Object evaluation processing method and device, and merchant evaluation presentation method and device

Abstract

The disclosed embodiments disclose an object evaluation processing method and device, as well as a merchant evaluation presentation method and device. The object evaluation processing method not only considers the user's rating of the object, but also considers the user's evaluation of the object and the object's feedback on the user's evaluation, thereby expanding the dimension of object evaluation, expanding the evaluation distinction between objects, and improving the impact of the rating and evaluation on the object as a whole. The processing of the rating and evaluation by the user and the object will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object are more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to the user identifying the rating and evaluation of each dimension of the object.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to an object evaluation processing method and device, and a merchant evaluation presentation method and device. Background Art

[0002] When online shopping platforms in related art rate merchants, they generally use the average score of merchant ratings over a longer period of time (e.g., 90 days) as the merchant rating (e.g., 1-2 points: bad rating, 3 points: medium rating, 4-5 points: good rating). Under the rating processing method in related art, the following problems may occur:

[0003] 1) 70% of merchants have a rating of 4.5 or above, and there is little difference between merchants;

[0004] 2) The overall impact of the rating on merchants is not obvious;

[0005] 3) The rating remains unchanged after the negative review is deleted;

[0006] 4) There are new positive reviews recently but the rating has not increased.

[0007] Taking all the above issues into consideration, the relevant technologies are not accurate enough in rating merchants, making it difficult for merchants to influence the ratings, and it is not conducive to user identification. Summary of the invention

[0008] In order to solve the problems in the related art, the embodiments of the present disclosure provide an object evaluation processing method and device, and a merchant evaluation presentation method and device.

[0009] In a first aspect, an embodiment of the present disclosure provides an object evaluation processing method, comprising:

[0010] Obtain the user's first rating of the object within a preset time range, the user's evaluation of the object, and the object's feedback on the user's evaluation;

[0011] Based on whether the first rating of the object by the user within the preset time range meets the preset rating standard, determine a first weight of the first rating of the object by the user within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation;

[0012] Based on the first weight, a first score of the object given by the user is weighted to obtain a first weighted value; based on the second weight, a second weighted value is weighted to obtain a second weighted value; based on the third weight, a feedback of the object on the user's evaluation is weighted to obtain a third weighted value; and the first weighted value, the second weighted value and the third weighted value are summed to calculate a second score of the object as an overall score of the object within a preset time range;

[0013] Provide the user's first score for the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall score.

[0014] In combination with the first aspect, in a first implementation of the first aspect of the present disclosure, the first rating of the object by the user includes the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user, and the first weight includes a first sub-weight of the rating of the object itself by the user, a second sub-weight of the rating of the product of the object by the user, and a third sub-weight of the rating of the packaging of the product of the object by the user,

[0015] The step of performing weighted calculation on the first score given to the object by the user based on the first weight to obtain a first weighted value includes:

[0016] Calculating a weighted score of the object by the user based on the score of the object by the user and the first sub-weight;

[0017] Calculate a weighted score of the product of the object by the user based on the score of the product of the object by the user and the second sub-weight;

[0018] Calculate a weighted score of the packaging of the product of the object by the user based on the score of the packaging of the product of the object by the user and the third sub-weight;

[0019] The first weighted value is calculated based on the weighted score of the object itself given by the user, the weighted score of the product of the object given by the user, and the weighted score of the packaging of the product of the object given by the user,

[0020] The providing of the first rating of the object by the user within a preset time range, the evaluation of the object by the user, the feedback of the object on the user's evaluation, and the overall rating includes:

[0021] Provide the user's rating of the object itself within a preset time range, the user's rating of the object's product, the user's rating of the object's product packaging, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

[0022] In combination with the first implementation of the first aspect, in the second implementation of the first aspect of the present disclosure, the user's evaluation of the object includes the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in all the evaluation content and the proportion of the orders between the user and the object that have the user's evaluation, and the second weight includes a fourth sub-weight of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in all the evaluation content, and a fifth sub-weight of the proportion of the orders between the user and the object that have the user's evaluation,

[0023] The step of performing weighted calculation on the user's evaluation of the object based on the second weight to obtain a second weighted value includes:

[0024] Calculating a weighted value of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content based on the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content and the fourth sub-weight;

[0025] Calculating a weighted value of the proportion of orders with user evaluations among the orders between the user pair and the object based on the proportion of orders with user evaluations among the orders between the user pair and the object and the fifth sub-weight;

[0026] The second weighted value is calculated based on the weighted value of the proportion of the evaluation contents of the user's evaluation of the object that meet the preset evaluation conditions in the total evaluation contents and the weighted value of the proportion of the orders between the user and the object that have the user's evaluation.

[0027] The providing of the first rating of the object by the user within a preset time range, the evaluation of the object by the user, the feedback of the object on the user's evaluation, and the overall rating includes:

[0028] Provide user ratings of the object itself within a preset time period, user ratings of the object's products, user ratings of the object's product packaging, the proportion of user evaluations of the object that meet preset evaluation conditions in all evaluations, the proportion of orders between the user and the object that include user evaluations, the object's feedback on the user's evaluation, and the overall rating.

[0029] In combination with the first aspect, the first implementation manner of the first aspect, and any one of the second implementation manners of the first aspect, in a third implementation manner of the first aspect of the present disclosure, the preset scoring standard is a preset score, and the first score not reaching the preset score indicates that the user's first score for the object is a bad review,

[0030] The method of determining a first weight of the first score of the object by the user within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation within the preset time range based on whether the user's first score of the object within the preset time range meets the preset score standard includes:

[0031] Based on the first rating of the object by the user within the preset time range being a bad rating, the first weight is set to a first weight value, the second weight is set to a second weight value, and the third weight is set to a third weight value, or

[0032] Based on the fact that the first rating of the object by the user within the preset time range is not a bad rating, the first weight is set to a fourth weight value, the second weight is set to a fifth weight value, and the third weight is set to a sixth weight value.

[0033] In combination with the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect of the present disclosure, the preset scores include a first preset sub-score of the user's score for the object itself, a second preset sub-score of the user's score for the product of the object, and a third preset sub-score of the user's score for the packaging of the product of the object, wherein if the user's score for the object itself does not reach the first preset sub-score, it means that the user's first score for the object is a bad review, and / or if the user's score for the product of the object does not reach the second preset sub-score, it means that the user's first score for the object is a bad review, and / or if the user's score for the product of the object does not reach the third preset sub-score, it means that the user's first score for the object is a bad review.

[0034] In combination with the first aspect, in a fifth implementation of the first aspect of the present disclosure, the first score of the object given by the user is weighted based on the first weight to obtain a first weighted value, the evaluation of the object given by the user is weighted based on the second weight to obtain a second weighted value, the feedback of the object on the user's evaluation is weighted based on the third weight to obtain a third weighted value, and the first weighted value, the second weighted value and the third weighted value are summed to calculate the second score of the object as the overall score of the object within a preset time range, including:

[0035] A first weighted value is obtained by weighted calculation of the user's first score for the object based on the first weight, a second weighted value is obtained by weighted calculation of the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighted calculation of the object's feedback on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are normalized to calculate the second score of the object as the overall score of the object within a preset time range.

[0036] In combination with the first aspect, the first implementation manner of the first aspect, and any one of the second implementation manners, the sixth implementation manner of the first aspect of the present disclosure further includes:

[0037] Calculate and provide the change in the user's first score for the object within the current preset time range compared to the previous preset time range, the change in the user's evaluation of the object, the change in the object's feedback on the user's evaluation, and the change in the overall score.

[0038] In a second aspect, an embodiment of the present disclosure provides an object evaluation processing device, comprising:

[0039] An object evaluation processing device, comprising:

[0040] An acquisition module is configured to acquire a user's first rating of an object, a user's evaluation of the object, and the object's feedback on the user's evaluation within a preset time range;

[0041] A weight calculation module is configured to determine a first weight of the first score of the object given by the user within a preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation based on whether the user's first score of the object within a preset time range meets a preset score standard;

[0042] an overall score calculation module, configured to perform weighted calculation on the first score of the user on the object based on the first weight to obtain a first weighted value, perform weighted calculation on the evaluation of the user on the object based on the second weight to obtain a second weighted value, perform weighted calculation on the feedback of the object on the user's evaluation based on the third weight to obtain a third weighted value, and calculate the second score of the object as the overall score of the object within a preset time range by summing the first weighted value, the second weighted value and the third weighted value;

[0043] The evaluation providing module is configured to provide the user's first score on the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall score.

