled evaluation information in the information storage server 50. Aggregation processing is performed (step S105). The information management unit 52 of the information storage server 50 that has received this request stores the received evaluation information in the storage unit 52 as the poster evaluation data 52f, the support history data 52g, and the poster ranking data 52h.

  Then, the store evaluation information totaling unit 63 checks whether or not this word-of-mouth information totaling process end request has been received by an input device (not shown) of the information totaling server 60 (step S106), and the word-of-mouth information totaling process end request Is received (step S106, Yes), the word-of-mouth information aggregation process is terminated. When the termination request for the word-of-mouth information totaling process has not been received (step S106, No), the process returns to step S101 and the time information acquisition process is performed again.

  Next, the processing procedure of the store evaluation information tabulation process shown in FIG. 19 will be described in more detail. FIG. 20 is a diagram for explaining the processing procedure of the store evaluation information tabulation process shown in FIG. Here, the case where the store evaluation information registered in the specialty area store evaluation data 52d shown in FIG. 14 is totaled will be described.

  As illustrated in FIG. 20, first, the store evaluation information totaling unit 63 selects a restaurant corresponding to the poster's area registered in the poster data 52b from the word-of-mouth information stored in the posted data 52c. The posted word-of-mouth information is extracted (step S201). The area and genre of each restaurant can be examined with reference to the store data 52a.

  And the shop evaluation information total part 63 totals the number of extracted word-of-mouth information for every restaurant, and calculates the number of word-of-mouth in the specialty area shop evaluation data 52d (step S202). Subsequently, the store evaluation information totaling unit 63 ranks the restaurants in descending order of the number of reviews posted, and calculates the number of reviews in the specialty area store evaluation data 52d (step S203).

  Thereafter, the store evaluation information totaling unit 63 totals the star ratings of the extracted word-of-mouth information for each restaurant, and calculates the star rating in the specialty area store evaluation data 52d (step S204). Then, the store evaluation information totaling unit 63 ranks the restaurants in order of increasing five stars in the star evaluation totaled for each restaurant, and calculates the five-star rank in the specialty area store evaluation data 52d (step). S205).

  Thereafter, the store evaluation information totaling unit 63 calculates an evaluation average score in the specialty area store evaluation data 52d using the information of star evaluation totaled for each restaurant (step S206). Then, the store evaluation information totaling unit 63 totals the information on the amount of money in the extracted word-of-mouth information for each restaurant, and generates budget information in the specialty area store evaluation data 52d (step S207).

  Subsequently, the store evaluation information totaling unit 63 totals the atmosphere information in the extracted word-of-mouth information for each restaurant, and generates the atmosphere information in the specialty area store evaluation data 52d (step S208).

  Then, the store evaluation information totaling unit 63, based on the poster ID in the extracted word-of-mouth information and the gender and date of birth information corresponding to the poster ID stored in the poster data 52b. The gender / generation information is aggregated for each restaurant, and the gender / generation information in the specialty area evaluation data 52d is generated (step S209).

  Subsequently, the store evaluation information totaling unit 63 determines the latest word-of-mouth information in the evaluation data 52d from the posting date / time information in the extracted word-of-mouth information (step S210). Further, the store evaluation information totaling unit 63 determines useful word-of-mouth information in the evaluation data 52d by calculating the number of support points from the support rate and non-support rate information in the extracted word-of-mouth information (step S211).

  Thereafter, the store evaluation information totaling unit 63 transmits the result obtained by the processing from step S201 to step S211 to the information storage server 50 (step S212), and the result is sent to the information storage server 50 as the specialty area store evaluation data. 52d is stored, and this store evaluation information totaling process is terminated.

  Here, the case where the store evaluation information registered in the specialty area store evaluation data 52d shown in FIG. 14 is totaled has been described. However, when the store evaluation information registered in the store evaluation data 52d is totalized, In step S201, instead of extracting the word-of-mouth information posted to the restaurant corresponding to the poster's area registered in the poster data 52b, all the word-of-mouth information is acquired, and in the subsequent processing, Each process is performed on all acquired word-of-mouth information.

  Next, the processing procedure of the contributor evaluation information tabulation process shown in FIG. 19 will be described in more detail. FIG. 21 is a diagram for describing the processing procedure of the contributor evaluation information aggregation processing shown in FIG. As shown in FIG. 21, first, the contributor evaluation information totaling unit 64 sums up the number of reviews posted in the posting data 52c for each contributor, and calculates the number of reviews posted in the contributor evaluation data 52f (step). S301).

