JP2006113681A - Reputation information processing apparatus, reputation information processing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a reputation information processing apparatus or the like that enables even reputation attributes with a small number of descriptions within reputation information about one target to reflect public reputation, and that is capable of displaying more appropriate reputation attributes as the characteristics of the one target. <P>SOLUTION: A category present in a reputation information storage medium is presented to the user and reputation information belonging to the category designated by the user is obtained for each target from the reputation information storage medium. The appearance frequency of reputation attributes included in the reputation information is counted. Weight is calculated on the basis of the appearance frequency of the attributes, and is imparted to each of the reputation attributes of each target. An evaluated value for each reputation attribute of each target is calculated with the weight taken into account. The reputation information including the evaluated value is stored in the reputation information storage medium. Of the evaluated values of the reputation attributes, the pieces of reputation information that satisfy display requirements stored in a display requirement storage medium are displayed. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

The present invention relates to an apparatus, a processing method, and a program for processing reputation information described in relation to the reputation of an object.

  A method is known in which reputation information is processed to represent the characteristics of one target thing, and the frequency of reputation attributes of the target thing is tabulated and displayed (see, for example, Patent Document 1 and Non-Patent Document 1).

In the above-described conventional method, as the number of reputation attributes having a good attribute value increases in one target thing, the reputation attribute represents the feature of the target thing.
Japanese Patent No. 3402599 Kenji Tateishi and eight others, “Extracting Opinion Information from Web Documents and Generating Summaries Based on Points of Interest”, Proc. 644-647, March 2004

  The conventional method of evaluating and displaying the reputation attribute of the subject matter is evaluated only by the number of reputation attributes, and does not consider how much the reputation attribute is noticed in the world. Even if the reputation attribute is high, there is a problem that if the number of description of the reputation attribute is small in the reputation information of one target thing, the reputation attribute does not become a feature for the target thing.

  For example, in a given category (for example, automobile), even if reputation attributes (for example, “fuel efficiency”) are regarded as important in the world, if the number of descriptions of “fuel efficiency” is small in the reputation information of a certain automobile product, In the prior art, “fuel consumption” is hardly included as a feature of the automobile product.

  In other words, the above-mentioned conventional example cannot reflect the reputation of the world better if it is a reputation attribute with a small number of descriptions in the reputation information of one target thing, and it is more appropriate as a feature of the target thing. There is a problem that the reputation attribute cannot be displayed.

The present invention can better reflect the reputation of the world even in the case of a reputation attribute with a small number of descriptions in the reputation information of one target thing. An object of the present invention is to provide a reputation information processing apparatus, a reputation information processing method, and a program capable of displaying a message.

  The present invention relates to a device for processing reputation information described in relation to the reputation of a subject matter, category presenting means for presenting a category existing in a reputation information storage medium storing the reputation information to the user, and the category The category designation means for the user to designate one category from the categories presented by the presentation means, and the reputation information belonging to the category specified by the user in the category designation means for each subject matter from the reputation information storage medium. Reputation information acquisition means to be acquired, and the number of appearances of reputation attributes included in the reputation information obtained by the reputation information acquisition means are counted by the reputation attribute appearance count counting means and the reputation attribute appearance count counting means The weight is calculated according to the number of appearances of the received reputation attribute, and the above weight is assigned to each reputation attribute of the subject matter. A weight assigning means, a reputation attribute evaluation value calculating means for calculating an evaluation value for each reputation attribute of each target thing in consideration of the weight given by the weight giving means for each target thing, and the reputation attribute evaluation Reputation information storage means for storing reputation information including the evaluation value calculated by the value calculation means in the reputation information storage medium, and among the evaluation values of the reputation attributes stored by the reputation information storage means, a display condition storage medium And a reputation information display means for displaying reputation information that satisfies the display conditions stored in the reputation information processing apparatus.

