Information processing system

Abstract

To further effectively use evaluation information of products / service.SOLUTION: An information processing system 10 includes: aggregation means 12 for aggregating the number of pieces of evaluation information and an evaluation value for every store based on evaluation information including evaluation values representing degrees of evaluation for stores, and calculating, for every attribute set to each store, a total value obtained by totaling the number of pieces of store evaluation information included in the attribute and an evaluation total value obtained by aggregating evaluation values included in evaluation information into one; and output means 13 for outputting to display distribution of attributes based on the total value and the evaluation total value in a coordinate space, with the number of pieces of evaluation information and the evaluation values respectively defined as coordinate axes.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing method, and a program. [Background technology]

[0002] On Internet websites, in addition to information introducing products and services provided by businesses, evaluation information, including opinions and evaluation values ​​posted by users who have used the products and services, is also posted. For example, evaluation information is published on websites such as search sites, reservation sites, review sites, survey sites, weblogs, and SNS (Social Networking Service).

[0003] While such evaluation information can be used as a reference by general users who are considering using a product or service, it is also extremely important information for business operators who provide products and services in order to develop products and improve services in the future. For this reason, business operators collect and analyze user evaluation information. For example, Patent Document 1 describes a method of calculating an evaluation score based on the number or ratio of positive evaluation information and negative evaluation information, and expressing the evaluation score in a time-series line graph. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-12615 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the method of Patent Document 1 described above targets evaluation information of one store, and it is difficult to analyze evaluation information of multiple stores at once. In addition, it is difficult to analyze evaluation information of all products and services at once, not limited to evaluation information of stores. As a result, a problem occurs in that it is not possible to make more effective use of evaluation information by users.

[0006] Therefore, an object of the present invention is to solve the above-mentioned problem of being unable to make more effective use of evaluation information of products and services. [Means for solving the problem]

[0007] An information processing system according to one embodiment of the present invention comprises: aggregating means for aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on evaluation information including evaluation values ​​that indicate the degree of evaluation of the store, and calculating, for each attribute set for the store, a total value obtained by adding up the number of pieces of evaluation information for the store included in the attribute, and an evaluation aggregate value obtained by aggregating the evaluation values ​​included in the evaluation information into one; an output means for outputting a distribution of the attribute based on the total value and the evaluation aggregate value in a coordinate space having the number of pieces of evaluation information and the evaluation value as coordinate axes; Equipped with The structure is as follows.

[0008] Further, an information processing method according to one aspect of the present invention includes: aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on evaluation information including evaluation values ​​that indicate the degree of evaluation of the store, and calculating, for each attribute set for the store, a total value obtained by adding up the number of pieces of evaluation information for the store included in the attribute and an evaluation aggregate value obtained by aggregating the evaluation values ​​included in the evaluation information into one; outputting the distribution of the attribute based on the total value and the evaluation aggregate value so as to be displayed in a coordinate space having the number of pieces of evaluation information and the evaluation value as coordinate axes; The structure is as follows.

[0009] In addition, a program according to one aspect of the present invention includes: aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on evaluation information including evaluation values ​​that indicate the degree of evaluation of the store, and calculating, for each attribute set for the store, a total value obtained by adding up the number of pieces of evaluation information for the store included in the attribute and an evaluation aggregate value obtained by aggregating the evaluation values ​​included in the evaluation information into one; outputting the distribution of the attribute based on the total value and the evaluation aggregate value so as to be displayed in a coordinate space having the number of pieces of evaluation information and the evaluation value as coordinate axes; Have a computer carry out the process, The structure is as follows. Effect of the Invention

[0010] By being configured as described above, the present invention can make more effective use of evaluation information of products and services. [Brief description of the drawings]

[0011] [Figure 1] 1 is a diagram showing an overall configuration of an information processing system according to a first embodiment of the present invention. [Diagram 2] 2 is a functional block diagram showing a configuration of the management server disclosed in FIG. 1. [Figure 3A] 2 is a diagram showing a process performed by the management server disclosed in FIG. 1; [Figure 3B] 2 is a diagram showing a process performed by the management server disclosed in FIG. 1; [Figure 4] 2 is a diagram showing a process performed by the management server disclosed in FIG. 1; [Diagram 5] 2 is a diagram showing a process performed by the management server disclosed in FIG. 1; [Figure 6] 2 is a diagram showing a process performed by the management server disclosed in FIG. 1; [Figure 7] 2 is a diagram showing a process performed by the management server disclosed in FIG. 1; [Figure 8]2 is a flowchart showing the operation of the management server disclosed in FIG. 1; [Figure 9] FIG. 11 is a diagram showing a process performed by a management server according to the second embodiment of the present invention. [Figure 10] FIG. 11 is a diagram showing a process performed by a management server according to the second embodiment of the present invention. [Figure 11] FIG. 11 is a diagram showing a process performed by a management server according to the second embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] <Embodiment 1> A first embodiment of the present invention will be described with reference to Figures 1 to 8. Figures 1 and 2 are diagrams for explaining the configuration of an information processing system, and Figures 3 to 8 are diagrams for explaining the processing operation of the information processing system.