  Then, the contributor evaluation information totaling unit 64 ranks contributors in descending order of the number of reviews posted for each contributor, and calculates the number of reviews posted in the contributor evaluation data 52f (step S302).

  Subsequently, the poster evaluation information totaling unit 64 totals the star ratings stored in the posting data 52c for each poster, and calculates the star rating in the poster evaluation data 52f (step S303). Then, the poster evaluation information totaling unit 64 totals the amount information stored in the posting data 52c for each poster, and generates budget information in the poster evaluation data 52f (step S304).

  Thereafter, the poster evaluation information totaling unit 64 obtains the genre information of the restaurant based on the store ID stored in the post data 52c and the genre information corresponding to the store ID stored in the store data 52a. The information is totaled for each contributor, and genre information in the contributor evaluation data 52f is generated (step S305).

  Then, the poster evaluation information totaling unit 64 totals the information on the number of support and the number of disapproval stored in the post data 52c for each contributor, and calculates the number of support and the number of unsupport in the poster evaluation data 52f ( Step S306).

  Subsequently, the contributor evaluation information totaling unit 64 calculates the support score in the contributor evaluation data 52f by subtracting the unsupported number from the total supported number (step S307). Then, the contributor evaluation information totaling unit 64 calculates a support rate in the contributor evaluation data 52f by calculating a ratio of the support number in the total number of the support number and the non-support number (step). S308).

  Thereafter, the poster evaluation information totaling unit 64 refers to the icon determination data 62a and the support rate history data 52g, and counts the number of reviews posted for each contributor specified by the contributor ID, and the calculated support rate. Based on the past support rate, icon information in the poster evaluation data 52f is generated (step S309).

  Subsequently, the contributor evaluation information totaling unit 64 sums up the number of views of the posting data 52c for each contributor, and calculates the number of reviews of word-of-mouth information in the contributor evaluation data 52f (step S310).

  Then, the contributor evaluation information totaling unit 64 includes information on the nickname stored in the contributor data 52b, icons of each contributor generated for the contributor evaluation data 52f, the number of reviews posted, the number of support points, and the support rate information. Using the above, the poster ranking data 52h is generated by arranging the posters in the descending order of (number of reviews posted × number of support points) (step S311).

  Here, when (the number of reviews contributed × the number of support points) is the same, a contributor with a large number of support points is regarded as an upper contributor. Further, if the support points are also the same, those posters are assigned the same ranking, and ranking is performed in alphabetical order using the poster ID.

  Thereafter, the poster evaluation information totaling unit 64 transmits the result obtained by the processing from step S301 to step S311 to the information storage server 50 (step S312), and the result is sent to the information storage server 50 by the poster evaluation data. 52f is stored as contributor ranking data 52h, and the contributor evaluation information totaling process is terminated.

  Below, the process sequence of the restaurant information provision process which concerns on a present Example is demonstrated. FIG. 22 is a flowchart illustrating the processing procedure of the restaurant information providing process according to the present embodiment.

  As shown in FIG. 22, first, the information provision processing unit 43 of the information provision server 40 accepts a processing request for restaurant information provision processing from the user terminals 10a to 10c (step S401), and examines the contents of the accepted processing request. (Step S402).

  If the received processing request is a review information posting process execution request, the information provision processing unit 43 and the information management unit 53 of the information storage server 50 execute a review information posting process (step S403).

  Specifically, the information provision processing unit 43 outputs a post acceptance screen 130 as shown in FIG. 5 to the user terminals 10a to 10c, and accepts input of word-of-mouth information by the user. Then, the information provision processing unit 43 transmits the received word-of-mouth information to the information management unit 53. Then, the information management unit 53 stores the received word-of-mouth information in the storage unit 52 as post data 52c.

  After completion of the word-of-mouth information posting process, the information provision processing unit 43 checks whether or not this restaurant information provision process termination request has been received by an input device (not shown) of the information provision server 40 (step S408). When the end request for the store information providing process is received (step S408, Yes), the restaurant information providing process is ended.

  When the termination request for the restaurant information provision process has not been received (No at Step S408), the process returns to Step S401, and the process for accepting the processing request for the restaurant information provision process from the user terminals 10a to 10c is performed again.