[0044] In combination with the second aspect, in a first implementation of the second aspect of the present disclosure, the first rating of the object by the user includes the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user, and the first weight includes a first sub-weight of the rating of the object itself by the user, a second sub-weight of the rating of the product of the object by the user, and a third sub-weight of the rating of the packaging of the product of the object by the user,

[0045] Wherein, the overall score calculation module is further configured as follows:

[0046] Calculating a weighted score of the object by the user based on the score of the object by the user and the first sub-weight;

[0047] Calculate a weighted score of the product of the object by the user based on the score of the product of the object by the user and the second sub-weight;

[0048] Calculate a weighted score of the packaging of the product of the object by the user based on the score of the packaging of the product of the object by the user and the third sub-weight;

[0049] The first weighted value is calculated based on the weighted score of the object itself given by the user, the weighted score of the product of the object given by the user, and the weighted score of the packaging of the product of the object given by the user,

[0050] Wherein, the evaluation providing module is further configured to:

[0051] Provide the user's rating of the object itself within a preset time range, the user's rating of the object's product, the user's rating of the object's product packaging, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

[0052] In combination with the first implementation of the second aspect, in the second implementation of the second aspect of the present disclosure, the user's evaluation of the object includes the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in all the evaluation content and the proportion of orders between the user and the object that have user evaluations, and the second weight includes a fourth sub-weight of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in all the evaluation content, and a fifth sub-weight of the proportion of orders between the user and the object that have user evaluations.

[0053] Wherein, the overall score calculation module is further configured as follows:

[0054] Calculating a weighted value of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content based on the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content and the fourth sub-weight;

[0055] Calculating a weighted value of the proportion of orders with user evaluations among the orders between the user pair and the object based on the proportion of orders with user evaluations among the orders between the user pair and the object and the fifth sub-weight;

[0056] The second weighted value is calculated based on the weighted value of the proportion of the evaluation contents of the user's evaluation of the object that meet the preset evaluation conditions in the total evaluation contents and the weighted value of the proportion of the orders between the user and the object that have the user's evaluation.

[0057] Wherein, the evaluation providing module is further configured to:

[0058] Provide user ratings of the object itself within a preset time period, user ratings of the object's products, user ratings of the object's product packaging, the proportion of user evaluations of the object that meet preset evaluation conditions in all evaluations, the proportion of orders between the user and the object that include user evaluations, the object's feedback on the user's evaluation, and the overall rating.

[0059] In combination with the second aspect, the first implementation manner of the second aspect, and any one of the second implementation manners, in a third implementation manner of the second aspect of the present disclosure, the preset scoring standard is a preset score, and the first score not reaching the preset score indicates that the user's first score for the object is a bad review,

[0060] Wherein, the weight calculation module is further configured as follows:

[0061] Based on the first rating of the object by the user within the preset time range being a bad rating, the first weight is set to a first weight value, the second weight is set to a second weight value, and the third weight is set to a third weight value, or

[0062] Based on the fact that the first rating of the object by the user within the preset time range is not a bad rating, the first weight is set to a fourth weight value, the second weight is set to a fifth weight value, and the third weight is set to a sixth weight value.

[0063] In combination with the third implementation manner of the second aspect, in the fourth implementation manner of the second aspect of the present disclosure, the preset scores include a first preset sub-score of the user's score for the object itself, a second preset sub-score of the user's score for the product of the object, and a third preset sub-score of the user's score for the packaging of the product of the object, wherein if the user's score for the object itself does not reach the first preset sub-score, it means that the user's first score for the object is a bad review, and / or the user's score for the product of the object does not reach the second preset sub-score, it means that the user's first score for the object is a bad review, and / or the user's score for the product of the object does not reach the third preset sub-score, it means that the user's first score for the object is a bad review.

[0064] In combination with the second aspect, in a fifth implementation of the second aspect of the present disclosure, the overall score calculation module is further configured as follows:

[0065] A first weighted value is obtained by weighted calculation of the user's first score for the object based on the first weight, a second weighted value is obtained by weighted calculation of the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighted calculation of the object's feedback on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are normalized to calculate the second score of the object as the overall score of the object within a preset time range.

[0066] In combination with the second aspect, the first implementation manner of the second aspect, and any one of the second implementation manners, the sixth implementation manner of the second aspect of the present disclosure further includes:

[0067] The evaluation change calculation and provision module is configured to calculate and provide the change of the user's first score of the object within the current preset time range compared with the previous preset time range, the change of the user's evaluation of the object, the change of the object's feedback on the user's evaluation, and the change of the overall score.

[0068] In a third aspect, an embodiment of the present disclosure provides a merchant evaluation presentation method, including:

[0069] Obtaining the user's rating of the merchant within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of orders between the user and the merchant that have user evaluations, and the merchant's feedback on the user's evaluation;

[0070] Based on whether one or all of the user's rating of the merchant itself, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging within the preset time range meet the preset rating standard, determine a first weight of the user's rating of the merchant itself within the preset time range, a second weight of the user's rating of the merchant's products, a third weight of the user's rating of the merchant's product packaging, a fourth weight of the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content, a fifth weight of the proportion of orders between the user and the merchant that have user evaluations, and a sixth weight of the merchant's feedback on the user's evaluation;

[0071] Based on the first weight, the user's rating of the merchant itself is weighted to obtain a first weighted value; based on the second weight, the user's rating of the merchant's product is weighted to obtain a second weighted value; based on the third weight, the user's rating of the merchant's product packaging is weighted to obtain a third weighted value; based on the fourth weight, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content is weighted to obtain a fourth weighted value; based on the fifth weight, the proportion of the orders between the user and the merchant that have the user's evaluation is weighted to obtain a fifth weighted value; based on the sixth weight, the merchant's feedback on the user's evaluation is weighted to obtain a sixth weighted value;

[0072] normalizing the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value, and the sixth weighted value to calculate a second score of the object as an overall score of the object within a preset time range,

[0073] The overall rating, the user's rating of the merchant itself, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of user evaluation content on the merchant that meets preset evaluation conditions in the total evaluation content, the proportion of orders between users and merchants that include user evaluations, and the merchant's feedback on user evaluations are presented.

[0074] In a fourth aspect, an embodiment of the present disclosure provides a merchant evaluation presentation device, including:

[0075] The acquisition module is configured to acquire the user's rating of the merchant itself within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of the orders between the user and the merchant that have the user's evaluation, and the merchant's feedback on the user's evaluation;

[0076] The weight calculation module is configured to determine, based on whether one or all of the user's rating of the merchant itself, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging within the preset time range meet the preset rating standard, a first weight of the user's rating of the merchant itself within the preset time range, a second weight of the user's rating of the merchant's products, a third weight of the user's rating of the merchant's product packaging, a fourth weight of the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, a fifth weight of the proportion of the orders between the user and the merchant that have the user's evaluation, and a sixth weight of the merchant's feedback on the user's evaluation;

[0077] The weighted value calculation module is configured to perform weighted calculation on the user's rating of the merchant itself based on the first weight to obtain a first weighted value, perform weighted calculation on the user's rating of the merchant's product based on the second weight to obtain a second weighted value, perform weighted calculation on the user's rating of the merchant's product packaging based on the third weight to obtain a third weighted value, perform weighted calculation on the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content based on the fourth weight to obtain a fourth weighted value, perform weighted calculation on the proportion of orders between the user and the merchant that have user evaluations based on the fifth weight to obtain a fifth weighted value, and perform weighted calculation on the merchant's feedback on the user's evaluation based on the sixth weight to obtain a sixth weighted value;

[0078] an overall score calculation module, configured to perform normalization processing on the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value, and the sixth weighted value to calculate a second score of the object as the overall score of the object within a preset time range,

[0079] The presentation module is configured to present the overall score, the user's score for the merchant itself, the user's score for the merchant's products, the user's score for the merchant's product packaging, the proportion of user evaluation content on the merchant that meets preset evaluation conditions in all evaluation content, the proportion of orders between users and merchants that include user evaluations, and the merchant's feedback on user evaluations.

[0080] In a fifth aspect, an electronic device is provided in an embodiment of the present disclosure, comprising a memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps described in the first aspect, the first to sixth implementations of the first aspect, and any one of the third aspect.

[0081] In a sixth aspect, a computer-readable storage medium is provided in an embodiment of the present disclosure, on which computer instructions are stored. When the computer instructions are executed by a processor, the method steps described in the first aspect, the sixth implementation method to the fifth implementation method of the first aspect, and any one of the third aspect are implemented.

[0082] In the seventh aspect, a computer program product is provided in an embodiment of the present disclosure, which includes computer instructions, which, when executed by a processor, implement the method steps as described in the first aspect, the sixth to fifth implementations of the first aspect, and any one of the third aspect.

[0083] According to the technical solution provided by the embodiment of the present disclosure, the object evaluation processing method includes: obtaining a first score of a user on an object within a preset time range, the user's evaluation of the object, and the object's feedback on the user's evaluation; determining a first weight of the user's first score of the object within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation based on whether the user's first score of the object within the preset time range meets a preset scoring standard; performing a weighted calculation on the user's first score of the object based on the first weight to obtain a first weighted value, performing a weighted calculation on the user's evaluation of the object based on the second weight to obtain a second weighted value, and performing a weighted calculation on the user's evaluation of the object based on the third weight to obtain a first weighted value. The feedback of the user's evaluation is weighted to obtain a third weighted value, and the first weighted value, the second weighted value and the third weighted value are summed to calculate the second score of the object as the overall score of the object within the preset time range; the first score of the user on the object, the user's evaluation of the object, the feedback of the object on the user's evaluation, and the overall score are provided within the preset time range, and not only the user's score on the object is considered, but also the user's evaluation of the object and the object's feedback on the user's evaluation are considered, thereby expanding the dimension of object evaluation, expanding the evaluation distinction between objects, and improving the impact of the score and evaluation on the object as a whole. The processing of the score and evaluation by the user and the object will affect the overall score and the evaluation of the corresponding dimensions. Therefore, the scoring and evaluation of the object are more accurate, which is conducive to improving the scoring and evaluation of the object, and is also conducive to the user identifying the scoring and evaluation of each dimension of the object.