[0013] [composition] The information processing system of the present invention is for tallying up evaluation information posted on websites such as posting sites, so-called word-of-mouth sites, and search sites. As shown in Fig. 1, the information processing system is composed of a management server 10, a posting site server 20, and a business operator terminal 30, which are connected via a network N. Each component will be described in detail below.

[0014] The posting site server 20 is an information processing device managed by a business that provides a service for disclosing evaluation information, and has established a website such as a posting site on the Internet. In this embodiment, the posting site provided by the posting site server 20 publishes information on stores such as restaurants, and publishes evaluation information posted by users who have used the stores. For example, the evaluation information posted and published by users includes text information in which the users have written evaluations of the stores, and an evaluation value that quantifies the degree of evaluation of the stores by the users. For example, the text information may include keywords related to services and items provided by the stores. For example, if the store is a "pharmacy," keywords include "prescription," "medicine dispensing," and "pharmacist." The evaluation value is set to a value of "0 to 5," for example, and the larger the value, the higher the evaluation. However, the evaluation value may be expressed in any range of values, and may be expressed in any information, not limited to numerical values.

[0015] The evaluation information also includes time information. For example, the time information is information that indicates a time, such as the date when the user used the store or the date when the evaluation information was posted by the user. The time information is included in the evaluation information, for example, by being input together with the evaluation information when the user posts the evaluation information, or by being added by the posting site server 20 when the evaluation information is posted.

[0016] The evaluation information also includes access information that indicates the method by which the user who posted the evaluation information accessed the store. For example, the access information is information that indicates the method by which the user obtained store information, the method by which the user inquired about the store, the method by which the user visited the store, and the like. As an example, the access information includes information such as "website" as the method by which the user obtained store information, "phone" as the method by which the user inquired about the store, and "route guidance" as the method by which the user visited the store. The access information can be added to the evaluation information by the posting site server 20. For example, the posting site server 20 publishes, as access information for the store, the address information of the store's website, the telephone number of the store, and route guidance information on a map to the store, as the store information, on the posting site. When a user logs in to the posting site using his / her own identification information and selects access information for the store, the selected access information is associated with the user's identification information. Then, when the same user subsequently logs in to the posting site and posts evaluation information for the store, the access information associated with the user is added to the evaluation information. However, the access information may be input by the user together with the evaluation information at the time of posting.

[0017] The evaluation information handled by the posting site provided by the posting site server 20 is not limited to information about stores such as pharmacies and restaurants, but may be information about stores of any type, or evaluation information about products or services (objects). Furthermore, the evaluation information is not limited to information about stores or products, but may be information about any object.

[0018] In addition, the number of posting site servers 20 is not limited to one, and there may be multiple posting site servers 20, each of which may have a different posting site. Therefore, evaluation information on the same store may be posted and made public on each posting site established by each posting site server 20.

[0019] Furthermore, the posting site server 20 is not necessarily limited to publishing the evaluation information on a website, etc. For example, the posting site server 20 may be a server that merely sets up a questionnaire site or a payment site and acquires evaluation information from users.

[0020] The business operator terminal 30 is an information processing terminal operated by a person who analyzes evaluation information of a store at a business operator who operates the store. The business operator terminal 30 accesses the management server 10 and displays and analyzes the aggregation results of the evaluation information of the store by the management server 10 as described below.

[0021] In this embodiment, it is assumed that an operator who operates a store operates multiple stores. For example, it is assumed that the operator operates 50 stores, and analyzes the aggregated results of evaluation information for these stores. However, the operator who operates a store may only operate one store, and may analyze the aggregated results of evaluation information for multiple stores including his / her own store and stores of other operators.

[0022] The management server 10 is composed of one or more information processing devices each having a calculation device and a storage device. As shown in FIG. 2, the management server 10 includes an acquisition unit 11, a counting unit 12, and an output unit 13. The functions of the acquisition unit 11, the counting unit 12, and the output unit 13 can be realized by the calculation device executing a program for realizing each function stored in the storage device. The management server 10 also includes an evaluation information storage unit 16. The evaluation information storage unit 16 is composed of a storage device. Each component will be described in detail below.

