CN117273832A

CN117273832A - Evaluation method, device and system

Info

Publication number: CN117273832A
Application number: CN202210411748.5A
Authority: CN
Inventors: 马山河
Original assignee: Hebei Xiongan 3000 Technology Co ltd
Current assignee: Hebei Xiongan 3000 Technology Co ltd
Priority date: 2022-04-19
Filing date: 2022-04-19
Publication date: 2023-12-22

Abstract

The embodiment of the specification provides an evaluation method, an evaluation device and an evaluation system, wherein the evaluation method comprises the following steps: acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information; synthesizing user anonymous identity information of the user and activity codes of the activities under the condition that the user participates in the activities, generating activity feature codes, and endowing the activity feature codes to activity participators, wherein the activity participators comprise the user and/or the activity party of the activities; responding to the initial scores submitted by any one of the activity participants for other activity participants by using the activity feature codes, and obtaining the reputation coefficient of any one of the activity participants; and calculating the initial scores by using the credit coefficients of any activity participants, and calculating the credibility scores of any activity participant on the other activity participants.

Description

Evaluation method, device and system

Technical Field

The embodiment of the specification relates to the technical field of computers, in particular to an evaluation method.

Background

To improve the quality of online service, online platforms typically allow users to submit scores to activities such as goods or services. The user needs to become a registered user of the online platform, and then uses the registered real identity to participate in activities such as commodity transaction, service and the like of the online platform. After participating in an activity, the user needs to score the activity using the registered true identity.

However, users submit scores on an online platform using a true identity, which, while guaranteeing the authenticity of the scores, exposes the privacy of the user. Therefore, some online platforms also allow users to submit scores using various identities at will, but this in turn results in the appearance of a large number of water armies, which cannot protect the privacy of the users at the same time while guaranteeing the authenticity and credibility of the scores. Therefore, the current evaluation mode cannot meet the various requirements of protecting the privacy, the authenticity and the credibility of the user.

Disclosure of Invention

In view of this, the present embodiment provides an evaluation method. One or more embodiments of the present specification relate to an evaluation apparatus, an evaluation system, a computing device, a computer-readable storage medium, and a computer program that solve the technical drawbacks existing in the prior art.

According to a first aspect of embodiments of the present specification, there is provided an evaluation method including: acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information; synthesizing user anonymous identity information of the user and activity codes of the activities under the condition that the user participates in the activities, generating activity feature codes, and endowing the activity feature codes to activity participators, wherein the activity participators comprise the user and/or the activity party of the activities; responding to the initial scores submitted by any one of the activity participants for other activity participants by using the activity feature codes, and obtaining the reputation coefficient of any one of the activity participants; and calculating the initial scores by using the credit coefficients of any activity participants, and calculating the credibility scores of any activity participant on the other activity participants.

According to a second aspect of embodiments of the present specification, there is provided an evaluation device comprising: and the information protection component is configured to acquire the real identity information of the user and generate anonymous identity information of the user based on the real identity information. And the feature code generating component is configured to synthesize the user anonymous identity information of the user and the activity code of the activity under the condition that the user participates in the activity, generate an activity feature code and endow the activity feature code to an activity participant, wherein the activity participant comprises the user and/or the activity participant of the activity. An evaluation response component configured to obtain reputation coefficients of any of the active participants in response to the active participants submitting initial scores for other active participants using the activity feature code. And a score calculating component configured to calculate the initial score by using the reputation coefficient of any one of the activity participants, and calculate the credibility scores of the other activity participants by the any one of the activity participants.

According to a third aspect of embodiments of the present specification, there is provided an evaluation system comprising: the server side is configured to acquire real identity information of a user, generate user anonymous identity information based on the real identity information, synthesize the user anonymous identity information of the user and an activity code of the activity under the condition that the user participates in the activity, generate an activity feature code, and endow the activity feature code to an activity participant, wherein the activity participant comprises the user and/or the activity participant, and respond to the fact that any activity participant submits initial scores for other activity participants by using the activity feature code, acquire reputation coefficients of any activity participant, calculate the initial scores by using the reputation coefficients of any activity participant, and calculate the credible scores of any activity participant on the other activity participants. A first client configured for the any one of the active participants to submit initial scores for the other active participants using the activity feature code.