  When the content of the processing request checked in step S402 is a restaurant search processing execution request made by the user on the top screen 100 described in FIG. 2, the information provision processing unit 43 and the information management unit 53 Store search processing is executed (step S404).

  Specifically, the information provision processing unit 43 transmits the narrowing-down conditions input on the top screen 100 to the information management unit 53 and requests to search for restaurant information that matches the narrowing-down conditions such as the designation of the area.

  The information management unit 53 that has received this request searches the restaurant data 52a and the specialty area store evaluation data 52d for restaurant information and evaluation information for the restaurant that match the narrowing-down conditions, and the searched information is the information provision processing unit 43. Send to.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information management unit 53, generates data constituting the regional store ranking output screen 110 as shown in FIG. 3 using the information, Data is transmitted to the user terminals 10a to 10c, and the regional store ranking output screen 110 is output. After the restaurant search process ends, the process proceeds to step S408, and the subsequent processes are executed.

  In addition, instead of outputting the restaurant ranking generated based on the word-of-mouth information posted by each contributor on the area he / she is good at, information on the restaurant ranking output request generated by summing up all the word-of-mouth information When the provision processing unit 43 receives from the user terminals 10a to 10c, the information provision processing unit 43 configures the regional store ranking output screen using the store evaluation data 52e generated by collecting all the word-of-mouth information. The data to be generated is generated, and the data is transmitted to the user terminals 10a to 10c to output the regional store ranking output screen.

  The content of the processing request checked in step S402 was a word-of-mouth information output request made by clicking the store name [genre] with the mouse or the like in the restaurant ranking 111 on the regional ranking output screen 110 shown in FIG. In this case, the information provision processing unit 43 and the information management unit 53 execute a word-of-mouth information output process (step S405).

  Specifically, the information provision processing unit 43 transmits information on a restaurant clicked with a mouse or the like to the information management unit 53 and requests to search for word-of-mouth information corresponding to the restaurant. Upon receiving this request, the information management unit 53 searches the post data 52c for the latest review information and useful review information of the specialty area store evaluation data 52d, and sends the searched review information to the information provision processing unit 43. Send.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information management unit 53, generates data constituting the word-of-mouth information output screen 120 as shown in FIG. 4 using the information, and stores the data. It transmits to the user terminals 10a-10c, and the word-of-mouth information output screen 120 is output. After the word-of-mouth information output process ends, the process proceeds to step S408, and the subsequent processes are executed.

  When the content of the processing request checked in step S402 is a contributor ranking output request made by the user on the top screen 100 described in FIG. 2, the information provision processing unit 43 and the information management unit 53 Ranking output processing is executed (step S406).

  Specifically, when the display button 105 of the contributor ranking display reception area 103 on the top screen 100 is clicked by an operation of a mouse or the like, the information provision processing unit 43 displays the contributor ranking to the information management unit 53. Request to send information.

  The information management unit 53 that has received this request transmits the information stored as the poster ranking data 52 h to the information provision processing unit 43. Thereafter, the information provision processing unit 43 receives the information transmitted by the information provision processing unit 43, generates data constituting the poster ranking output screen 150 as shown in FIG. 7 using the information, Data is transmitted to the user terminals 10a to 10c and the poster ranking output screen 150 is output.

  Further, when the status icons 151a to 151d on the poster ranking output screen 150 are clicked by the user with the mouse or the like, the information provision processing unit 43 displays the information of the poster corresponding to the clicked status icons 151a to 151d. The information management unit 53 is requested to transmit the support history information.

  Upon receiving this request, the information management unit 53 reads the support rate history information of the poster corresponding to the clicked status icons 151 a to 151 d from the support rate history data 52 g and transmits it to the information provision processing unit 43.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information provision processing unit 43, generates data constituting the support rate history output screen 160 as shown in FIG. 9 using the information, Data is transmitted to the user terminals 10a to 10c and the support rate history output screen 160 is output.

  Further, as described with reference to FIG. 10, drag and drop for dragging the status icons 151 a to 151 d of a certain poster and dropping them on the status icons 151 a to 151 d of other posters is performed on the poster ranking output screen 150. When the operation is performed with a mouse or the like, the information provision processing unit 43 requests the information management unit 53 to search for word-of-mouth information posted by both posters on the same restaurant.