  The present invention also relates to a method for processing reputation information described in relation to the reputation of an object, and a category presenting step for presenting a category existing in a reputation information storage medium storing the reputation information to a user, The category designation step in which the user designates one category from the categories presented in the category presentation step and stores it in the memory, and the reputation information belonging to the category specified by the user in the category designation step is stored in the reputation information storage. Reputation information acquisition step for each target thing from the medium and stored in the memory, and the number of appearances of the reputation attribute included in the reputation information obtained by the above reputation information acquisition step, and the reputation attribute stored in the memory Calculated by the appearance count tabulation step and the reputation attribute appearance count tabulation step In accordance with the number of appearances of the size attribute, the weight is calculated, the weight is given to each reputation attribute of the target thing, and the weight given in the memory and the weight given by the weight giving step are considered, For each reputation attribute of each target thing, an evaluation value is calculated and stored in a reputation attribute evaluation value calculating step, and reputation information including the evaluation value calculated by the above-mentioned reputation attribute evaluation value calculating step is stored as reputation information Of the reputation information storage step stored in the medium and the evaluation value of the reputation attribute stored in the reputation information storage step, the reputation information satisfying the display condition stored in the display condition storage medium is displayed and stored in the memory A reputation information processing method comprising: a reputation information display step.

Furthermore, the present invention relates to a category presenting procedure for presenting a category existing in a reputation information storage medium storing the reputation information to a user in a program for processing reputation information described in relation to the reputation of the subject matter, The category designation procedure in which the user designates one category from the categories presented by the category presentation procedure and stores it in the memory, and the reputation information belonging to the category specified by the user in the category designation procedure is stored in the reputation information storage. Reputation information acquisition procedure for each target thing from the medium and stored in the memory, and the reputation attribute stored in the memory by counting the number of appearances of the reputation attribute included in the reputation information obtained by the above reputation information acquisition procedure Depending on the number of appearance counts and the number of appearances of reputation attributes calculated by the above reputation attribute counts The weight is calculated, the weight is assigned to each reputation attribute of the target thing, and the weight assignment procedure stored in the memory and the weight given by the weight assignment procedure are considered, and the reputation attribute of each target thing is determined. A reputation attribute evaluation value calculating procedure for calculating an evaluation value and storing it in a memory, and a reputation information storing procedure for storing reputation information including the evaluation value calculated by the reputation attribute evaluation value calculating procedure in a reputation information storage medium A reputation information display procedure for displaying reputation information satisfying the display condition stored in the display condition storage medium among the evaluation values of the reputation attribute stored by the reputation information storage procedure and storing the reputation information in the memory. It is a program to be executed.

According to the present invention, even in the case of reputation information with a small number of descriptions in one target object, it is possible to better reflect the degree of attention in the world of reputation attributes in that category, and the characteristics of the target object As a result, it is possible to display a reputation attribute reflecting the opinion of the world.

  The best mode for carrying out the invention is the following examples.

  FIG. 1 is a block diagram illustrating a reputation information processing apparatus 100 that is Embodiment 1 of the present invention.

  The reputation information processing apparatus 100 includes a reputation information storage medium 10, a communication means 20, a category presentation means 30, a category designation means 40, a reputation information acquisition means 50, a reputation attribute evaluation value giving means 60, and a reputation information storage. Means 70, reputation information storage medium 80 with reputation attribute evaluation value, reputation information display means 90, and display condition storage medium A.

  The category presenting means 30 presents the category stored in the reputation information storage medium 10 in which the reputation information is stored to the user through the communication means 20. Here, it is presented through the communication means 20, but when the reputation information processing apparatus 100 is one computer apparatus and the reputation information storage medium 10 is provided therein, it is not necessary to communicate. Also in the first embodiment and the second embodiment described later, there is no need to communicate if there is no storage medium at a distance.

  In addition, when the category presenting means 30 presents a category, the category may be displayed on the display and presented, or the category may be presented by voice.

  The user designates one category from the categories presented by the category presentation unit 30 via the category designation unit 40.

  The reputation information acquisition means 50 receives the reputation information belonging to the category designated by the user via the category designation means 40 from the reputation information stored in the reputation information storage medium 10 via the communication means 20 for each subject matter. To get to.

  Note that the “target object” is an object of reputation that belongs to a certain category. For example, if the category is an automobile or a notebook computer, it is a specific product name. Here, the reputation object is an object, but not limited to this, any object that can be evaluated by a person, such as a person, an organization, or a restaurant, may be considered as an object.

  The reputation attribute evaluation value assigning means 60 includes a reputation attribute appearance count totaling means 61, a weight assigning means 62, and a reputation attribute evaluation value calculating means 63.

  The reputation attribute appearance count counting means 61 counts the number of appearances of reputation attributes included in the reputation information. The “reputation attribute” is a property of the target thing used when the target thing is evaluated, and includes fuel consumption, design, speed, price, and the like.