[0084] According to the technical solution provided by the embodiment of the present disclosure, a merchant evaluation presentation method is provided, including: obtaining the user's rating of the merchant itself within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content, the proportion of orders between the user and the merchant that have user evaluations, and the merchant's feedback on the user's evaluation; based on whether one or all of the user's rating of the merchant itself within the preset time range, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging meet the preset rating standards, determining the user's rating of the merchant itself within the preset time range. a first weight of the rating, a second weight of the rating of the merchant's products by the user, a third weight of the rating of the merchant's product packaging by the user, a fourth weight of the proportion of the user's evaluation of the merchant that meets the preset evaluation conditions in the total evaluation content, a fifth weight of the proportion of orders between the user and the merchant that have user evaluations, and a sixth weight of the merchant's feedback on the user's evaluation; based on the first weight, the user's rating of the merchant itself is weighted to obtain a first weighted value, based on the second weight, the user's rating of the merchant's products is weighted to obtain a second weighted value, and based on the third weight, the user's rating of the merchant's product packaging is weighted to obtain a third weighted value. three weighted values, based on the fourth weight, weighted calculation is performed on the proportion of the evaluation content of the user's evaluation of the merchant that meets the preset evaluation conditions in the total evaluation content to obtain a fourth weighted value, based on the fifth weight, weighted calculation is performed on the proportion of the orders between the user and the merchant that have user evaluations to obtain a fifth weighted value, and based on the sixth weight, weighted calculation is performed on the merchant's feedback on the user's evaluation to obtain a sixth weighted value; the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value and the sixth weighted value are normalized to calculate the second score of the object as the overall score of the object within the preset time range, and the second score of the object is presented as the overall score of the object within the preset time range. The overall rating, the user's rating of the merchant itself, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of orders between users and merchants that have user evaluations, and the merchant's feedback on user evaluations. Not only the user's rating of the merchant is considered, but also the user's evaluation of the merchant and the merchant's feedback on the user's evaluation are considered, thereby expanding the dimensions of merchant evaluation, expanding the evaluation distinction between merchants, and improving the impact of ratings and evaluations on merchants as a whole. The processing of ratings and evaluations by users and merchants will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the ratings and evaluations of merchants are more accurate, which is conducive to merchants improving their ratings and evaluations, and is also conducive to users identifying the ratings and evaluations of merchants in various dimensions.

[0085] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Other features, objectives and advantages of the present disclosure will become more apparent through the following detailed description of non-limiting embodiments in conjunction with the accompanying drawings. In the accompanying drawings:

[0087] Figure 1 A flowchart showing an object evaluation processing method according to an embodiment of the present disclosure;

[0088] Figure 2A An exemplary schematic diagram showing a merchant-side evaluation interface presented on a mobile terminal in the related art;

[0089] Figure 2B An exemplary schematic diagram showing a merchant-side evaluation interface presented on a mobile terminal after being processed by the object evaluation processing method according to an embodiment of the present disclosure;

[0090] Figure 3 A structural block diagram of an object evaluation processing device according to an embodiment of the present disclosure is shown;

[0091] Figure 4 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown;

[0092] Figure 5 A schematic diagram showing the structure of a computer device suitable for implementing the method according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0093] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, parts not related to the description of the exemplary embodiments are omitted in the accompanying drawings.

[0094] In the present disclosure, it should be understood that terms such as "include" or "have" are intended to indicate the presence of features, numbers, steps, behaviors, components, parts, or a combination thereof disclosed in the present specification, and are not intended to exclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or a combination thereof exist or are added.

[0095] In the present disclosure, the acquisition of user information or user data is an operation authorized and confirmed by the user, or actively selected by the user.

[0096] It should also be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0097] As mentioned above, when the online shopping platform of the related art rates merchants, it generally uses the average score of merchant ratings within a longer period of time (e.g., 90 days) as the merchant rating (e.g., (1-2 points: bad rating, 3 points: medium rating, 4-5 points: good rating). Under the rating processing method of the related art, the following problems may occur:

[0098] 1) 70% of merchants have a rating of 4.5 or above, and there is little difference between merchants;

[0099] 2) The overall impact of the rating on merchants is not obvious;

[0100] 3) The rating remains unchanged after the negative review is deleted;

[0101] 4) There are new positive reviews recently but the rating has not increased.

[0102] Taking all the above issues into consideration, the relevant technologies are not accurate enough in rating merchants, making it difficult for merchants to influence the ratings, and it is not conducive to user identification.

[0103] In order to solve the above problems, the present disclosure proposes an object evaluation processing method and device, and a merchant evaluation presentation method and device.

[0104] According to the technical solution provided by the embodiment of the present disclosure, the object evaluation processing method includes: obtaining a first score of a user on an object within a preset time range, the user's evaluation of the object, and the object's feedback on the user's evaluation; determining a first weight of the user's first score of the object within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation based on whether the user's first score of the object within the preset time range meets a preset scoring standard; performing a weighted calculation on the user's first score of the object based on the first weight to obtain a first weighted value, performing a weighted calculation on the user's evaluation of the object based on the second weight to obtain a second weighted value, and performing a weighted calculation on the user's evaluation of the object based on the third weight to obtain a first weighted value. The feedback of the user's evaluation is weighted to obtain a third weighted value, and the first weighted value, the second weighted value and the third weighted value are summed to calculate the second score of the object as the overall score of the object within the preset time range; the first score of the user on the object, the user's evaluation of the object, the feedback of the object on the user's evaluation, and the overall score are provided within the preset time range, and not only the user's score on the object is considered, but also the user's evaluation of the object and the object's feedback on the user's evaluation are considered, thereby expanding the dimension of object evaluation, expanding the evaluation distinction between objects, and improving the impact of the score and evaluation on the object as a whole. The processing of the score and evaluation by the user and the object will affect the overall score and the evaluation of the corresponding dimensions. Therefore, the scoring and evaluation of the object are more accurate, which is conducive to improving the scoring and evaluation of the object, and is also conducive to the user identifying the scoring and evaluation of each dimension of the object.

[0105] The following reference Figure 1 An object evaluation processing method according to an embodiment of the present disclosure is described.

[0106] Figure 1 A flowchart showing an object evaluation processing method according to an embodiment of the present disclosure is shown.

[0107] like Figure 1 As shown, the object evaluation processing method includes steps S101, S102, S103, and S104.

[0108] In step S101, the first rating of the object by the user, the evaluation of the object by the user, and the feedback of the object on the user's evaluation within a preset time range are obtained.

[0109] In step S102, based on whether the user's first score for the object within the preset time range meets the preset score standard, a first weight of the user's first score for the object within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation are determined.

[0110] In step S103, a first weighted value is obtained by weighting the user's first score for the object based on the first weight, a second weighted value is obtained by weighting the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighting the feedback of the object on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are summed to calculate the second score of the object as the overall score of the object within a preset time range.

[0111] In step S104, the first rating of the user on the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating are provided.

[0112] In one embodiment of the present disclosure, in order to solve the problem in the related art that the rating of merchants is not accurate enough, merchants are difficult to influence the rating, and it is not conducive to user identification, the embodiment of the present disclosure uses the first rating of the object by the user within the preset time range, the evaluation of the object by the user, and the feedback of the object to the user's evaluation to calculate the overall rating of the object within the preset time range, and presents the first rating of the object by the user within the preset time range, the evaluation of the object by the user, the feedback of the object to the user's evaluation, and the overall rating to the object. In this way, the object rating can be presented in multiple dimensions, which is conducive to user identification, and the object can improve the object's evaluation of the user by giving feedback on the user's evaluation, thereby improving the accuracy of the evaluation of the object.

[0113] In one embodiment of the present disclosure, the object may refer to a merchant, and the user may refer to a user who places an order with the merchant. In one embodiment of the present disclosure, the object evaluation processing method may be executed on a server of an online service platform, on a user terminal, or on a merchant terminal.

[0114] In one embodiment of the present disclosure, a preset time range may be set according to actual needs, for example, 30 days, 20 days, 15 days, etc. Setting the preset time range to be shorter may make the first score of the object by the user, the evaluation of the object by the user, and the feedback of the object to the user's evaluation more in line with the current actual situation, and because the number of data samples is small, when the object gives feedback to the user's evaluation, it may be easier to help the object improve the feedback of the object to the user's evaluation and the overall score.

[0115] In one embodiment of the present disclosure, the first rating of the object by the user may refer to any one of the rating of the object itself, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user, or two of them, or all of them. In one embodiment of the present disclosure, the first rating of the object by the user may refer to the weighted average of the rating of the object itself, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user. In one embodiment of the present disclosure, the first rating of the object by the user may adopt a 5-point rating standard (1-2 points: bad rating, 3 points: medium rating, 4-5 points: good rating), or other rating standards such as 10-point or 100-point ratings. In one embodiment of the present disclosure, each of the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user may adopt a 5-point rating standard, or other rating standards such as 10-point or 100-point ratings.