  The information management unit 53 that has received this request searches the posted data 52c for the review information posted by both contributors on the same restaurant, and transmits the review information obtained by the search to the information provision processing unit 43. In addition, the restaurant information and the evaluation information for the restaurant are searched from the store data 52a and the specialty area store evaluation data 52d, and the searched information is transmitted to the information provision processing unit 43.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information provision processing unit 43, and displays the latest word of mouth information 122 and the useful word of mouth information 123 for two persons on the word of mouth information output screen 120 as shown in FIG. The data constituting the word-of-mouth information output screen replaced with the word-of-mouth information is generated, and the data is transmitted to the user terminals 10a to 10c to output the word-of-mouth information output screen.

  When such processing is completed, the process proceeds to step S408, and the subsequent processing is executed.

  The content of the processing request checked in step S402 is the latest review information 122 on the review information output screen 120 shown in FIG. 4, the nickname of the contributor in the useful review information 123, or the contributor ranking output screen 150 shown in FIG. If the poster information output request is made by clicking on the nickname of the poster in the mouse or the like, the information provision processing unit 43 and the information management unit 53 execute a poster information output process (step S407). ).

  Specifically, the information provision processing unit 43 requests the information management unit 53 to transmit the posting history information of the poster corresponding to the poster whose nickname is clicked. The information management unit 53 that has received this request reads out the posting history information of the poster corresponding to the poster whose nickname was clicked from the poster evaluation data 52 f and transmits it to the information provision processing unit 43.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information management unit 53, generates data constituting the poster review history output screen 140 as shown in FIG. The data is transmitted to the user terminals 10a to 10c, and the contributor word-of-mouth history output screen 140 is output.

  After the end of the poster information output process, the process proceeds to step S408, and the subsequent processes are executed.

  In the above embodiment, the case where the word-of-mouth information management process is realized on each computer has been described. However, a program for realizing the word-of-mouth information management process is recorded on a computer-readable recording medium, and this recording medium is recorded. The word-of-mouth information management process may be realized by causing the computer to read and execute the program recorded on the computer.

  FIG. 23 is a block diagram illustrating a hardware configuration of a computer 200 that implements word-of-mouth information management processing. As shown in FIG. 23, the computer 200 includes a CPU 210 that executes the program, an input device 220 that inputs data, a ROM 230 that stores various data, a RAM 240 that stores calculation parameters and the like, and word-of-mouth information management processing A reading device 250 that reads a program from a recording medium 300 that records a program for realizing the above, an output device 260 such as a display, and a network interface 270 that exchanges data with other computers via the network 400 However, they are connected by a bus 280.

  The CPU 210 implements the word-of-mouth information management process by reading the program recorded on the recording medium 300 via the reading device 250 and then executing the program. Examples of the recording medium 300 include an optical disk, a flexible disk, a CD-ROM, and a hard disk. Further, this program may be installed in the computer 200 via the network 400.

  As described above, in this embodiment, the information storage server 50 stores the word-of-mouth information for the restaurant posted by the contributor, and the information aggregation server 60 is based on the word-of-mouth information stored in the information storage server 50. And generating information related to an evaluation ranking that ranks restaurants corresponding to a predetermined region (good region) registered by the poster and / or a predetermined genre (special genre) of the restaurant registered by the poster. Therefore, it is possible to provide information that reflects the characteristics of each contributor more strongly and provides it to the user in a ranking format that is easy for the user to view. Reliability can be increased.

  Further, in this embodiment, the information totaling server 60 generates information related to the posting history in which the poster posted the word-of-mouth information as shown in FIG. 6 based on the word-of-mouth information stored by the information storage server 50. Therefore, the past posting tendency of the poster can be checked, and the user can easily confirm the reliability of the information posted by the poster.

  In the present embodiment, the information related to the posting history is information related to the distribution of genres of restaurants where the word-of-mouth information is posted by the poster. It is possible to check whether the information has been posted, and the user can easily check the reliability of the information posted by the poster.

  Further, in this embodiment, the information totaling server 60 is input by the user or the region designated by the GPS function provided in the user terminals 10a to 10c based on the word-of-mouth information stored by the information storage server 50. Since the information related to the evaluation ranking that ranks the restaurants corresponding to the region is generated, the user can easily check the restaurants with high evaluation in the region where the information is desired.

  Further, in this embodiment, the information totaling server 60 is based on the word-of-mouth information stored by the information storage server 50, for each age and / or gender of the word-of-mouth information poster for the restaurant as shown in FIG. Therefore, the user can easily check what age and / or gender has posted the word-of-mouth information, and can analyze the evaluation result.