[0023] The acquisition unit 11 (acquisition means) accesses the posting site server 20, acquires the evaluation information published on each posting site, and stores it in the evaluation information storage unit 16. At this time, the acquisition unit 11 acquires evaluation information for each store from the posting site server 20 and stores it in the evaluation information storage unit 16, distinguishing between each store. At this time, the number of pieces of evaluation information for each store is usually a number greater than one, but if the number of posts is small, the number may be 0 or 1. Note that when there are a plurality of posting site servers 20, the acquisition unit 11 acquires evaluation information for each store from each posting site server 20.

[0024] In this embodiment, multiple stores are operated by the same business operator, and in this case, the acquisition unit 11 pre-stores a store group to which multiple stores are associated. Therefore, the acquisition unit 11 acquires evaluation information corresponding to each of the multiple stores forming the store group from the posting site server 20, and stores the acquired evaluation information in the evaluation information storage unit 16 together for the store group of multiple stores.

[0025] The tallying unit 12 (counting means) tallies the evaluation information stored in the evaluation information storage unit 16. For example, the tallying unit 12 tallies the number of pieces of evaluation information and the evaluation value for each store for the evaluation information of a plurality of stores constituting a predetermined store group. Specifically, the tallying unit 12 first counts and calculates the number of pieces of evaluation information for each store. The tallying unit 12 also calculates the average value of the evaluation values ​​expressed as numerical values ​​for each store, and calculates this as the evaluation tally value. In this way, one piece of evaluation information and one evaluation tally value are generated for each store. However, the evaluation tally value is not limited to being the average value of the evaluation values ​​for each store, and may be a value tallied by any method, such as the most frequently occurring value of the evaluation values ​​for each store, or the average value of evaluation values ​​randomly extracted from the evaluation values ​​for each store.

[0026] The tabulation unit 12 also tabulates the number of pieces of evaluation information and the evaluation value for each attribute according to the attribute set for each store. Here, the store is given an attribute value corresponding to each type of attribute set in advance. The types of attributes include store name, prefecture (location), brand, franchisee, area manager, location, and whether or not there is a parking lot. For this reason, for each type of attribute as described above, information such as the store name, the name of the prefecture where the store is located, the brand name of the store itself, the name of the franchisee who operates the store, the name of the area manager (person in charge) who manages the store, the location status such as downtown or suburbs, and whether or not there is a parking lot are set as attribute values ​​for the store. Note that information unique to a store, such as the store name, may be excluded from the types of attributes. In other words, an attribute may be a characteristic to which multiple stores may belong.

[0027] Then, the counting unit 12 counts the evaluation information of the stores for which the attribute value is set for each attribute type within the attribute type. As an example, for an attribute type such as prefecture, for an attribute such as Tokyo, a total value of the number of pieces of evaluation information and a total evaluation value of the evaluation values ​​included in the evaluation information are calculated based on the evaluation information for all stores for which the attribute of Tokyo is set. As a result, one total value of the number of pieces of evaluation information and one total evaluation value are generated for one attribute, that is, prefecture. Similarly, the counting unit 12 calculates the total value of the number of pieces of evaluation information and the total evaluation value for each attribute, such as for each brand name and each franchisee. Since the store name is also an attribute, the number of pieces of evaluation information and the total evaluation value calculated for each store as described above can be said to be the total value of the number of pieces of evaluation information and the total evaluation value for each attribute.

[0028] Further, the aggregation unit 12 classifies each attribute into a preset evaluation group for each type of attribute based on the total value of the number of evaluation information items and the evaluation aggregation value calculated for each attribute as described above. For example, the evaluation groups are classified according to thresholds set for the total value of the number of evaluation information items and the evaluation aggregation value. As an example, when the type of attribute is a store name, three groups are set, such as "evaluation group A: evaluation aggregation value 3.7 or more, number of evaluation information items: 20 or more", "evaluation group B: evaluation aggregation value less than 3.7, number of evaluation information items: 20 or more", and "evaluation group C: number of evaluation information items: less than 20". In this case, it can be said that the evaluation group A is a group that has a sufficient number of evaluation information items and is judged to have a good evaluation value, the evaluation group B is a group that has a sufficient number of evaluation information items but is judged to have a bad evaluation value, and the evaluation group C is a group that has an insufficient number of evaluation information items and is difficult to evaluate. The evaluation aggregation value and the threshold value for the number of evaluation information items for classifying the evaluation groups can be changed depending on the type of the target attribute, the number of collected evaluation information items, and the evaluation value. For example, if the attribute type is prefecture, multiple stores will belong to each prefecture, and the amount of evaluation information for each prefecture may be large, so the threshold for the number of evaluation information may be set high accordingly.