[0116] In one embodiment of the present disclosure, the preset scoring standard may refer to a specific score, for example, 3 points in a 5-point system is the preset scoring standard, and the user's first score for the object reaches 3 points, which means that the preset scoring standard is met. Therefore, when the user's first score for the object reaches the preset scoring standard within the preset time range, a set of first weights, second weights, and third weights can be respectively allocated to the user's first score for the object, the user's evaluation of the object, and the object's feedback on the user's evaluation. When the user's first score for the object does not reach the preset scoring standard within the preset time range, another set of first weights, second weights, and third weights can be respectively allocated to the user's first score for the object, the user's evaluation of the object, and the object's feedback on the user's evaluation.

[0117] In one embodiment of the present disclosure, when a user's first rating of an object may refer to three ratings: the user's rating of the object itself, the user's rating of the product of the object, and the user's rating of the packaging of the product of the object, the first weight may include a first sub-weight of the user's rating of the object itself, a second sub-weight of the user's rating of the product of the object, and a third sub-weight of the user's rating of the packaging of the product of the object, and the three sub-weights are respectively assigned to the user's rating of the object itself, the user's rating of the product of the object, and the user's rating of the packaging of the product of the object, to calculate a first weighted value obtained by weighted calculation of the user's first rating of the object by the first weight.

[0118] In one embodiment of the present disclosure, the user's evaluation of the object may refer to one or both of the proportion of the user's evaluation of the object that meets preset evaluation conditions in all evaluation contents, and the proportion of orders between the user and the object that include user evaluations.

[0119] In one embodiment of the present disclosure, the preset evaluation condition may refer to that the user's evaluation content of the object includes a specific number (e.g., 1 picture) and a specific number of words (e.g., 100 words, 200 words, etc.). For example, the proportion of the user's evaluation content of the object that meets the preset evaluation condition in the total evaluation content may be the proportion of the user's evaluation content of the object that meets the evaluation content of 1 picture plus 100 words (which may be referred to as high-quality evaluation content) in the total evaluation content.

[0120] In one embodiment of the present disclosure, the proportion of orders between users and objects with user evaluations refers to the proportion of orders between users and merchants with user evaluation content (with text content) in all orders.

[0121] In one embodiment of the present disclosure, the feedback of the object on the user's evaluation refers to how many negative reviews the object has responded to out of all the negative reviews, for example, with manual text content replies, when the user posts a negative review on the object (for example, the first score is lower than 3 points on a 5-point scale).

[0122] In one embodiment of the present disclosure, the merchant or user may be provided with the user's first rating of the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

[0123] The following describes, using Table 1 as an example, the weight distribution of the user's first score for the object, the user's evaluation of the object, and the object's feedback on the user's evaluation when calculating the merchant's overall score.

[0124] Table 1

[0125]

[0126]

[0127] As can be seen from Table 1, when calculating the overall score of a merchant, when the user has a bad review or does not have a bad review for the merchant, the weights of the specific 6 scoring sub-basis A1%, B1%, C1%, D1%, E1%, F1% and A2%, B2%, C2%, D2%, E2% are different, but the sum of the total weights of the 6 scoring sub-basis is 100%. In addition, the weight values ​​of the scoring sub-basis shown in Table 1 above are only examples, and different weights can be used for each scoring sub-basis according to actual conditions. Moreover, the above weights are only used to calculate the overall score of the merchant. When presenting the user's evaluation of the merchant in multiple dimensions, in addition to presenting the overall score, the scoring basis and its specific value can also be presented, or the scoring sub-basis and its specific value can be presented. In this way, the scores of different merchants can be better distinguished, allowing users to better choose suitable merchants, and merchants can also have the option of improving their evaluation. It should be understood that the weight distribution method shown in Table 1 is only an example, and the present disclosure is not limited thereto. The sum of the weights of each scoring basis or sub-scoring basis is not limited to 100%, and any value can be selected according to actual conditions.

[0128] In one embodiment of the present disclosure, if it is necessary to evaluate a merchant in fewer dimensions within a preset time range (for example, the last 30 days), only the three scoring criteria shown in Table 1 may be adopted, that is, when providing an evaluation of a merchant, only the user's first score for the merchant, the user's evaluation of the merchant, the merchant's feedback on the user's evaluation, and the overall score calculated based on these three scoring criteria are provided. In one embodiment of the present disclosure, the first rating of a merchant by a user may be a direct rating by the user, or a value calculated using the first rating of the merchant, including the rating of the merchant itself by the user, the rating of the merchant's products by the user, and the rating of the merchant's product packaging as shown in Table 1 (for example, calculated by taking the average or weighted average); the evaluation of the merchant by the user may be a value directly obtained or calculated from the user's evaluation, for example, a value calculated by taking the proportion of high-quality evaluations of the merchant by the user in all evaluations, and the proportion of orders between the user and the merchant that include user evaluations (for example, calculated by taking the average or weighted average); the feedback of the merchant on the user's evaluation may be a value directly obtained or calculated from the feedback of the merchant on the user's evaluation, for example, it may be the proportion of negative reviews manually replied by the merchant in all negative reviews.

[0129] In one embodiment of the present disclosure, when calculating the overall score, the weight of the user's first score for the merchant (first weight) may be the sum of the respective weights of the user's score for the merchant itself, the user's score for the merchant's products, and the user's score for the merchant's product packaging, as shown in Table 1. The weight of the user's evaluation of the merchant (second weight) may be the sum of the respective weights of the proportion of the user's high-quality evaluation content of the merchant in the total evaluation content, as shown in Table 1, and the proportion of orders between the user and the merchant that have user evaluations. The weight of the merchant's feedback on the user's evaluation (third weight) may be the weight of the proportion of the negative reviews manually replied by the merchant in all the negative reviews, as shown in Table 1.

[0130] In one embodiment of the present disclosure, a first score given by a user to a merchant is weighted based on a first weight to obtain a first weighted value, a second weighted value is weighted based on a second weight to obtain a second weighted value, and a third weighted value is weighted based on a third weight to obtain a third weighted value. The first weighted value, the second weighted value, and the third weighted value are summed to calculate the second score of the merchant as the overall score of the merchant within a preset time range.

[0131] It should be understood that the above description is only an example, and the overall score of the merchant calculated based on fewer dimensions to evaluate the merchant is not limited to the evaluation based on the three dimensions of the scoring basis shown in Table 1, and the merchant can also be evaluated in other dimensions. The following description calculates the overall score of the merchant based on more dimensions, for example, the overall score of the merchant is calculated based on the dimensions of the six scoring sub-basis shown in Table 1.

[0132] In one embodiment of the present disclosure, based on the scoring sub-basis shown in Table 1, within a preset time range (e.g., the last 30 days), assuming that the user's score for the merchant itself is 4.3 points (out of 5 points), the user's score for the merchant's products is 4.2 points (out of 5 points), the user's score for the merchant's product packaging is 5.6 points (out of 10 points), the user's high-quality evaluation content for the merchant accounts for 56% of the total evaluation content, the proportion of orders with user evaluations between users and merchants accounts for 32%, and the negative reviews manually replied by merchants account for 56% of all negative reviews. Based on the weights of the scoring sub-basis when there are negative reviews, the weighted values ​​of the above scoring sub-basis are normalized and summed to obtain the merchant's overall score, for example, 4.2. The specific implementation of the normalization method is not discussed here, and those skilled in the art can obtain it from the relevant technology.

[0133] The following reference Figure 2A Describe an example of a merchant evaluation interface presented on a mobile terminal in the related art, refer to Figure 2BAn example of a merchant evaluation interface presented on a mobile terminal according to an embodiment of the present disclosure is described.

[0134] Figure 2A An exemplary schematic diagram showing a merchant-side evaluation interface presented on a mobile terminal in the related art.

[0135] like Figure 2A As shown, the evaluation interface 210 of the merchant end of the mobile terminal presents, for example, the customer evaluation of the XXX application, which includes the evaluation window 211 of the XXX application on the merchant end, and the evaluation window 211 of the XXX application includes the XXX application rating part 212. In the XXX application rating part 212, the merchant's overall rating is 4.8, and the taste rating of the merchant's products is 4.8, and the packaging rating of the merchant's products is 4.9. In addition, the XXX application rating part 212 also shows that the merchant's delivery satisfaction is 97%.

[0136] exist Figure 2A In the merchant evaluation interface 210 of the mobile terminal shown, due to the limited rating dimensions, the merchant rating is not accurate enough, it is difficult for the merchant to influence the rating, and it is not conducive to user identification.

[0137] Figure 2A The merchant evaluation interface 210 of the mobile terminal also presents an evaluation details window 213, which shows the user's evaluation details, such as text content and picture or video content. For example, in the evaluation of the merchant by user XXXXXX, the taste score is 2 and the packaging score is 3. The content of the evaluation details is not the focus of the embodiment of the present disclosure, and further description thereof is omitted here.

[0138] Figure 2B An exemplary schematic diagram is shown of a merchant-side evaluation interface presented on a mobile terminal after being processed by the object evaluation processing method according to an embodiment of the present disclosure.