  Further, in this embodiment, the information providing server 40 receives the evaluation made on the word-of-mouth information stored by the information storage server 50, and the information totaling server 60 performs the received evaluation as shown in FIG. Since the information related to the evaluation ranking that ranks the posters is generated based on the information, the user can easily check the reliable posters.

  Further, in this embodiment, the information totaling server 60 performs the evaluation performed on the poster within a predetermined period as shown in FIG. 9 based on the evaluation of the word-of-mouth information received by the information providing server 40. Since the information related to the history is generated, the user can easily check the transition of the evaluation with respect to the poster, and can accurately check the reliable poster.

  Further, in this embodiment, the information totaling server 60 counts the number of word-of-mouth information stored by the information storage server 50 for each contributor and ranks the contributors based on the totaled result. Since the information is generated, the user has a large number of postings of word-of-mouth information, and can easily check reliable posters.

  Further, in this embodiment, the information totaling server 60 generates information related to the history of the number of contributions posted by the contributor within a predetermined period based on the above totaling result. It is possible to easily check the transition of the number of postings of the user's word-of-mouth information, and to accurately check the author who can be trusted.

  In this embodiment, the information totaling server 60 totals the number of reviews of the word-of-mouth information stored by the information storage server 50 for each contributor who posted the word-of-mouth information, and ranks the poster based on the totaled result. Since the information related to the attached evaluation ranking is generated, the number of reviews of the word-of-mouth information is large, and a reliable poster can be easily checked.

  In the present embodiment, the information totaling server 60 generates information related to the number of histories of the number of reviews posted by the contributor within a predetermined period based on the above totaling result. The transition of the number of reviews of the contributor's word-of-mouth information can be easily checked, and the reliable contributor can be accurately checked.

  Although the embodiments of the present invention have been described so far, the present invention may be implemented in various different embodiments in addition to the above-described embodiments within the scope of the technical idea described in the claims. It ’s good.

  For example, in the above-described embodiment, the contributor registers in advance the area and genre that he / she is good at. However, the present invention is not limited to this, and the information management unit 53 of the information storage server 50 can post the post. Among the regions and genres corresponding to restaurants where the user has posted reviews in the past, the most frequently posted regions and genres are detected, and the detected regions and genres are set as the poster's favorite regions and genres. It is good as well.

  In addition, among the processes described in this embodiment, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method.

  In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

  Each component of each illustrated device is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  Furthermore, all or some of the processing functions performed in each device may be realized by a CPU and a program that is analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  As described above, the evaluation information management system, the evaluation information management program, and the posting information management method according to the present invention require the user to provide information that more strongly reflects the characteristics of each poster. Useful for management systems.

It is a figure explaining the structure of the information provision system 20 which concerns on a present Example. It is a figure which shows an example of the top screen 100 which receives the output request of restaurant information. It is a figure which shows an example of the restaurant ranking output screen 110 according to area. It is a figure which shows an example of the word-of-mouth information output screen. 5 is a diagram illustrating an example of a posting acceptance screen 130. FIG. It is a figure which shows an example of the author review contribution log | history output screen. It is a figure which shows an example of the contributor ranking output screen. It is a figure explaining the arrow which shows the support rate change of the status icons 160a-160c. It is a figure which shows an example of the support rate log | history output screen. It is a figure explaining drag and drop operation of status icons 151a-151d. It is a figure which shows an example of the shop data 52a shown in FIG. It is a figure which shows an example of the contributor data 52b shown in FIG. It is a figure which shows an example of the posting data 52c shown in FIG. It is a figure which shows an example of the specialty area store evaluation data 52d shown in FIG. It is a figure which shows an example of the contributor evaluation data 52f shown in FIG. It is a figure which shows an example of the support rate log | history data 52g shown in FIG. It is a figure which shows an example of the contributor ranking data 52h shown in FIG. It is a figure which shows an example of the icon determination data 62a shown in FIG. It is a flowchart which shows the process sequence of the word-of-mouth information total process which concerns on a present Example. It is a figure explaining the process sequence of the shop evaluation information total process shown in FIG. It is a figure explaining the process sequence of the contributor evaluation information total process shown in FIG. It is a flowchart which shows the process sequence of the restaurant information provision process which concerns on a present Example. It is a block diagram which shows the hardware constitutions of the computer 200 which implement | achieves word-of-mouth information management processing.