[0029] The aggregation unit 12 may aggregate the evaluation information for each attribute in advance, or may aggregate the evaluation information for each attribute for the selected attribute type when the type of attribute is selected from the business operator terminal 30, as described below. Furthermore, when a period is set, the aggregation unit 12 may aggregate the evaluation information for the set period based on time information included in the evaluation information. Alternatively, the aggregation unit 12 may aggregate the evaluation information for each preset period, for example, every month. However, the aggregation unit 12 may aggregate the evaluation information for any period and may aggregate at any timing.

[0030] The output unit 13 (output means) outputs the tabulated results as described above to the display device of the business operator terminal 30 for display. Specifically, as shown in FIG. 3A, the output unit 13 displays the distribution of each attribute on the coordinate plane by displaying circles at coordinates corresponding to the total value of the number of evaluation information of each attribute and the evaluation tabulated value on a coordinate plane with the number of evaluation information and the evaluation value as coordinate axes. At this time, the output unit 13 displays an attribute selection field R for selecting the type of attribute on the business operator terminal 30 as shown by the reference character R in FIG. 3. For this reason, the output unit 13 accepts the selection of the type of attribute from the business operator terminal 30 inputted in the attribute selection field R, and displays the distribution of attributes included in the selected type of attribute. For example, in the example of FIG. 3, the type of attribute such as "store" is selected in the attribute selection field R, so the distribution of each store is displayed, and in the example of FIG. 4, the type of attribute such as "prefecture" is selected, so the distribution of each prefecture is displayed based on the tabulation results for each prefecture.

[0031] Furthermore, when displaying the distribution of attributes, the output unit 13 displays the distribution of attributes so that the evaluation group into which each attribute is classified can be identified. For example, the output unit 13 displays each attribute by color for each evaluation group. FIG. 3A shows an example in which the type of attribute is a store, and each store is classified and displayed into three evaluation groups, such as "evaluation group A: evaluation aggregate value 3.7 or more, number of evaluation information: 20 or more", "evaluation group B: evaluation aggregate value less than 3.7, number of evaluation information: 20 or more", and "evaluation group C: number of evaluation information: less than 20". In this case, evaluation group A (Ga) is displayed in black, evaluation group B (Gb) in gray, and evaluation group C (Gc) in white. FIG. 4 shows an example in which the type of attribute is prefectures, and the prefectures are classified into three evaluation groups, such as "evaluation group A: evaluation total value 3.7 or more, number of evaluation information: 300 or more," "evaluation group B: evaluation total value less than 3.7, number of evaluation information: 300 or more," and "evaluation group C: number of evaluation information: less than 300," and are displayed. In this case, the evaluation group A (Ga) is displayed in black, the evaluation group B (Gb) in gray, and the evaluation group C (Gc) in white. Note that the method of displaying the evaluation groups into which each attribute is classified so as to be identifiable is not limited to the above-mentioned color coding, and any method may be used. For example, the output unit 13 may display a line (dotted line in FIG. 3B) corresponding to the above-mentioned threshold value on the coordinate plane as shown in FIG. 3B, and identify the evaluation group by the area divided by the line. The output unit 13 may also identify the evaluation group by color coding of each area by displaying each area divided by the line corresponding to the threshold value on the coordinate plane as shown in FIG. 3B in a different color. When the evaluation groups are identified by color-coding each region, the dotted lines as shown in FIG. 3B do not need to be displayed.

[0032] Furthermore, when an attribute is selected from the business operator terminal 30 on the above-mentioned coordinate plane, the output unit 13 displays information about the store included in the attribute. For example, in the example shown in FIG. 5 where the type of attribute is store, when a circle of a certain store is selected by hovering the mouse over it by the business operator, the output unit 13 displays "AA store AA branch (store name), rating: 3.0 (rating value), number of cases: 87 (number of evaluation information)" as information about the store in a pop-up. In the example shown in FIG. 6 where the type of attribute is prefecture, when a circle of a certain prefecture is selected by hovering the mouse over it by the business operator, the output unit 13 displays "Tokyo (prefecture name), rating: 3.85 (rating value), number of cases: 1050 (total number of evaluation information)" as information about the prefecture in a pop-up. In this case, "rating" and "number of cases" are the total number of evaluation information for all stores belonging to Tokyo, which is the selected prefecture, and the evaluation aggregate value obtained by aggregating the evaluation values. Note that, when multiple stores belong to the selected attribute, information such as the store names of all or some of the stores may be displayed in the pop-up.