  The weight assigning means 62 assigns a weight to the reputation attribute in consideration of the number of appearances of the reputation attribute. In addition, the reputation attribute is weighted in consideration of the appearance frequency of the reputation attribute and the attribute value. Note that the above “attribute value” is a subjective expression used when evaluating the object, and is good, normal, bad, and the like.

  The reputation attribute evaluation value calculation means 63 calculates the evaluation value of the reputation attribute in consideration of the weight related to the reputation attribute for each reputation attribute of each target thing.

  The reputation information storage means 70 sends the reputation information including the evaluation value of the reputation attribute of each target thing given by the reputation attribute evaluation value giving means 60 through the communication means 20 and the reputation information storage medium with reputation attribute evaluation value. Store to 80.

  The reputation information display means 90 displays, through the communication means 20, the reputation information that satisfies the conditions related to the display stored in the display condition storage medium A among the evaluation values of the reputation attributes stored by the reputation information storage means 70. . Here, the “conditions related to display (display conditions)” are, for example, the number of reputation attributes, the maximum value and the minimum value of evaluation values assigned to reputation attributes, and the like. The reputation information display unit 90 includes a display condition designating unit 91. In the display condition designating means 91, the user designates the display conditions, and the display conditions are stored in the display condition storage medium A through the communication means 20.

  Next, the operation of the reputation information processing apparatus 100 will be described.

  FIG. 2 is a flowchart showing the operation of the reputation information processing apparatus 100 when weights are given based only on reputation attributes.

  First, the category presenting means 30 presents the categories existing in the reputation information stored in the reputation information storage medium 10 through the communication means 20 (S1), and the user designates the category designation means 40 from the presented categories. One category is specified and stored in the memory (S2), and the reputation information acquisition unit 50 acquires the reputation information of the specified category from the reputation information storage medium 10 through the communication unit 20 for each target matter. Store in the memory (S3).

  Reputation attribute appearance count totaling means 61 counts the number of appearances of reputation attributes included in the reputation information and stores them in a memory (S4), and weight assigning means 62 sets the weight of the reputation attribute as the frequency of the reputation attribute as a whole. The weight is assigned to each reputation attribute of the thing and stored in the memory (S5). The reputation attribute evaluation value calculation means 63 calculates the sum of the weights as the evaluation value for each reputation attribute of each target thing and stores it in the memory (S6), and the reputation information storage means 70 obtains the evaluation value of the reputation attribute. The included reputation information is stored in the reputation information storage medium with reputation value evaluation value 80 through the communication means 20 (S7).

  Then, the display condition is specified by the display condition specifying means 91, and the reputation condition display condition is stored in the display condition storage medium A through the communication means 20 (S8). The reputation attribute satisfying the display condition of the reputation information stored in the display condition storage medium A and its reputation information are extracted from the reputation information storage medium 80 with reputation attribute evaluation value through the communication means 20, and the reputation information display means 90 The reputation information is displayed and stored in the memory (S9).

  Next, the above operation will be described more specifically.

  FIG. 3 is a diagram illustrating a specific example of reputation information stored in the reputation information storage medium 10 in the first embodiment.

  In the example illustrated in FIG. 3, the reputation information is information including four types of information, that is, a category, a target thing, a reputation attribute, and an attribute value.

  Note that, for example, the target things and reputation attributes may be hierarchized, and the types thereof may be increased as compared to the example illustrated in FIG. In addition, various contents can be considered depending on the category, such as the subject matter, reputation attribute, and attribute value.

  It should be noted that the reputation information may be automatically captured from the Web, for example, from a bulletin board related to the subject matter, using a method known in Patent Literature 1, Non-Patent Literature 1, or the like. It may be created manually from a questionnaire survey or the like.

  In S1 shown in FIG. 2, the category presenting means 30 presents the category existing in the reputation information stored in the reputation information storage medium 10 through the communication means 20, but in the example shown in FIG. "There is only", so "Automobile" is presented. If a plurality of categories are stored in the reputation information storage medium 10, all categories are presented.

  In S2 shown in FIG. 2, the user designates one category from the presented categories, but in the first embodiment, since there is only one category of “automobile”, “automobile” is designated. If a plurality of categories are presented, the user selects one category from them.

  In S <b> 3 shown in FIG. 2, the reputation information acquisition unit 50 acquires the specified category of reputation information from the reputation information storage medium 10 for each target thing through the communication unit 20. In the first embodiment, in addition to the reputation information shown in FIG. 3, it is assumed that all the reputation information related to the category “automobile” has been acquired. In the following, description will be given focusing on “product A” and “product B”. .