[0139] like Figure 2B As shown, the customer evaluation of, for example, the XXX application is presented in the merchant-side evaluation interface 220 of the mobile terminal. Figure 2BA window 221 for user star rating is shown, in which a rating presentation window 222 including specific ratings of 6 dimensions and an overall rating of the merchant is shown. In the rating presentation window 222, the merchant rating is the rating of the merchant itself by the user as shown in Table 1 above, the taste rating is the rating of the merchant's products by the user as shown in Table 1 above, the packaging rating is the rating of the merchant's product packaging by the user as shown in Table 1 above, the negative review manual reply rate is the proportion of negative reviews manually replied by the merchant in all negative reviews as shown in Table 1 above, the high-quality evaluation rate is the proportion of high-quality evaluation content of the merchant by the user as shown in Table 1 above in all evaluation content, and the order evaluation rate is the proportion of orders with user evaluations in the orders between the user and the merchant as shown in Table 1 above. The merchant's overall rating of 4.2 can be calculated based on the merchant rating of 4.3, the taste rating of 4.2, the packaging rating of 5.6, the negative review manual reply rate of 56%, the high-quality evaluation rate of 56%, and the order evaluation rate of 32%. The merchant's overall score of 4.2 may refer to the merchant's overall score calculated based on the score sub-criteria of 6 dimensions within a preset time range (eg, the last 30 days).

[0140] like Figure 2B As shown, the rating presentation window 222 also shows the change in the merchant's current (e.g., the last 30 days from today) overall rating compared to yesterday's (e.g., the last 30 days from yesterday), for example, a decrease of 0.2 points. Figure 2B As shown, the window 221 of the user star rating also shows the change in the current (eg, the last 30 days from today) high-quality rating rate compared to yesterday (eg, the last 30 days from yesterday), for example, a decrease of 0.2 percentage points.

[0141] Figure 2B The merchant evaluation interface 220 of the mobile terminal shown also includes an evaluation details window 223, the details of which are similar to Figure 2A The evaluation details window 213 shown is similar, and its details are not repeated here.

[0142] from Figure 2B As shown in the merchant evaluation interface 220 of the mobile terminal, the object evaluation processing method of the embodiment of the present disclosure not only considers the user's rating of the merchant, but also considers the user's evaluation of the merchant and the merchant's feedback on the user's evaluation, thereby expanding the dimensions of merchant evaluation, expanding the evaluation distinction between merchants, and improving the impact of ratings and evaluations on merchants as a whole. The processing of ratings and evaluations by users and merchants will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of merchants are more accurate, which is conducive to merchants improving their ratings and evaluations, and is also conducive to users identifying the ratings and evaluations of merchants in various dimensions.

[0143] In addition, although Figure 2BThe merchant-side evaluation interface 220 of the mobile terminal is shown, but it should be understood that the user-side evaluation interface may also adopt a similar multi-dimensional evaluation interface, which may allow the user to better distinguish between different merchants.

[0144] In one embodiment of the present disclosure, the first rating of the object by the user includes the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user, and the first weight includes a first sub-weight of the rating of the object itself by the user, a second sub-weight of the rating of the product of the object by the user, and a third sub-weight of the rating of the packaging of the product of the object by the user,

[0145] Wherein, step S103 includes:

[0146] Calculating a weighted score of the object by the user based on the score of the object by the user and the first sub-weight;

[0147] Calculate a weighted score of the product of the object by the user based on the score of the product of the object by the user and the second sub-weight;

[0148] Calculate a weighted score of the packaging of the product of the object by the user based on the score of the packaging of the product of the object by the user and the third sub-weight;

[0149] The first weighted value is calculated based on the weighted score of the object itself given by the user, the weighted score of the product of the object given by the user, and the weighted score of the packaging of the product of the object given by the user,

[0150] The providing of the first rating of the object by the user within a preset time range, the evaluation of the object by the user, the feedback of the object on the user's evaluation, and the overall rating includes:

[0151] Provide the user's rating of the object itself within a preset time range, the user's rating of the object's product, the user's rating of the object's product packaging, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

[0152] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0153] In one embodiment of the present disclosure, the user's evaluation of the object includes the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content and the proportion of the orders between the user and the object that have the user's evaluation, and the second weight includes a fourth sub-weight of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content, and a fifth sub-weight of the proportion of the orders between the user and the object that have the user's evaluation,

[0154] Wherein, step S103 includes:

[0155] Calculating a weighted value of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content based on the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content and the fourth sub-weight;

[0156] Calculating a weighted value of the proportion of orders with user evaluations among the orders between the user pair and the object based on the proportion of orders with user evaluations among the orders between the user pair and the object and the fifth sub-weight;

[0157] The second weighted value is calculated based on the weighted value of the proportion of the evaluation contents of the user's evaluation of the object that meet the preset evaluation conditions in the total evaluation contents and the weighted value of the proportion of the orders between the user and the object that have the user's evaluation.

[0158] The providing of the first rating of the object by the user within a preset time range, the evaluation of the object by the user, the feedback of the object on the user's evaluation, and the overall rating includes:

[0159] Provide user ratings of the object itself within a preset time period, user ratings of the object's products, user ratings of the object's product packaging, the proportion of user evaluations of the object that meet preset evaluation conditions in all evaluations, the proportion of orders between the user and the object that include user evaluations, the object's feedback on the user's evaluation, and the overall rating.

[0160] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0161] In one embodiment of the present disclosure, the preset scoring standard is a preset score, and if the first score does not reach the preset score, it means that the user's first score for the object is a bad review.

[0162] Wherein, step S102 includes:

[0163] Based on the first rating of the object by the user within the preset time range being a bad rating, the first weight is set to a first weight value, the second weight is set to a second weight value, and the third weight is set to a third weight value, or

[0164] Based on the fact that the first rating of the object by the user within the preset time range is not a bad rating, the first weight is set to a fourth weight value, the second weight is set to a fifth weight value, and the third weight is set to a sixth weight value.

[0165] According to the technical solution provided by the embodiment of the present disclosure, the preset scoring standard is a preset score, and the first score does not reach the preset score, indicating that the user's first score of the object is a bad review, wherein the first weight of the user's first score of the object within the preset time range, the second weight of the user's evaluation of the object, and the third weight of the object's feedback on the user's evaluation are determined based on whether the user's first score of the object within the preset time range reaches the preset scoring standard, including: based on the user's first score of the object within the preset time range is a bad review, the first weight is set to the first weight value, the second weight is set to the second weight value, and the third weight is set to the third weight value, or based on the user's first score of the object within the preset time range is not a bad review, the first weight is set to the fourth weight value, the second weight is set to the fifth weight value, and the third weight is set to the sixth weight value, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the score and evaluation on the object as a whole is improved. The processing of the score and evaluation by the user and the object will affect the overall score and the evaluation of the corresponding dimensions. Therefore, the scoring and evaluation of the object are more accurate, which is conducive to improving the scoring and evaluation of the object, and is also conducive to the user identifying the scoring and evaluation of each dimension of the object.

[0166] In one embodiment of the present disclosure, the preset scores include a first preset sub-score of the user's score for the object itself, a second preset sub-score of the user's score for the product of the object, and a third preset sub-score of the user's score for the packaging of the product of the object, wherein if the user's score for the object itself does not reach the first preset sub-score, it means that the user's first score for the object is a bad review, and / or the user's score for the product of the object does not reach the second preset sub-score, it means that the user's first score for the object is a bad review, and / or the user's score for the product of the object does not reach the third preset sub-score, it means that the user's first score for the object is a bad review.

[0167] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0168] In one embodiment of the present disclosure, step S103 includes:

[0169] A first weighted value is obtained by weighted calculation of the user's first score for the object based on the first weight, a second weighted value is obtained by weighted calculation of the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighted calculation of the object's feedback on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are normalized to calculate the second score of the object as the overall score of the object within a preset time range.

[0170] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0171] In one embodiment of the present disclosure, the object evaluation processing method further includes:

[0172] Calculate and provide the change in the user's first score for the object within the current preset time range compared to the previous preset time range, the change in the user's evaluation of the object, the change in the object's feedback on the user's evaluation, and the change in the overall score.

[0173] According to the technical solution provided by the embodiment of the present disclosure, by calculating and providing the change of the first score of the user on the object within the current preset time range compared with the previous preset time range, the change of the user's evaluation of the object, the change of the feedback of the object on the user's evaluation, and the change of the overall score, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the score and evaluation on the object as a whole is improved. The processing of the score and evaluation by the user and the object will affect the overall score and the evaluation of the corresponding dimensions. Therefore, the scoring and evaluation of the object is more accurate, which is conducive to improving the scoring and evaluation of the object, and is also conducive to the user identifying the scoring and evaluation of each dimension of the object.

[0174] The following reference Figure 3 A subject evaluation processing device according to an embodiment of the present disclosure is described.

[0175] Figure 3 The structure block diagram of the object evaluation processing device according to the embodiment of the present disclosure is shown. The device 300 can be implemented by software, hardware or a combination of both.