[0033] Furthermore, the output unit 13 also displays text information included in the evaluation information for stores included in the selected attribute as information on the selected attribute. For example, when displaying information on the attribute (Tokyo) selected by mouse over as shown in Fig. 6, the output unit 13 displays a link such as "See reviews", which is information for displaying text information. When the link is selected by clicking on the business terminal 30, the output unit 13 displays a list of word-of-mouth information, which is text information for stores belonging to the selected attribute (Tokyo), as shown in Fig. 7. At this time, the list of word-of-mouth information includes the store name of the store to be evaluated, the name of the posting site where the evaluation information was posted, the evaluation value, text information indicating the evaluation content, date and time, the poster's name, etc.

[0034] [Operation] Next, the operation of the above-mentioned information processing system, particularly the operation of the management server 10, will be described mainly with reference to the flowchart of FIG.

[0035] First, in the posting site server 20, evaluation information on shops is posted by users on the posting site and made publicly available to general users.

[0036] The management server 10 periodically or at any timing acquires the evaluation information published on each posting site from the posting site server 20 (step S1). Then, the management server 10 stores the evaluation information acquired from the posting site server 20 for each store.

[0037] After that, the management server 10 aggregates the evaluation information for the set period (step S2). At this time, the management server 10 calculates the total number of evaluation information items and the evaluation aggregate value for each attribute, such as each store or each prefecture, and classifies the attributes into each evaluation group based on the calculated values.

[0038] Then, the management server 10 outputs the evaluation information aggregation result to the business operator terminal 30 for display (step S3). For example, the management server 10 displays the distribution of each attribute based on the total value of the number of evaluation information of each attribute and the evaluation aggregation value for the attribute type selected from the business operator terminal 30. At this time, the management server 10 displays each attribute and a color according to the evaluation group into which the attribute is classified. For example, as shown in FIG. 3A, the distribution of each store is displayed in a different color according to the evaluation group, and as shown in FIG. 4, the distribution of each prefecture is displayed in a different color according to the evaluation group. Note that, when the type of attribute is changed in the attribute selection field R by the business operator terminal 30, the management server 10 displays the distribution of attributes included in the changed attribute type.

[0039] Furthermore, when an attribute is selected on the coordinate plane by the business operator terminal 30 (Yes in step S4), the management server 10 displays information about the stores included in the attribute (step S5). For example, as shown in Fig. 6, when a circle of a prefecture (Tokyo) on the coordinate plane is selected by hovering the mouse over the circle on the business operator terminal 30, the information about the prefecture is displayed in a pop-up, including "Tokyo (name of prefecture), rating: 3.85 (rating value), number of items: 1050 (total number of rating information items)". Furthermore, when "View reviews" displayed in the pop-up is selected by the business operator terminal 30, the management server 10 displays a list of review information, which is text information about stores belonging to the selected attribute (Tokyo), as shown in Fig. 7.

[0040] As described above, in the present invention, the number of pieces of evaluation information and evaluation values ​​are tallied for each attribute of a store from the evaluation information for a plurality of stores, and the tallied results are output as a distribution of attributes. Therefore, business operators can obtain the distribution of evaluations for each attribute of a store, which can be used as a reference for future improvements. As a result, the evaluation information can be used more effectively.

[0041] <Embodiment 2> Next, a second embodiment of the present invention will be described with reference to Figures 9 to 11. Figures 9 to 11 are diagrams for explaining the processing operation of an information processing system.

[0042] The information processing system in this embodiment, particularly the management server 10, has substantially the same configuration as that described in embodiment 1. In addition to this, the management server 10 in this embodiment has the following configuration.

[0043] First, the management server 10 in this embodiment has a function for making it possible to compare the evaluation information of a store belonging to an evaluation group with a good evaluation with the evaluation information of a store belonging to another evaluation group. For example, FIG. 9 shows an example in which the attribute type is prefecture, and shows the distribution of evaluation information for each prefecture. By comparing the evaluation information of a store belonging to a prefecture in evaluation group A with a high evaluation value with the evaluation information of a store belonging to a prefecture in evaluation group B with a low evaluation value, it is possible to provide information on the management, customer service, measures, know-how, etc. of the store belonging to evaluation group A to the store in evaluation group B, and it is considered that the sales amount of the store belonging to evaluation group B can be increased. Alternatively, it is considered that it is possible to identify the differences between the stores belonging to evaluation group A and the stores belonging to evaluation group B, and it is considered that it is possible to improve the stores in evaluation group B from the identified differences and increase the sales amount. From this viewpoint, the management server 10 in this embodiment has the following configuration.