According to a fourth aspect of embodiments of the present specification, there is provided a computing device comprising: a memory and a processor; the memory is configured to store computer-executable instructions that, when executed by the processor, perform the steps of the evaluation method described above.

According to a fifth aspect of embodiments of the present specification, there is provided a computer-readable storage medium storing computer-executable instructions which, when executed by a processor, implement the steps of the above-described evaluation method.

According to a sixth aspect of the embodiments of the present specification, there is provided a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-described evaluation method.

According to the evaluation method, a server side of the method obtains real identity information of a user, generates user anonymous identity information based on the real identity information, synthesizes the user anonymous identity information of the user and an activity code of the activity under the condition that the user participates in the activity, generates an activity feature code, and endows the activity feature code to an activity participant, wherein the activity participant comprises the user and/or the activity participant of the activity, and responds to the fact that any activity participant submits initial scores for other activity participants by using the activity feature code, the reputation coefficient of any activity participant is obtained, the initial scores are calculated by using the reputation coefficient of any activity participant, and the credibility scores of any activity participant are calculated.

Drawings

FIG. 1 is a flow chart of a method of evaluation provided in one embodiment of the present disclosure;

FIG. 2 is a process flow diagram of an evaluation method provided in one embodiment of the present disclosure;

FIG. 3 is a process flow diagram of an evaluation method according to another embodiment of the present disclosure;

FIG. 4 is a process flow diagram of an evaluation method according to another embodiment of the present disclosure;

fig. 5 is a schematic flow chart of an evaluation method according to an embodiment of the present disclosure.

Fig. 6 is a schematic diagram showing the effect of an evaluation method according to an embodiment of the present disclosure.

FIG. 7 is a schematic view showing the structure of an evaluation apparatus according to an embodiment of the present disclosure;

FIG. 8 is a schematic diagram of an evaluation system according to an embodiment of the present disclosure;

FIG. 9 is a schematic diagram of an evaluation system according to another embodiment of the present disclosure;

FIG. 10 is a block diagram of a computing device provided in one embodiment of the present description.

Detailed Description

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many other forms than described herein and similarly generalized by those skilled in the art to whom this disclosure pertains without departing from the spirit of the disclosure and, therefore, this disclosure is not limited by the specific implementations disclosed below.

The terminology used in the one or more embodiments of the specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of the specification. As used in this specification, one or more embodiments and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any or all possible combinations of one or more of the associated listed items.

It should be understood that, although the terms first, second, etc. may be used in one or more embodiments of this specification to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first may also be referred to as a second, and similarly, a second may also be referred to as a first, without departing from the scope of one or more embodiments of the present description. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.

In the present specification, an evaluation method is provided, and the present specification relates to an evaluation apparatus, an evaluation system, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

Referring to fig. 1, fig. 1 shows a flowchart of an evaluation method according to an embodiment of the present specification, which specifically includes the following steps.

Step 102: acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information.

Wherein the user may be understood as a registered user of the online platform. An online platform refers to a platform for providing various activities such as commodity transaction, service and the like for users based on Internet online. The real identity information used by the user on the online platform may include, for example, but is not limited to, personal or organizational unique identity information such as name, credential number, residence address information, social security information, and the like.

The specific implementation mode of generating the user anonymous identity information based on the real identity information is not limited, and the purpose of protecting the privacy of the user can be achieved as long as the active party and other users can not know the real identity of the user through the user anonymous identity information. In addition, the process of generating user anonymous identity information based on real identity information is reversible so that when a dispute occurs in a rating, a relevant party, such as a rating scale, can trace back to the real identity information to determine the user in order to resolve the dispute.