[0176] like Figure 3 As shown, the object evaluation processing device 300 includes:

[0177] The acquisition module 301 is configured to acquire the first score of the user on the object, the evaluation of the user on the object, and the feedback of the object on the user's evaluation within a preset time range;

[0178] The weight calculation module 302 is configured to determine a first weight of the first score of the object given by the user within a preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation, based on whether the user's first score of the object within a preset time range meets a preset score standard;

[0179] The overall score calculation module 303 is configured to perform weighted calculation on the first score of the user on the object based on the first weight to obtain a first weighted value, perform weighted calculation on the evaluation of the user on the object based on the second weight to obtain a second weighted value, perform weighted calculation on the feedback of the object on the user's evaluation based on the third weight to obtain a third weighted value, and calculate the second score of the object as the overall score of the object within a preset time range by summing the first weighted value, the second weighted value and the third weighted value;

[0180] The evaluation providing module 304 is configured to provide the user's first rating of the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

[0181] According to the technical solution provided by the embodiment of the present disclosure, not only the user's rating of the object is considered, but also the user's evaluation of the object and the object's feedback on the user's evaluation, thereby expanding the dimension of object evaluation, expanding the evaluation distinction between objects, and improving the impact of the rating and evaluation on the object as a whole. The processing of the rating and evaluation by the user and the object will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to the user identifying the rating and evaluation of each dimension of the object.

[0182] In one embodiment of the present disclosure, the first rating of the object by the user includes the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user, and the first weight includes a first sub-weight of the rating of the object itself by the user, a second sub-weight of the rating of the product of the object by the user, and a third sub-weight of the rating of the packaging of the product of the object by the user,

[0183] Wherein, the overall score calculation module is further configured as follows:

[0184] Calculating a weighted score of the object by the user based on the score of the object by the user and the first sub-weight;

[0185] Calculate a weighted score of the product of the object by the user based on the score of the product of the object by the user and the second sub-weight;

[0186] Calculate a weighted score of the packaging of the product of the object by the user based on the score of the packaging of the product of the object by the user and the third sub-weight;

[0187] The first weighted value is calculated based on the weighted score of the object itself given by the user, the weighted score of the product of the object given by the user, and the weighted score of the packaging of the product of the object given by the user,

[0188] Wherein, the evaluation providing module is further configured to:

[0189] Provide the user's rating of the object itself within a preset time range, the user's rating of the object's product, the user's rating of the object's product packaging, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

[0190] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0191] In one embodiment of the present disclosure, the user's evaluation of the object includes the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content and the proportion of the orders between the user and the object that have the user's evaluation, and the second weight includes a fourth sub-weight of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content, and a fifth sub-weight of the proportion of the orders between the user and the object that have the user's evaluation,

[0192] Wherein, the overall score calculation module is further configured as follows:

[0193] Calculating a weighted value of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content based on the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content and the fourth sub-weight;

[0194] Calculating a weighted value of the proportion of orders with user evaluations among the orders between the user pair and the object based on the proportion of orders with user evaluations among the orders between the user pair and the object and the fifth sub-weight;

[0195] The second weighted value is calculated based on the weighted value of the proportion of the evaluation contents of the user's evaluation of the object that meet the preset evaluation conditions in the total evaluation contents and the weighted value of the proportion of the orders between the user and the object that have the user's evaluation.

[0196] Wherein, the evaluation providing module is further configured to:

[0197] Provide user ratings of the object itself within a preset time period, user ratings of the object's products, user ratings of the object's product packaging, the proportion of user evaluations of the object that meet preset evaluation conditions in all evaluations, the proportion of orders between the user and the object that include user evaluations, the object's feedback on the user's evaluation, and the overall rating.

[0198] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0199] In one embodiment of the present disclosure, the preset scoring standard is a preset score, and if the first score does not reach the preset score, it means that the user's first score for the object is a bad review.

[0200] Wherein, the weight calculation module is further configured as follows:

[0201] Based on the first rating of the object by the user within the preset time range being a bad rating, the first weight is set to a first weight value, the second weight is set to a second weight value, and the third weight is set to a third weight value, or

[0202] Based on the fact that the first rating of the object by the user within the preset time range is not a bad rating, the first weight is set to a fourth weight value, the second weight is set to a fifth weight value, and the third weight is set to a sixth weight value.

[0203] According to the technical solution provided by the embodiment of the present disclosure, the impact of the rating and evaluation on the object as a whole is improved, and the processing of the rating and evaluation by the user and the object will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to the user identifying the rating and evaluation of each dimension of the object.

[0204] In one embodiment of the present disclosure, the preset scores include a first preset sub-score of the user's score for the object itself, a second preset sub-score of the user's score for the product of the object, and a third preset sub-score of the user's score for the packaging of the product of the object, wherein if the user's score for the object itself does not reach the first preset sub-score, it means that the user's first score for the object is a bad review, and / or the user's score for the product of the object does not reach the second preset sub-score, it means that the user's first score for the object is a bad review, and / or the user's score for the product of the object does not reach the third preset sub-score, it means that the user's first score for the object is a bad review.

[0205] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0206] In one embodiment of the present disclosure, the overall score calculation module is further configured to:

[0207] A first weighted value is obtained by weighted calculation of the user's first score for the object based on the first weight, a second weighted value is obtained by weighted calculation of the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighted calculation of the object's feedback on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are normalized to calculate the second score of the object as the overall score of the object within a preset time range.

[0208] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0209] In one embodiment of the present disclosure, the object evaluation processing device further includes:

[0210] The evaluation change calculation and provision module is configured to calculate and provide the change of the user's first score of the object within the current preset time range compared with the previous preset time range, the change of the user's evaluation of the object, the change of the object's feedback on the user's evaluation, and the change of the overall score.

[0211] According to the technical solution provided by the embodiment of the present disclosure, through more specific object evaluation dimensions, the evaluation distinction between objects is expanded, and the impact of the rating and evaluation on the object as a whole is improved. The processing of the rating and evaluation by users and objects will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the object is more accurate, which is conducive to improving the rating and evaluation of the object, and is also conducive to users identifying the rating and evaluation of each dimension of the object.

[0212] In one embodiment of the present disclosure, a method for presenting merchant evaluation is provided, comprising:

[0213] Obtaining the user's rating of the merchant within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of orders between the user and the merchant that have user evaluations, and the merchant's feedback on the user's evaluation;

[0214] Based on whether one or all of the user's rating of the merchant itself, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging within the preset time range meet the preset rating standard, determine a first weight of the user's rating of the merchant itself within the preset time range, a second weight of the user's rating of the merchant's products, a third weight of the user's rating of the merchant's product packaging, a fourth weight of the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content, a fifth weight of the proportion of orders between the user and the merchant that have user evaluations, and a sixth weight of the merchant's feedback on the user's evaluation;

[0215] Based on the first weight, the user's rating of the merchant itself is weighted to obtain a first weighted value; based on the second weight, the user's rating of the merchant's product is weighted to obtain a second weighted value; based on the third weight, the user's rating of the merchant's product packaging is weighted to obtain a third weighted value; based on the fourth weight, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content is weighted to obtain a fourth weighted value; based on the fifth weight, the proportion of the orders between the user and the merchant that have the user's evaluation is weighted to obtain a fifth weighted value; based on the sixth weight, the merchant's feedback on the user's evaluation is weighted to obtain a sixth weighted value;

[0216] normalizing the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value, and the sixth weighted value to calculate a second score of the object as an overall score of the object within a preset time range,

[0217] The overall rating, the user's rating of the merchant itself, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of user evaluation content on the merchant that meets preset evaluation conditions in the total evaluation content, the proportion of orders between users and merchants that include user evaluations, and the merchant's feedback on user evaluations are presented.

[0218] According to the technical solution provided by the embodiment of the present disclosure, not only the user's rating of the merchant is considered, but also the user's evaluation of the merchant and the merchant's feedback on the user's evaluation, thereby expanding the dimension of merchant evaluation, expanding the evaluation distinction between merchants, and improving the impact of the rating and evaluation on the merchant as a whole. The processing of the rating and evaluation by users and merchants will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the merchant are more accurate, which is conducive to the merchant to improve the rating and evaluation, and is also conducive to the user to identify the rating and evaluation of each dimension of the merchant.

[0219] In one embodiment of the present disclosure, a merchant evaluation presentation device is provided, comprising:

[0220] The acquisition module is configured to acquire the user's rating of the merchant itself within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of the orders between the user and the merchant that have the user's evaluation, and the merchant's feedback on the user's evaluation;

[0221] The weight calculation module is configured to determine, based on whether one or all of the user's rating of the merchant itself, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging within the preset time range meet the preset rating standard, a first weight of the user's rating of the merchant itself within the preset time range, a second weight of the user's rating of the merchant's products, a third weight of the user's rating of the merchant's product packaging, a fourth weight of the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, a fifth weight of the proportion of the orders between the user and the merchant that have the user's evaluation, and a sixth weight of the merchant's feedback on the user's evaluation;

[0222] The weighted value calculation module is configured to perform weighted calculation on the user's rating of the merchant itself based on the first weight to obtain a first weighted value, perform weighted calculation on the user's rating of the merchant's product based on the second weight to obtain a second weighted value, perform weighted calculation on the user's rating of the merchant's product packaging based on the third weight to obtain a third weighted value, perform weighted calculation on the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content based on the fourth weight to obtain a fourth weighted value, perform weighted calculation on the proportion of orders between the user and the merchant that have user evaluations based on the fifth weight to obtain a fifth weighted value, and perform weighted calculation on the merchant's feedback on the user's evaluation based on the sixth weight to obtain a sixth weighted value;

[0223] an overall score calculation module, configured to perform normalization processing on the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value, and the sixth weighted value to calculate a second score of the object as the overall score of the object within a preset time range,

[0224] The presentation module is configured to present the overall score, the user's score for the merchant itself, the user's score for the merchant's products, the user's score for the merchant's product packaging, the proportion of user evaluation content on the merchant that meets preset evaluation conditions in all evaluation content, the proportion of orders between users and merchants that include user evaluations, and the merchant's feedback on user evaluations.