[0044] In this embodiment, the aggregation unit 12 of the management server 10 analyzes the evaluation information for each evaluation group for the stores belonging to the evaluation group, and generates text evaluation information in which text information included in the evaluation information is associated with information based on the evaluation value. In particular, the aggregation unit 12 generates text evaluation information in which keywords included in the text information are associated with the proportions of each category into which the evaluation values ​​are classified, based on the evaluation information.

[0045] Specifically, the counting unit 12 extracts text information and evaluation values ​​included in each evaluation information for a store for each evaluation group, and first extracts preset keywords from the text information. For example, if the store is a "pharmacy," the keywords are, for example, "prescription," "dispensing," and "pharmacist." The counting unit 12 then classifies the evaluation value of the evaluation information including the keyword for each keyword according to the value. For example, a classification threshold for the evaluation value is set in advance, and if the evaluation value is equal to or greater than the classification threshold, the evaluation is classified into a high classification, and if the evaluation value is less than the classification threshold, the evaluation is classified into a low classification. Furthermore, the counting unit 12 calculates, for each evaluation group and for each keyword, the ratio of the high classification to the low classification into which the evaluation value of the evaluation information including the keyword is classified.

[0046] FIG. 10 shows an example of text evaluation information generated for each evaluation group. In this figure, first, 1271 pieces of evaluation information for stores belonging to evaluation group A are extracted, and 1146 pieces of evaluation information for stores belonging to evaluation group B are extracted. Then, distinguishing between evaluation group A and evaluation group B, evaluation information containing the keywords "prescription", "prescription", and "pharmacist" is extracted from the text information of each evaluation information, and it is determined whether the evaluation value of the evaluation information for each keyword is high or low relative to a threshold value, and the ratio of the classification with high evaluation value and the classification with low evaluation value is calculated. In the example of FIG. 10, for the keyword "prescription", the evaluation information for stores belonging to evaluation group A is 83% in the high evaluation category and 17% in the low evaluation category, and the evaluation information for stores belonging to evaluation group B is 79% in the high evaluation category and 21% in the low evaluation category.

[0047] The output unit 13 of the management server 10 in this embodiment outputs the text evaluation information generated as described above to be displayed on the business operator terminal 30, distinguishing between evaluation groups. In particular, the output unit 13 outputs text evaluation information corresponding to the same keyword so as to be displayed so as to be comparable between different evaluation groups. For example, as shown in Fig. 10, the output unit 13 displays the proportions of evaluation classifications for the same keyword side by side for evaluation group A and evaluation group B, thereby making it possible to compare the evaluations.

[0048] Here, in the example of FIG. 10, the evaluations of evaluation group A and evaluation group B are compared. It can be seen that for the keyword "prescription", the ratio of high-rated categories and low-rated categories is about the same. On the other hand, for the keyword "pharmacist", in the evaluation information for the stores belonging to evaluation group A, 75% are high-rated categories and 25% are low-rated categories, while in the evaluation information for the stores belonging to evaluation group B, 29% are high-rated categories and 71% are low-rated categories. Then, when the evaluations of evaluation group A and evaluation group B for the keyword "pharmacist" are compared, it can be seen that the ratio of high-rated categories and low-rated categories is the exact opposite. In other words, it can be seen that the evaluation value of the stores in evaluation group A that include the keyword "pharmacist" tends to be high, while the evaluation value of the stores in evaluation group B that include the keyword "pharmacist" tends to be low.

[0049] Furthermore, the output unit 13 may receive the comparison result, extract evaluation information including the keyword "pharmacist", and output it to the business operator terminal 30. For example, when a predetermined criterion is met, such as the ratio of high evaluation categories and low evaluation categories being opposite between the evaluation groups for the same keyword as described above, the output unit 13 may extract and output evaluation information including the keyword. This allows the business operator to compare evaluation information including the keyword "pharmacist" for stores belonging to evaluation group A with evaluation information including the keyword "pharmacist" for stores belonging to evaluation group B, analyze the differences, and use the results to improve the management of the stores belonging to evaluation group B.