Explanation of symbols

10a to 10c User terminal 20 Information providing system 30, 70 Network 40 Information providing server 41 Communication processing unit 42 Storage unit 42a Content data 42b User data 43 Information providing processing unit 44 Control unit 50 Information storage server 51 Communication processing unit 52 Storage unit 52a Store data 52b Poster data 52c Posting data 52d Specialty area store evaluation data 52e Store evaluation data 52f Contributor evaluation data 52g Support rate history data 52h Contributor ranking data 53 Information management unit 54 Control unit 60 Information totaling server 61 Communication processing unit 62 Storage unit 62a Icon determination data 63 Store evaluation information totaling unit 64 Contributor evaluation information totaling unit 65 Control unit

Claims (33)

An evaluation information management system for managing evaluation information posted by a contributor to an evaluation target,
Storage means for storing evaluation information for an evaluation object posted by the contributor;
Based on the evaluation information stored by the storage means, an evaluation ranking in which evaluation objects corresponding to a predetermined region registered by the contributor and / or a predetermined genre of evaluation objects registered by the contributor are ranked. Generating means for generating information related to
An evaluation information management system characterized by comprising:   The post history information generating means for generating information related to a post history in which the contributor posted the evaluation information based on the evaluation information stored by the storage means. Evaluation information management system.   The evaluation information management system according to claim 2, wherein the information related to the posting history is information related to a distribution of an evaluation target genre for which evaluation information is posted by a poster.   Based on the evaluation information stored by the storage means, the area designation receiving means for receiving the designation of the area, and information related to the evaluation ranking that ranks the evaluation objects corresponding to the areas that have received the designation by the area designation receiving means. The evaluation information management system according to claim 1, further comprising: evaluation target ranking information generation means for generating.   The information processing apparatus further comprises distribution information generation means for generating information relating to the distribution of each evaluation subject's age and / or gender based on the evaluation information stored by the storage means. The evaluation information management system according to any one of claims 1 to 4.   An evaluation receiving unit that receives an evaluation made on the evaluation information stored by the storage unit, and an evaluation ranking that generates information related to an evaluation ranking in which posters are ranked based on the evaluation received by the evaluation receiving unit. The evaluation information management system according to any one of claims 1 to 5, further comprising information generation means.   An evaluation history information generating unit configured to generate information related to a history of evaluations made to the poster within a predetermined period based on the evaluation received by the evaluation receiving unit. Item 7. The evaluation information management system according to Item 6.   The number of evaluation information stored by the storage means is calculated for each contributor, and the evaluation ranking that ranks the contributors based on the totaled result calculated by the evaluation information number totaling means The evaluation information management system according to claim 1, further comprising evaluation information number ranking information generation means for generating information.   The system further comprises post number history information generating means for generating information related to the history of the number of postings of the evaluation information by the contributor within a predetermined period based on the totaling result totaled by the evaluation information number totaling means. The evaluation information management system according to claim 8.   The number-of-views counting means for counting the number of browsing of the evaluation information stored in the storage means for each contributor who posted the evaluation information, and the posters were ranked based on the counting results totaled by the number-of-viewing counting means The evaluation information management system according to claim 1, further comprising browsing number ranking information generation means for generating information related to the evaluation ranking.   Based on the results counted by the browsing number counting means, the information further includes browsing number history information generating means for generating information relating to the history of the number of evaluation information posted by the poster viewed within a predetermined period. The evaluation information management system according to claim 10. An evaluation information management program for managing evaluation information posted by a contributor to an evaluation target,
Computer
Storage means for storing evaluation information for an evaluation object posted by the contributor;
Based on the evaluation information stored by the storage means, an evaluation ranking in which evaluation objects corresponding to a predetermined region registered by the contributor and / or a predetermined genre of evaluation objects registered by the contributor are ranked. Generating means for generating information relating to
An evaluation information management program characterized by functioning as   13. The computer is further caused to function as a posting history information generating unit that generates information related to a posting history in which the poster posted the evaluation information based on the evaluation information stored by the storage unit. Evaluation information management program described in 1.   The evaluation information management program according to claim 13, wherein the information related to the posting history is information related to a distribution of an evaluation target genre in which evaluation information is posted by a contributor.   Based on the evaluation information stored in the area designation receiving means for receiving the designation of the area, and the storage means, the computer ranks the evaluation ranking corresponding to the area for which the designation is accepted by the area designation receiving means. The evaluation information management program according to claim 12, 13 or 14, further functioning as evaluation target ranking information generation means for generating such information.   