  In S4 illustrated in FIG. 2, the reputation attribute appearance count totaling unit 61 counts the number of appearances of the reputation attribute for each reputation attribute for all target items belonging to the category designated by the user. In other words, the reputation attributes of all the target matters included in the category to which the target thing belongs are not totaled, but only the reputation attributes in the target thing the user is paying attention to.

  FIG. 4 is a diagram illustrating an example of counting reputation attributes according to the first embodiment.

  In the first embodiment, for example, the total result shown in FIG. 4, that is, “fuel consumption” is 200 times, “design” is 20 times, etc. Suppose that it was obtained from the reputation information.

  In S5 shown in FIG. 2, the weight assigning means 62 sets the weight as the reputation attribute overall frequency and assigns the weight to the reputation attribute. In the first embodiment, the frequency of the entire reputation attribute is assumed as the “weight”. However, other weighting methods may be used as long as the weight reflects the frequency number of each reputation attribute, such as a ratio of frequency numbers. You may make it employ | adopt. In other words, the weight may be calculated according to the appearance, such as calculating the weight based on the ratio of the number of appearances without using the number of appearances itself for calculating the weight.

  FIG. 5 is a diagram illustrating a result of assigning the weight of the reputation attribute to all the reputation attributes of each target thing when the example of the count of appearances of the reputation attribute illustrated in FIG. 4 is used in the first embodiment.

  In S6 shown in FIG. 2, the reputation attribute evaluation value calculation means 63 calculates the sum of the weights as the evaluation value for each evaluation attribute of each target thing. That is, in Example 1, the evaluation value of the reputation attribute of “design” of “product A” is, for example, 20 + 20 = 40 from the result of weighting shown in FIG. The evaluation value of the reputation attribute of “50 + 50 = 100”.

  FIG. 6 shows evaluation values related to the reputation attributes of “product A” and “product B”, calculated from the weighting result shown in FIG.

  In the first embodiment, the above-mentioned “total weight” is assumed as the reputation attribute evaluation value. However, if the calculation method reflects the weight, other calculation methods such as multiplying all the weights may be used. You may make it employ | adopt.

  In S7 shown in FIG. 2, the reputation information storage unit 70 stores the reputation information including the evaluation value of the reputation attribute in the reputation information storage medium 80 with the evaluation value of the reputation attribute through the communication unit 20. In the first embodiment, the reputation information shown in FIG. 3 includes the evaluation value of the reputation attribute of each object shown in FIG. 6 and is stored in the reputation information storage medium 80 with the evaluation value of the reputation attribute.

  In S <b> 8 shown in FIG. 2, reputation information display conditions are designated by the display condition designation means 91 and stored in the display condition storage medium A through the communication means 20. In the first embodiment, “display the top four reputation attributes of evaluation values” is set as a display condition. The display condition is not limited to this example, and any display condition may be used, such as “display a reputation attribute with an evaluation value of 3 digits or more”. This display condition is stored in the display condition storage medium A. In addition, the display condition may be stored in advance in the display condition storage medium A as a default value. In this case, the display condition designating unit 91 may not specify the display condition.

  In S9 shown in FIG. 2, the reputation information satisfying the display condition stored in the display condition storage medium A is extracted from the reputation information storage medium 80 with the evaluation value of the reputation attribute through the communication means 20, and the reputation information display means 90 indicate.

  FIG. 7 is a diagram illustrating a display example 1 of reputation status for each target object in the first embodiment.

  In the first embodiment, since “displaying the top four reputation attributes of evaluation values” is a display condition, for example, reputation information shown in FIG. 7 is displayed. That is, since the “top four reputation attributes” regarding “product A” are “price”, “fuel consumption”, “safety”, and “speed”, these are displayed. In FIG. 7, the reputation attribute and the evaluation value are displayed as the “reputation status”, but if the display condition stored in the display condition storage medium A is satisfied, the evaluation value is displayed in a graph. For example, various other display methods may be used. In the display example 1 shown in FIG. 7, the evaluation of the reputation attribute of the product becomes higher as the reputation attribute appears more frequently in the category. Therefore, many people pay attention in the category, and among the products. It is possible to know the reputation attributes that are attracting attention.