[0050] 10, the evaluation values ​​of evaluation information in which the text information contains the same keywords are compared between evaluation groups, but the evaluation values ​​of evaluation information in which the keywords are not completely the same but contain keywords with the same meaning may also be compared between evaluation groups. Furthermore, the keywords in the text information are not limited to satisfying the criteria of having the same characters or the same meaning, and when the text information satisfies some preset criteria, the evaluation values ​​of evaluation information containing such text information may be compared between evaluation groups.

[0051] The management server 10 may extract evaluation information for each of three or more evaluation groups and compare the evaluation information between the three or more evaluation groups. The management server 10 may also extract evaluation information of stores belonging to a specific evaluation group, such as the highest evaluation group or the lowest evaluation group, from among the classified evaluation groups, and output the information to be presented to the business operator. The management server 10 may also extract information other than evaluation information regarding stores belonging to a specific evaluation group from among the classified evaluation groups. For example, the management server 10 may extract operation information associated with a store belonging to the highest evaluation group and registered in advance, such as customer service methods, purchasing methods, price setting methods, know-how, and the like, and present the information to the business operator.

[0052] The management server 10 in this embodiment further comprises the following configuration. First, the counting unit 12 of the management server 10 counts up the access information included in the evaluation information for stores that belong to attributes classified into each evaluation group. For example, the counting unit 12 classifies the access information included in the evaluation information by type (route guidance, telephone, website, etc.) for each evaluation group, and calculates the ratio of the number of each type to the number of all evaluation information in the evaluation group. At this time, the counting unit 12 may count the access information for evaluation information for a certain period, such as every month. However, any method may be used to count the access information.

[0053] The output unit 13 of the management server 10 in this embodiment outputs the access status of users to stores belonging to each evaluation group, that is, the access information collected as described above, to be displayed on the business operator terminal 30. For example, the output unit 13 may display the number of stores belonging to each evaluation group by month and by each evaluation group, as well as the ratio of each access type to the number of evaluation information, as shown in Fig. 11. In the example of Fig. 11, for stores belonging to evaluation group B in December, it is displayed that, among the users who posted evaluation information, 0.70% used route guidance, 0.28% used the phone, and 0.55% used the website.

[0054] Although the present invention has been described above with reference to the above-mentioned embodiment, the present invention is not limited to the above-mentioned embodiment. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. In addition, at least one or more functions of the above-mentioned acquisition unit 11, aggregation unit 12, output unit 13, and evaluation information storage unit 16 may be executed by an information processing device installed and connected anywhere on a network, that is, they may be executed by so-called cloud computing.

[0055] The above-mentioned program can be stored and supplied to a computer using various types of non-transitory computer readable media. The non-transitory computer readable medium includes various types of tangible storage media. Examples of the non-transitory computer readable medium include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, and semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)). The program may also be supplied to a computer by various types of transitory computer readable media. Examples of the transitory computer readable medium include electric signals, optical signals, and electromagnetic waves. The transitory computer readable medium can supply the program to a computer via a wired communication path such as an electric wire and an optical fiber, or via a wireless communication path.