[0225] According to the technical solution provided by the embodiment of the present disclosure, not only the user's rating of the merchant is considered, but also the user's evaluation of the merchant and the merchant's feedback on the user's evaluation, thereby expanding the dimension of merchant evaluation, expanding the evaluation distinction between merchants, and improving the impact of the rating and evaluation on the merchant as a whole. The processing of the rating and evaluation by users and merchants will affect the overall rating and the evaluation of the corresponding dimensions. Therefore, the rating and evaluation of the merchant are more accurate, which is conducive to the merchant to improve the rating and evaluation, and is also conducive to the user to identify the rating and evaluation of each dimension of the merchant.

[0226] Those skilled in the art will understand that referring to Figure 3 The technical solutions described can be compared with Figure 1 Combined with the embodiment described in FIG. 2 , thus having reference Figure 1 The technical effects achieved by the embodiment described in FIG. 2 are as follows. Figure 1 The specific contents of the description in FIG. 2 will not be repeated here.

[0227] The present disclosure also discloses an electronic device, Figure 4 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0228] like Figure 4 As shown, the electronic device 400 includes a memory 401 and a processor 402, wherein the memory 401 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 402 to implement the above reference Figure 1 and the steps of the object evaluation processing method described in FIG. 2 .

[0229] Figure 5 A schematic diagram showing the structure of a computer device suitable for implementing the method according to an embodiment of the present disclosure is shown.

[0230] like Figure 5 As shown, the computer device 500 includes a processing unit 501, which can perform various processes in the above-mentioned embodiments according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 are also stored. The processing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0231] The following components are connected to the I / O interface 505: an input part 506 including a keyboard, a mouse, etc.; an output part 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage part 508 including a hard disk, etc.; and a communication part 509 including a network interface card such as a LAN card, a modem, etc. The communication part 509 performs communication processing via a network such as the Internet. The drive 510 is also connected to the I / O interface 505 as needed. Removable media 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive 510 as needed, so that the computer program read therefrom is installed into the storage part 508 as needed. Among them, the processing unit 501 can be implemented as a processing unit such as a CPU, a GPU, a TPU, an FPGA, an NPU, etc.

[0232] In particular, according to an embodiment of the present disclosure, the method described above can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes computer instructions, and the computer instructions are executed by a processor to implement the method steps described above. In such an embodiment, the computer program product can be downloaded and installed from a network through the communication part 509, and / or installed from a removable medium 511.

[0233] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the devices, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based device that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0234] The units or modules involved in the embodiments described in the present disclosure may be implemented by software or programmable hardware. The units or modules described may also be set in a processor, and the names of these units or modules do not constitute limitations on the units or modules themselves in some cases.

[0235] As another aspect, the present disclosure further provides a computer-readable storage medium, which may be a computer-readable storage medium included in the electronic device or computer device in the above embodiment; or a computer-readable storage medium that exists independently and is not assembled into the device. The computer-readable storage medium stores one or more programs, and the programs are used by one or more processors to execute the method described in the present disclosure.

[0236] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present disclosure is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other.

Claims

1. A method for object evaluation processing, comprising: Obtain the user's first rating of the object within a preset time range, the user's evaluation of the object, and the object's feedback on the user's evaluation; Based on whether the first rating of the object by the user within the preset time range meets the preset rating standard, determine a first weight of the first rating of the object by the user within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation; Based on the first weight, a first score of the object given by the user is weighted to obtain a first weighted value; based on the second weight, a second weighted value is weighted to obtain a second weighted value; based on the third weight, a feedback of the object on the user's evaluation is weighted to obtain a third weighted value; and the first weighted value, the second weighted value and the third weighted value are summed to calculate a second score of the object as an overall score of the object within a preset time range; Providing the user's first rating of the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating; The user's evaluation of the object includes the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content and the proportion of the orders between the user and the object that have the user's evaluation; The preset evaluation condition specifically includes that the user's evaluation content of the object includes a predetermined number of pictures and a predetermined number of words.

2. The method according to claim 1, wherein: The first rating of the object by the user includes the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user; the first weight includes a first sub-weight of the rating of the object itself by the user, a second sub-weight of the rating of the product of the object by the user, and a third sub-weight of the rating of the packaging of the product of the object by the user; The step of performing weighted calculation on the first score given to the object by the user based on the first weight to obtain a first weighted value includes: Calculating a weighted score of the object by the user based on the score of the object by the user and the first sub-weight; Calculate a weighted score of the product of the object by the user based on the score of the product of the object by the user and the second sub-weight; Calculate a weighted score of the packaging of the product of the object by the user based on the score of the packaging of the product of the object by the user and the third sub-weight; The first weighted value is calculated based on the weighted score of the object itself given by the user, the weighted score of the product of the object given by the user, and the weighted score of the packaging of the product of the object given by the user, The providing of the first rating of the object by the user within a preset time range, the evaluation of the object by the user, the feedback of the object on the user's evaluation, and the overall rating includes: Provide the user's rating of the object itself within a preset time range, the user's rating of the object's product, the user's rating of the object's product packaging, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

3. The method according to claim 2, wherein: The second weight includes a fourth sub-weight of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content, and a fifth sub-weight of the proportion of the orders between the user and the object that contain user evaluations. The step of performing weighted calculation on the user's evaluation of the object based on the second weight to obtain a second weighted value includes: Calculating a weighted value of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content based on the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content and the fourth sub-weight; Calculating a weighted value of the proportion of orders with user evaluations among the orders between the user pair and the object based on the proportion of orders with user evaluations among the orders between the user pair and the object and the fifth sub-weight; The second weighted value is calculated based on the weighted value of the proportion of the evaluation contents of the user's evaluation of the object that meet the preset evaluation conditions in the total evaluation contents and the weighted value of the proportion of the orders between the user and the object that have the user's evaluation. The providing of the first rating of the object by the user within a preset time range, the evaluation of the object by the user, the feedback of the object on the user's evaluation, and the overall rating includes: Provide user ratings of the object itself within a preset time period, user ratings of the object's products, user ratings of the object's product packaging, the proportion of user evaluations of the object that meet preset evaluation conditions in all evaluations, the proportion of orders between the user and the object that include user evaluations, the object's feedback on the user's evaluation, and the overall rating.

4. The method according to any one of claims 1 to 3, wherein: The preset scoring standard is a preset score, and if the first score does not reach the preset score, it means that the user's first score for the object is a bad review. The method of determining a first weight of the first score of the object by the user within the preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation within the preset time range based on whether the user's first score of the object within the preset time range meets the preset score standard includes: Based on the first rating of the object by the user within the preset time range being a bad rating, the first weight is set to a first weight value, the second weight is set to a second weight value, and the third weight is set to a third weight value, or Based on the fact that the first rating of the object by the user within the preset time range is not a bad rating, the first weight is set to a fourth weight value, the second weight is set to a fifth weight value, and the third weight is set to a sixth weight value.

5. The method according to claim 4, wherein: The preset scores include a first preset sub-score for the user's score on the object itself, a second preset sub-score for the user's score on the product of the object, and a third preset sub-score for the user's score on the packaging of the product of the object, wherein if the user's score on the object itself does not reach the first preset sub-score, it means that the user's first score on the object is a bad review, and / or the user's score on the product of the object does not reach the second preset sub-score, it means that the user's first score on the object is a bad review, and / or the user's score on the packaging of the product of the object does not reach the third preset sub-score, it means that the user's first score on the object is a bad review.

6. The method according to claim 1, wherein: The first weighted value is obtained by weighted calculation of the first score of the object by the user based on the first weight, the second weighted value is obtained by weighted calculation of the evaluation of the object by the user based on the second weight, the third weighted value is obtained by weighted calculation of the feedback of the object on the user's evaluation based on the third weight, and the second score of the object is calculated as the overall score of the object within a preset time range by summing the first weighted value, the second weighted value and the third weighted value. The method includes: A first weighted value is obtained by weighted calculation of the user's first score for the object based on the first weight, a second weighted value is obtained by weighted calculation of the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighted calculation of the object's feedback on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are normalized to calculate the second score of the object as the overall score of the object within a preset time range.

7. The method according to any one of claims 1 to 3, further comprising: Calculate and provide the change in the user's first score for the object within the current preset time range compared to the previous preset time range, the change in the user's evaluation of the object, the change in the object's feedback on the user's evaluation, and the change in the overall score.