  That is, in the first embodiment, the category presenting unit 30 presents the category existing in the reputation information storage medium 10 to the user through the communication unit 20 as described above, and the category designation unit 40 allows the user to select one category. The reputation information acquisition means 50 acquires the reputation information belonging to the category specified by the user from the reputation information stored in the reputation information storage medium 10 through the communication means 20 for each subject matter. The attribute appearance count totaling means 61 counts the number of appearances of the reputation attribute included in the reputation information, and the weight assigning means 62 assigns a weight to the reputation attribute in consideration of the appearance count of the reputation attribute. The evaluation value calculation means 63 calculates the evaluation value of the reputation attribute for each reputation attribute of each target object in consideration of the weight related to the reputation attribute, and the reputation information storage means 70 calculates the reputation attribute storage means 70. The reputation information including the evaluation value of the reputation attribute is stored in the reputation information storage medium 80 with the evaluation value of the reputation attribute through the communication means 20, and the reputation information display means 90 includes the display condition among the evaluation values of the reputation attribute. Reputation information that satisfies the display conditions stored in the storage medium A is displayed through the communication means 20.

  Alternatively, the user may specify the display condition via the display condition specifying unit 91 and store the display condition in the display condition storage medium A through the communication unit 20.

As a result, the evaluation value of the reputation attribute of the target object can be calculated so that the degree of importance becomes higher as the reputation attribute attracting public attention in the category. Further, when the user designates the display condition, the reputation attribute of each target thing reflecting the degree of attention in the world can be displayed by the display method desired by the user. For example, a user who does not know well about the reputation attribute of the category can easily know the reputation attribute that is attracting attention in the world and has become a topic for each product.

  FIG. 8 is a flowchart showing the second embodiment which is another operation in the reputation information processing apparatus 100.

  The flowchart shown in FIG. 8 is an operation for calculating the weight of each reputation attribute using the attribute value in addition to the reputation attribute when calculating the weight of the reputation attribute. That is, the flowchart shown in FIG. 8 is basically the same as the flowchart shown in FIG. 2, and is a flowchart in which step S15 is provided instead of step S5 in FIG.

  In S15, the weight assigning means 62 calculates a weight based on the reputation attribute and the attribute value, and when the attribute value of the reputation attribute is “bad”, a value obtained by multiplying the frequency (number of appearances) of the entire reputation attribute by minus 1. If the attribute value is “good”, on the other hand, the value obtained by multiplying the frequency of the overall reputation attribute by plus 1 (that is, the frequency of the reputation attribute itself as the weight) The weight is given and stored in the memory.

  In the second embodiment shown in FIG. 8, the “weight” is assumed to be a binary value, that is, a minus value and a plus value added to the attribute value value. It may be changed. For example, when the attribute value is “bad”, “normal”, and “good”, when the attribute value of the reputation attribute is “bad”, the frequency (number of appearances) of the reputation attribute is multiplied by minus 1. When the attribute value is “normal”, the value obtained by multiplying the frequency of the entire reputation attribute by 0 is used as the weight. When the attribute value is “good”, the frequency obtained by multiplying the frequency of the entire reputation attribute by 1 is added. A weight may be used (that is, the frequency of the reputation attribute itself may be used as a weight), and the weight may be assigned to each reputation attribute of the target thing.

  That is, when weighting the reputation attribute of the target thing, other methods may be adopted as long as the reputation attribute and the attribute value are used. In the case of this example, from FIG. 3, the “fuel consumption” of “product A” is “good”, and the weight is 200 based on the counting result shown in FIG. 4. On the other hand, among the “designs” of “product A”, “bad” is −20 based on the total result shown in FIG.

  FIG. 9 is a diagram illustrating a case where a weight is calculated for each reputation attribute of each target thing using a reputation attribute and an attribute value.

  In S6 in FIG. 8, the reputation attribute value calculating means 63 calculates the sum of the weights as the evaluation value for each reputation attribute of each target thing. In the example shown in FIG. 9, for example, 20-20 = 0 is calculated from FIG. 9 as the “design” weight of “product A”, and 15 + 15 = as the “size” weight of “product A”. 30 is calculated.

  FIG. 10 is an example showing an evaluation value for each reputation attribute of each target thing calculated using the attribute value in the second embodiment.

  In S <b> 7 in FIG. 8, the reputation information storage unit 70 stores the reputation information including the evaluation value of the reputation attribute in the reputation information storage medium 80 with the evaluation value of the reputation attribute through the communication unit 20. In the second embodiment, the reputation information shown in FIG. 3 includes the evaluation value of the reputation attribute of each object shown in FIG. 10 and is stored in the reputation information storage medium 80 with the evaluation value of the reputation attribute.