[0056] <Additional Notes> A part or all of the above-described embodiments can be described as follows: The following provides an overview of the configurations of an information processing system, an information processing method, and a program according to the present invention. However, the present invention is not limited to the following configurations. (Appendix 1) aggregating means for aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on evaluation information including evaluation values ​​that indicate the degree of evaluation of the store, and calculating, for each attribute set for the store, a total value obtained by adding up the number of pieces of evaluation information for the store included in the attribute, and an evaluation aggregate value obtained by aggregating the evaluation values ​​included in the evaluation information into one; an output means for outputting a distribution of the attribute based on the total value and the evaluation aggregate value in a coordinate space having the number of pieces of evaluation information and the evaluation value as coordinate axes; An information processing system comprising: (Appendix 2) 2. An information processing system according to claim 1, the output means receives a selection of the type of attribute and outputs a display of the distribution of the attribute for the selected type of attribute; Information processing system. (Appendix 3) The information processing system according to claim 1 or 2, The aggregation means classifies the attributes into groups based on the total value and the evaluation aggregation value; The output means outputs a distribution of the attribute so as to enable identification of the group. Information processing system. (Appendix 4) 4. An information processing system according to claim 3, the output means outputs the distribution of the attributes in a manner that colors the groups; Information processing system. (Appendix 5) An information processing system according to any one of claims 1 to 4, The output means outputs information of the store included in the selected attribute on the coordinate space so as to display the information. Information processing system. (Appendix 6) 6. The information processing system according to claim 5, the output means outputs, as the information of the store included in the attribute selected on the coordinate space, the evaluation information including text information evaluating the store in text, so as to be displayed; Information processing system. (Appendix 7) An information processing system according to any one of claims 1 to 6, the tallying means classifies the attributes into groups based on the total value and the evaluation tally value, and generates text evaluation information for each group by associating text information that evaluates the stores included in the group in a text manner with information based on the evaluation value for the store, The output means outputs the text evaluation information so as to display the text evaluation information for each of the groups. Information processing system. (Appendix 8) 8. The information processing system according to claim 7, the tallying means generates, for each group, the text evaluation information in which keywords extracted from the text information evaluating the stores included in the group are associated with information based on the evaluation value for the store. Information processing system. (Appendix 9) 9. The information processing system according to claim 8, the tallying means generates, for each group, the text evaluation information in which the keywords extracted from the text information of the stores included in the group are associated with a proportion of each category into which the evaluation values ​​for the stores are classified. Information processing system. (Appendix 10) The information processing system according to claim 8 or 9, the output means outputs the text evaluation information corresponding to the same keyword so as to display the information in a manner that allows comparison between different groups. Information processing system. (Appendix 11) 4. An information processing system according to claim 3, the tallying means acquires access information indicating a method for accessing the store by the user who inputs the evaluation information, and tallying up, for each group, the access information of the stores belonging to the group; the output means outputs the access information separately for each of the groups. Information processing system. (Appendix 12) aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on evaluation information including evaluation values ​​that indicate the degree of evaluation of the store, and calculating, for each attribute set for the store, a total value obtained by adding up the number of pieces of evaluation information for the store included in the attribute and an evaluation aggregate value obtained by aggregating the evaluation values ​​included in the evaluation information into one; outputting the distribution of the attribute based on the total value and the evaluation aggregate value so as to be displayed in a coordinate space having the number of pieces of evaluation information and the evaluation value as coordinate axes; Information processing methods. (Appendix 13) aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on evaluation information including evaluation values ​​that indicate the degree of evaluation of the store, and calculating, for each attribute set for the store, a total value obtained by adding up the number of pieces of evaluation information for the store included in the attribute and an evaluation aggregate value obtained by aggregating the evaluation values ​​included in the evaluation information into one; outputting the distribution of the attribute based on the total value and the evaluation aggregate value so as to be displayed in a coordinate space having the number of pieces of evaluation information and the evaluation value as coordinate axes; A program that causes a computer to execute a process. [Explanation of symbols]

[0057] 10 Management Server 11 Acquisition Department 12 Counting Unit 13 Output section 16 Evaluation information storage unit 20 Posting site server 30 Operator terminal

Claims

1. a counting means for counting the number of pieces of evaluation information and the evaluation values ​​for each store based on the evaluation information including evaluation values ​​that indicate the degree of evaluation of the store; an output means for outputting a distribution of the stores based on the number of pieces of evaluation information and the evaluation values ​​in a coordinate space having the number of pieces of evaluation information and the evaluation values ​​as coordinate axes; An information processing device comprising:

2. 2. The information processing device according to claim 1, the output means outputs, in the coordinate space, a distribution for each attribute based on the number of pieces of evaluation information for each attribute set for the store and the evaluation value, so as to be displayed. Information processing device.

3. 3. The information processing device according to claim 2, The attribute is the store. Information processing device.

4. 4. The information processing device according to claim 2, the output means outputs information on the selected attribute so as to be displayed on the coordinate space. Information processing device.

5. 5. The information processing device according to claim 4, the output means outputs information based on the evaluation information for the store as information on the selected attribute in the coordinate space. Information processing system.

6. The information processing device aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on the evaluation information including evaluation values ​​that indicate the degree of evaluation of the store; outputting the distribution of the stores based on the number of pieces of evaluation information and the evaluation values ​​so as to be displayed in a coordinate space having the number of pieces of evaluation information and the evaluation values ​​as coordinate axes, respectively; Information processing methods.

7. 2. The information processing device according to claim 1, The information processing device, outputting the coordinate space so as to display a distribution for each attribute based on the number of pieces of evaluation information for each attribute set for the store and the evaluation value; Information processing methods.

8. In the information processing device, aggregating the number of pieces of evaluation information and the evaluation values ​​for each store based on the evaluation information including evaluation values ​​that indicate the degree of evaluation of the store; outputting the distribution of the stores based on the number of pieces of evaluation information and the evaluation values ​​so as to be displayed in a coordinate space having the number of pieces of evaluation information and the evaluation values ​​as coordinate axes, respectively; A program that executes a process.

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