8. An object evaluation processing device, comprising: An acquisition module is configured to acquire a user's first rating of an object, a user's evaluation of the object, and the object's feedback on the user's evaluation within a preset time range; A weight calculation module is configured to determine a first weight of the first score of the object given by the user within a preset time range, a second weight of the user's evaluation of the object, and a third weight of the object's feedback on the user's evaluation based on whether the user's first score of the object within a preset time range meets a preset score standard; an overall score calculation module, configured to perform weighted calculation on the first score of the user on the object based on the first weight to obtain a first weighted value, perform weighted calculation on the evaluation of the user on the object based on the second weight to obtain a second weighted value, perform weighted calculation on the feedback of the object on the user's evaluation based on the third weight to obtain a third weighted value, and calculate the second score of the object as the overall score of the object within a preset time range by summing the first weighted value, the second weighted value and the third weighted value; An evaluation providing module is configured to provide a first score of the user on the object within a preset time range, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall score; The user's evaluation of the object includes the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content and the proportion of the orders between the user and the object that have the user's evaluation; The preset evaluation condition specifically includes that the user's evaluation content of the object includes a predetermined number of pictures and a predetermined number of words.

9. The device according to claim 8, wherein: The first rating of the object by the user includes the rating of the object itself by the user, the rating of the product of the object by the user, and the rating of the packaging of the product of the object by the user; the first weight includes a first sub-weight of the rating of the object itself by the user, a second sub-weight of the rating of the product of the object by the user, and a third sub-weight of the rating of the packaging of the product of the object by the user; Wherein, the overall score calculation module is further configured as follows: Calculating a weighted score of the object by the user based on the score of the object by the user and the first sub-weight; Calculate a weighted score of the product of the object by the user based on the score of the product of the object by the user and the second sub-weight; Calculate a weighted score of the packaging of the product of the object by the user based on the score of the packaging of the product of the object by the user and the third sub-weight; The first weighted value is calculated based on the weighted score of the object itself given by the user, the weighted score of the product of the object given by the user, and the weighted score of the packaging of the product of the object given by the user, Wherein, the evaluation providing module is further configured to: Provide the user's rating of the object itself within a preset time range, the user's rating of the object's product, the user's rating of the object's product packaging, the user's evaluation of the object, the object's feedback on the user's evaluation, and the overall rating.

10. The device according to claim 9, wherein: The second weight includes a fourth sub-weight of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation conditions in the total evaluation content, and a fifth sub-weight of the proportion of the orders between the user and the object that contain user evaluations. Wherein, the overall score calculation module is further configured as follows: Calculating a weighted value of the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content based on the proportion of the evaluation content of the user's evaluation of the object that meets the preset evaluation condition in the total evaluation content and the fourth sub-weight; Calculating a weighted value of the proportion of orders with user evaluations among the orders between the user pair and the object based on the proportion of orders with user evaluations among the orders between the user pair and the object and the fifth sub-weight; The second weighted value is calculated based on the weighted value of the proportion of the evaluation contents of the user's evaluation of the object that meet the preset evaluation conditions in the total evaluation contents and the weighted value of the proportion of the orders between the user and the object that have the user's evaluation. Wherein, the evaluation providing module is further configured to: Provide user ratings of the object itself within a preset time period, user ratings of the object's products, user ratings of the object's product packaging, the proportion of user evaluations of the object that meet preset evaluation conditions in all evaluations, the proportion of orders between the user and the object that include user evaluations, the object's feedback on the user's evaluation, and the overall rating.

11. The device according to any one of claims 8 to 10, wherein: The preset scoring standard is a preset score, and if the first score does not reach the preset score, it means that the user's first score for the object is a bad review. Wherein, the weight calculation module is further configured as follows: Based on the first rating of the object by the user within the preset time range being a bad rating, the first weight is set to a first weight value, the second weight is set to a second weight value, and the third weight is set to a third weight value, or Based on the fact that the first rating of the object by the user within the preset time range is not a bad rating, the first weight is set to a fourth weight value, the second weight is set to a fifth weight value, and the third weight is set to a sixth weight value.

12. The device according to claim 11, wherein The preset scores include a first preset sub-score for the user's score on the object itself, a second preset sub-score for the user's score on the product of the object, and a third preset sub-score for the user's score on the packaging of the product of the object, wherein if the user's score on the object itself does not reach the first preset sub-score, it means that the user's first score on the object is a bad review, and / or the user's score on the product of the object does not reach the second preset sub-score, it means that the user's first score on the object is a bad review, and / or the user's score on the packaging of the product of the object does not reach the third preset sub-score, it means that the user's first score on the object is a bad review.

13. The device according to claim 8, wherein: The overall score calculation module is also configured to: A first weighted value is obtained by weighted calculation of the user's first score for the object based on the first weight, a second weighted value is obtained by weighted calculation of the user's evaluation of the object based on the second weight, a third weighted value is obtained by weighted calculation of the object's feedback on the user's evaluation based on the third weight, and the first weighted value, the second weighted value and the third weighted value are normalized to calculate the second score of the object as the overall score of the object within a preset time range.

14. The device according to any one of claims 8 to 10, further comprising: The evaluation change calculation and provision module is configured to calculate and provide the change of the user's first score of the object within the current preset time range compared with the previous preset time range, the change of the user's evaluation of the object, the change of the object's feedback on the user's evaluation, and the change of the overall score.

15. A method for presenting merchant evaluations, comprising: Obtaining the user's rating of the merchant within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of orders between the user and the merchant that have user evaluations, and the merchant's feedback on the user's evaluation; Based on whether one or all of the user's rating of the merchant itself, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging within the preset time range meet the preset rating standard, determine a first weight of the user's rating of the merchant itself within the preset time range, a second weight of the user's rating of the merchant's products, a third weight of the user's rating of the merchant's product packaging, a fourth weight of the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content, a fifth weight of the proportion of orders between the user and the merchant that have user evaluations, and a sixth weight of the merchant's feedback on the user's evaluation; Based on the first weight, the user's rating of the merchant itself is weighted to obtain a first weighted value; based on the second weight, the user's rating of the merchant's product is weighted to obtain a second weighted value; based on the third weight, the user's rating of the merchant's product packaging is weighted to obtain a third weighted value; based on the fourth weight, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content is weighted to obtain a fourth weighted value; based on the fifth weight, the proportion of the orders between the user and the merchant that have the user's evaluation is weighted to obtain a fifth weighted value; based on the sixth weight, the merchant's feedback on the user's evaluation is weighted to obtain a sixth weighted value; normalizing the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value, and the sixth weighted value to calculate a second score of the object as an overall score of the object within a preset time range, Present the overall rating, the user's rating of the merchant itself, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of orders between the user and the merchant that have user evaluations, and the merchant's feedback on the user's evaluation; The preset evaluation condition specifically includes that the user's evaluation content of the object includes a predetermined number of pictures and a predetermined number of words.

16. A merchant evaluation presentation device, comprising: The acquisition module is configured to acquire the user's rating of the merchant itself within a preset time range, the user's rating of the merchant's products, the user's rating of the merchant's product packaging, the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of the orders between the user and the merchant that have the user's evaluation, and the merchant's feedback on the user's evaluation; The weight calculation module is configured to determine, based on whether one or all of the user's rating of the merchant itself, the user's rating of the merchant's products, and the user's rating of the merchant's product packaging within the preset time range meet the preset rating standard, a first weight of the user's rating of the merchant itself within the preset time range, a second weight of the user's rating of the merchant's products, a third weight of the user's rating of the merchant's product packaging, a fourth weight of the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in the total evaluation content, a fifth weight of the proportion of the orders between the user and the merchant that have the user's evaluation, and a sixth weight of the merchant's feedback on the user's evaluation; The weighted value calculation module is configured to perform weighted calculation on the user's rating of the merchant itself based on the first weight to obtain a first weighted value, perform weighted calculation on the user's rating of the merchant's product based on the second weight to obtain a second weighted value, perform weighted calculation on the user's rating of the merchant's product packaging based on the third weight to obtain a third weighted value, perform weighted calculation on the proportion of the user's evaluation content of the merchant that meets the preset evaluation conditions in all the evaluation content based on the fourth weight to obtain a fourth weighted value, perform weighted calculation on the proportion of orders between the user and the merchant that have user evaluations based on the fifth weight to obtain a fifth weighted value, and perform weighted calculation on the merchant's feedback on the user's evaluation based on the sixth weight to obtain a sixth weighted value; an overall score calculation module, configured to perform normalization processing on the first weighted value, the second weighted value, the third weighted value, the fourth weighted value, the fifth weighted value, and the sixth weighted value to calculate a second score of the object as the overall score of the object within a preset time range; A presentation module is configured to present the overall score, the user's score for the merchant itself, the user's score for the merchant's products, the user's score for the merchant's product packaging, the proportion of the user's evaluation content on the merchant that meets the preset evaluation conditions in the total evaluation content, the proportion of the orders between the user and the merchant that have the user's evaluation, and the merchant's feedback on the user's evaluation; The preset evaluation condition specifically includes that the user's evaluation content of the object includes a predetermined number of pictures and a predetermined number of words.

17. An electronic device comprising a memory and a processor; wherein: The memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps described in any one of claims 1-7 and 15.

18. A readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the method steps described in any one of claims 1-7 and 15.

19. A computer program product comprising computer instructions, which, when executed by a processor, implement the method steps described in any one of claims 1-7 and 15.

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