  In S8 shown in FIG. 8, a display condition of reputation information is specified via the display condition specifying means 91, and stored in the display condition storage medium A via the communication means 20. In the second embodiment, it is assumed that the display condition “display the top four reputation attributes of the evaluation value” is stored as a default value. First, the user does not specify the display condition and remains as it is. Next, a case where the display condition is satisfied will be described. Next, the user sets the display condition as “displaying a reputation attribute whose reputation attribute number is 50 or less and its evaluation value is 0 in the category” as a display condition. The case where it is specified will be described.

  In S9 shown in FIG. 8, the reputation information satisfying the display condition stored in the display condition storage medium A is extracted from the reputation information storage medium 80 with the evaluation value of the reputation attribute through the communication means 20, and the reputation information display means 90 indicate.

  FIG. 11 is a diagram illustrating a display example 2 of reputation status for each target matter in the second embodiment.

  In the example of the first display condition, “displaying the top four reputation attributes of the evaluation value” is the display condition. For example, the reputation information shown in FIG. 11 is displayed. That is, regarding “product A”, since “top four reputation attributes” are “price”, “fuel consumption”, “safety”, and “size”, these are displayed. In the case of the example shown in FIG. 11, the attribute value of the reputation attribute that frequently appears in the category has a higher score, for example, a reputation attribute that many people are interested in, and You can know the reputation attributes that have been evaluated as “good” in the product.

  FIG. 12 is a diagram illustrating a display example 3 of reputation status for each target matter in the second embodiment.

  Next, when the user designates “display a reputation attribute whose reputation attribute count is 50 or less and its evaluation value is 0” as a display condition in the category, for example, as shown in FIG. Reputation information is displayed. That is, “design” is displayed for “product A” and “silence” is displayed for “product B”.

  In the example shown in FIG. 12, it is possible to know what reputation attribute is a reputable attribute that is not so important in the category and whose opinion is broken in the product.

  That is, in the second embodiment, as described above, the category presenting unit 30 presents the category existing in the reputation information storage medium 10 to the user through the communication unit 20, and the category specifying unit 40 allows the user to select one category. The reputation information acquisition means 50 acquires the reputation information belonging to the category specified by the user from the reputation information stored in the reputation information storage medium 10 through the communication means 20 for each subject matter, The reputation attribute appearance count totaling means 61 counts the number of appearances of the reputation attribute included in the reputation information, and the weight assigning means 62 assigns a weight to the reputation attribute in consideration of the appearance count and attribute value of the reputation attribute. Then, the reputation attribute evaluation value calculation means 63 calculates the evaluation value of the reputation attribute for each reputation attribute of each target thing in consideration of the weight related to the reputation attribute, and the reputation information storage means 70 Reputation information including the evaluation value of the reputation attribute of each object is stored in the reputation information storage medium 80 with the evaluation value of the reputation attribute through the communication means 20, and the reputation information display means 90 includes the evaluation value of the reputation attribute. The reputation information that satisfies the display-related conditions stored in the display condition storage medium A is displayed through the communication means 20. Further, the user can specify display conditions via the display condition specifying means 91, and the conditions can be stored in the display condition storage medium A via the communication means 20.

  As a result, the reputation value of the subject matter can be calculated so that the importance of the reputation attribute having a higher attribute value is attracting attention in the world. Further, when the user designates the display condition, the reputation attribute of each target thing reflecting the degree of attention in the world can be displayed by the display method desired by the user. This is because, for example, it is easy to know, for each product, reputation attributes that are attracting attention and highly evaluated in the world, and conversely, they are not attracting much attention in the world and are pros and cons of the product It is also possible to know the reputation attribute that has become an unimportant reputation attribute. Moreover, even if the reputation attribute is the same, the evaluation value is different for each subject matter, so that the feature of the subject matter can be expressed simply by the reputation attribute.

  The first and second embodiments can be understood as a program invention.