Further causing the computer to function as distribution information generation means for generating information related to the age and / or sex distribution of the poster of the evaluation information for each evaluation object based on the evaluation information stored by the storage means. The evaluation information management program according to any one of claims 12 to 15, wherein   An evaluation receiving unit that receives an evaluation made on the evaluation information stored by the storage unit, and information related to an evaluation ranking that ranks a poster based on the evaluation received by the evaluation receiving unit. The evaluation information management program according to any one of claims 12 to 16, further functioning as evaluation ranking information generating means.   The computer is further caused to function as an evaluation history information generating unit that generates information related to a history of evaluations made to the poster within a predetermined period based on the evaluation received by the evaluation receiving unit. An evaluation information management program according to claim 17.   Evaluation ranking for the number of evaluation information stored by the storage means for each contributor in the computer, evaluation ranking that ranks the contributors based on the tabulation results tabulated by the number of evaluation information counting means The evaluation information management program according to any one of claims 12 to 18, further functioning as evaluation information number ranking information generation means for generating information related to the above.   The computer functions as a posting number history information generating unit that generates information related to the history of the number of postings of the evaluation information by the contributor within a predetermined period based on the counting result totaled by the evaluation information number counting unit. 20. The evaluation information management program according to claim 19, wherein:   A browsing number totaling unit that counts the number of browsing of evaluation information stored in the storage unit for each contributor who posted the evaluation information; and a poster based on the totaling result totaled by the browsing number totaling unit The evaluation information management program according to any one of claims 12 to 20, further functioning as browsing number ranking information generation means for generating information related to ranked evaluation rankings.   As a browsing number history information generating means for generating information related to the history of the number of times the evaluation information posted by the contributor has been browsed within a predetermined period based on the results counted by the browsing number counting means The evaluation information management program according to claim 21, further comprising a function. An evaluation information management method for managing evaluation information posted by a contributor to an evaluation target,
A storage step of storing evaluation information for an evaluation object posted by the contributor;
Based on the evaluation information stored in the storage step, the evaluation rankings rank the evaluation objects corresponding to the predetermined region registered by the contributor and / or the predetermined genre of the evaluation object registered by the contributor. A generation step of generating information according to
The evaluation information management method characterized by including.   In addition to generating the evaluation ranking, the generation step generates information related to a posting history in which the contributor posted evaluation information based on the evaluation information stored in the storage step. The evaluation information management method according to claim 23.   25. The evaluation information management method according to claim 24, wherein the information relating to the posting history is information relating to a distribution of an evaluation target genre in which the evaluation information is posted by a contributor.   In addition to generating the evaluation ranking, the generation step accepts designation of a region, and ranks evaluation targets corresponding to the region that has accepted designation based on the evaluation information stored in the storage step. 26. The evaluation information management method according to claim 23, 24 or 25, wherein information related to ranking is generated.   In addition to generating the evaluation ranking, the generation step is based on the evaluation information stored in the storage step, and information related to the distribution of the evaluation information for each evaluation subject by the age and / or gender 24. The evaluation information management method according to claim 23, wherein:   In addition to generating the evaluation ranking, the generation step accepts an evaluation made on the evaluation information stored by the storage step, and based on the received evaluation, information on the poster's evaluation ranking is received. The evaluation information management method according to claim 23, wherein the evaluation information management method is generated.   29. The information generation method according to claim 28, wherein the generation step generates information related to a history of evaluations made to the contributor within a predetermined period based on an evaluation made on the evaluation information. Evaluation information management method.   In addition to generating the evaluation ranking, the generation step counts the number of evaluation information stored by the storage step for each contributor, and relates to an evaluation ranking that ranks the contributor based on the aggregation result. 24. The evaluation information management method according to claim 23, wherein information is generated.   The evaluation information management method according to claim 30, wherein the generation step generates information related to a history of the number of postings of the evaluation information by the contributor within a predetermined period based on the aggregation result. .   In addition to generating the evaluation ranking, the generation step counts the number of evaluation information stored by the storage step for each poster who posted the evaluation information, and ranks the poster based on the total result. 24. The evaluation information management method according to claim 23, wherein information related to the attached evaluation ranking is generated.   The evaluation according to claim 32, wherein the generation step generates information related to a history of the number of evaluation information posted by the contributor viewed within a predetermined period based on the aggregation result. Information management method.

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