  That is, in the first embodiment, in the program for processing the reputation information described regarding the reputation of the target thing, the category presenting procedure for presenting the category existing in the reputation information storage medium storing the reputation information to the user, The category designating procedure in which the user designates one category from the categories presented by the category presenting procedure and stores it in the memory, and the reputation information belonging to the category specified by the user in the category designating procedure, Reputation information acquisition procedure acquired for each target thing from the information storage medium and stored in the memory, and the number of appearances of reputation attributes included in the reputation information obtained by the above reputation information acquisition procedure are totalized and stored in the memory Reputation attribute appearance count counting procedure, and the number of appearances of reputation attribute calculated by the above reputation attribute appearance count counting procedure Accordingly, a weight is calculated, the weight is assigned to each reputation attribute of the target thing, and the weight assignment procedure stored in the memory and the weight given by the weight assignment procedure are considered, and the reputation attribute of each target thing A reputation attribute evaluation value calculation procedure for calculating an evaluation value for each time and storing it in a memory, and reputation information including reputation information including the evaluation value calculated by the reputation attribute evaluation value calculation procedure in a reputation information storage medium And a reputation information display procedure for displaying reputation information satisfying the display condition stored in the display condition storage medium among the evaluation values of the reputation attributes stored by the reputation information storage procedure and storing the reputation information in the memory. It is an example of the program which makes a computer run.

  Further, the reputation information display procedure may include a display condition designation procedure in which the user designates display conditions, and a procedure for displaying reputation attributes that satisfy the display condition designated by the user.

  The second embodiment is an example of a program that is a procedure for calculating a weight in consideration of the attribute value of a reputation attribute in the weighting procedure. Like the first embodiment, the second embodiment includes a procedure for displaying the reputation information. FIG. 11 is an example of a program that causes a computer to execute a procedure for displaying a reputation attribute that satisfies a display condition specified by a user, including a display condition specifying procedure for a user to specify a display condition.

In the first and second embodiments, the category presentation procedure, the reputation information acquisition procedure, the reputation information storage procedure, and the reputation information display procedure include a communication procedure, and a program that communicates with a remote storage medium. There may be.

It is a block diagram which shows the reputation information processing apparatus 100 which is Example 1 of this invention. It is a flowchart which shows operation | movement of the reputation information processing apparatus 100 when attaching a weight based only on a reputation attribute. 5 is a diagram illustrating a specific example of reputation information stored in a reputation information storage medium 10 in Embodiment 1. FIG. It is a figure which shows the example of totalization of the reputation attribute in Example 1. FIG. FIG. 5 is a diagram illustrating a result of assigning weights of reputation attributes to all reputation attributes of each target thing when the example of counting the number of appearances of reputation attributes illustrated in FIG. 4 is used in Example 1. In Example 1, it is the evaluation value regarding each reputation attribute of "product A" and "product B" calculated from the weighting result shown in FIG. In Example 1, it is a figure which shows the example 1 of a display of the reputation condition for every target thing. 12 is a flowchart illustrating a second embodiment which is another operation in the reputation information processing apparatus 100. It is a figure which shows the case where a weight is calculated to each reputation attribute of each target thing using a reputation attribute and an attribute value. In Example 2, it is an example which shows the evaluation value for every reputation attribute of each target thing calculated also using the attribute value. In Example 2, it is a figure which shows the example 2 of a display of the reputation condition for every target thing. In Example 2, it is a figure which shows the example 3 of a display of the reputation condition for every target thing.

Explanation of symbols

100 ... Reputation information processing device,
10 ... Reputation information storage medium,
20. Communication means,
30 ... category presentation means,
40 ... category designation means,
50 ... Reputation information acquisition means,
60: Reputation attribute evaluation value giving means,
61. Reputation attribute appearance count counting means,
62 ... weighting means,
63 ... reputation attribute evaluation value calculation means,
70 ... Reputation information storage means,
80. Reputation information storage medium with evaluation value of reputation attribute,
90 ... Reputation information display means,
91: Display condition specifying means,
A: Display condition storage medium.

Claims (12)

In a device that processes reputation information that describes the reputation of the subject matter,
Category presenting means for presenting to a user a category that exists in the reputation information storage medium in which the reputation information is stored;
Category designation means for the user to designate one category from the categories presented by the category presentation means;
Reputation information acquisition means for acquiring reputation information belonging to the category specified by the user in the category specifying means for each object from the reputation information storage medium;
A reputation attribute appearance count counting means for counting the number of appearances of reputation attributes included in the reputation information obtained by the reputation information acquisition means;
A weighting means for calculating a weight according to the number of appearances of the reputation attribute counted by the reputation attribute appearance count counting means and assigning the weight to each reputation attribute of the target thing;
A reputation attribute evaluation value calculating means for calculating an evaluation value for each reputation attribute of each target thing in consideration of the weight given by the weight giving means for each target thing;
Reputation information storage means for storing reputation information including the evaluation value calculated by the reputation attribute evaluation value calculation means in a reputation information storage medium;
Reputation information display means for displaying reputation information satisfying the display conditions stored in the display condition storage medium among the evaluation values of the reputation attributes stored by the reputation information storage means;
A reputation information processing apparatus characterized by comprising: In claim 1,
A reputation information processing apparatus characterized in that the weighting means is means for calculating a weight in consideration of an attribute value of a reputation attribute. In claim 1,
A reputation information processing apparatus, wherein the reputation information display means includes display condition designation means for a user to designate display conditions, and displays reputation information satisfying a display condition designated by the user. In claim 1,
A reputation information processing apparatus comprising a communication means provided in the category presentation means, the reputation information acquisition means, the reputation information storage means, and the reputation information display means to communicate with a remote storage medium. In a method of processing reputation information that is written about the reputation of a subject matter,
A category presenting step for presenting a category to a user that exists in the reputation information storage medium in which the reputation information is stored;
A category designation step in which the user designates one category from the categories presented in the category presentation step and stores it in the memory;
Reputation information acquisition step of acquiring reputation information belonging to the category specified by the user in the category specifying step for each target matter from the reputation information storage medium and storing it in a memory;
A reputation attribute appearance count totaling step that counts the number of appearances of reputation attributes included in the reputation information obtained by the reputation information acquisition step and stores it in a memory;
A weighting step of calculating a weight according to the number of appearances of the reputation attribute tabulated by the reputation attribute appearance count tabulation step, assigning the weight to each reputation attribute of the target thing, and storing the weight in a memory;
A reputation attribute evaluation value calculating step of calculating an evaluation value for each reputation attribute of each target object in consideration of the weight given by the weighting step, and storing it in a memory;
A reputation information storage step of storing reputation information including the evaluation value calculated in the reputation attribute evaluation value calculation step in a reputation information storage medium;
A reputation information display step of displaying reputation information satisfying the display condition stored in the display condition storage medium among the evaluation values of the reputation attributes stored in the reputation information storage step, and storing the reputation information in a memory;
A reputation information processing method characterized by comprising: In claim 5,
A reputation information processing method, wherein the weighting step is a step of calculating a weight in consideration of an attribute value of a reputation attribute. In claim 5,
A reputation information processing method, wherein the reputation information display step includes a display condition designation step in which a user designates a display condition, and displays reputation information that satisfies a display condition designated by the user. In claim 5,
A reputation information processing method comprising a communication step in the category presentation step, the reputation information acquisition step, the reputation information storage step, and the reputation information display step to communicate with a storage medium in a remote place. In a program that processes reputation information that describes the reputation of the subject matter,
A category presenting procedure for presenting a category to a user that exists in the reputation information storage medium storing the reputation information;
A category designation procedure in which the user designates one category from the categories presented by the category presentation procedure and stores it in the memory;
Reputation information acquisition procedure for acquiring reputation information belonging to the category specified by the user in the category specifying procedure for each target thing from the reputation information storage medium;
A total number of appearances of reputation attributes included in the reputation information obtained by the above reputation information acquisition procedure, and a total number of reputation attribute appearances totaling procedure stored in a memory;
A weighting procedure for calculating a weight according to the number of appearances of the reputation attribute tabulated by the reputation attribute appearance count tabulation procedure, assigning the weight to each reputation attribute of the subject matter, and storing the weight in a memory;
Reputation attribute evaluation value calculation procedure for calculating an evaluation value for each reputation attribute of each target object in consideration of the weight given by the weighting procedure and storing it in a memory;
A reputation information storage procedure for storing reputation information including the evaluation value calculated by the reputation attribute evaluation value calculation procedure in a reputation information storage medium;
A reputation information display procedure for displaying reputation information satisfying a display condition stored in a display condition storage medium among evaluation values of reputation attributes stored by the reputation information storage procedure, and storing the reputation information in a memory;
A program that causes a computer to execute. In claim 9,
A program characterized in that a weight is calculated in consideration of an attribute value of a reputation attribute in the weighting procedure. In claim 9,
A program characterized in that the reputation information display procedure includes a display condition designating procedure in which a user designates a display condition, and displays reputation attributes that satisfy a display condition designated by the user. In claim 9,
A program characterized by including a communication procedure in the category presentation procedure, the reputation information acquisition procedure, the reputation information storage procedure, and the reputation information display procedure, and communicating with a storage medium at a remote location.

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