For example, in one or more embodiments of the present disclosure, encryption information set by a user may be obtained, and encryption of the real identity information using the encryption information set by the user generates the anonymous identity information of the user. The encryption information may be an encryption password set by a user. In addition, the anonymous identity information of the user can be decrypted as required under the condition of obtaining the authorization so as to trace back to obtain the real identity information of the user.

Step 104: and under the condition that the user participates in the activity, synthesizing the user anonymous identity information of the user and the activity code of the activity to generate an activity feature code, and endowing the activity feature code to an activity participant, wherein the activity participant comprises the user and/or the activity participant of the activity.

The activity can be understood as any activity that a user can participate in, such as commodity transaction activity, payment activity, service activity and the like of the online platform. The active party may be understood as a registered active party of the online platform, which is a transaction object of the activity, for example, the active party may appear as any service or product among services or products offered by merchants, etc. Of course, in some application scenarios, the active party may also directly appear as a service provider for a merchant, store, or the like.

Wherein the activity code of the activity can be understood as information for identifying the activity. For example, in one or more embodiments of the present description, to protect the privacy of the active party from exposure, the method may further include: and acquiring the real characteristic data of the activity, and encrypting the real characteristic data by utilizing the encryption information set by the activity party to generate the activity code. Wherein the real characteristic data of the activity may be identity information unique to a product such as a product number. Of course, depending on the actual application scenario requirements, if the privacy of the active party does not have privacy requirements, the active code may also be equal to the plaintext information identifying the activity, for example, may be the plaintext of the product number.

In addition, although the anonymous identity information of the user adopts encryption means and cannot identify the user, the anonymous identity information of the user is still sensitive information, and in order to protect the information security of both evaluation parties, the service end needs to obtain authorization of both parties for using the anonymous identity information of the user and the activity code. Specifically, before the generating the active feature code, the method further includes: and judging whether the authorization of the user and the active party is obtained, and if so, allowing the generation of the active feature code. For example, the server may issue an authorization permission request to both parties at any time before the active party makes an evaluation, and regenerate the active feature code after being permitted.

Wherein, the implementation mode of synthesizing the user anonymous identity information of the user and the activity code of the activity is not limited. For example, the user anonymous identity information and the activity codes of the activities may be directly spliced to obtain activity feature codes. For another example, the anonymous identity information of the user and the activity codes of the activities may be mixed according to a preset rule to obtain activity feature codes. When the activity feature codes are generated, the activity feature codes of any one of the activity participants can be generated according to the fact scene requirement, the activity feature codes of a plurality of different activity participants can be generated, and the activity feature codes of different activity participants can be different. It can be appreciated that, because the activity feature code can be used by any activity participant to publish the score as an identity, the extrinsic form of the information of the activity feature code can be presented as clear information that is easier for a person to understand that the publisher is the activity participant, and thus any activity participant can use the clear information as an identity for submitting the score.

In addition, the process of synthesizing the anonymous identity information of the user and the activity code to obtain the activity feature code is reversible, so that when the evaluation disputes, the anonymous identity information of the user can be traced back to the activity code from the activity feature code, and the true identity of the parties participating in the activity is determined to solve the dispute. Specifically, for example, the method may further include: acquiring an activity feature code of any one of the activity participants submitting the initial score; analyzing the activity feature code to trace back to obtain user anonymous identity information of the user and the activity code; analyzing the anonymous identity information of the user to trace back to obtain the real identity information of the user; analyzing the activity codes to trace back to obtain real characteristic data of the activity; determining the user based on the true identity information; the active party is determined based on the real characteristic data.

The specific method for analyzing and tracing is not limited, and reverse analysis rules can be set according to the active feature codes, anonymous identity information and the generation rules of the active codes. For example, the activity feature code is obtained by splicing, and then the user anonymous identity information and the activity code can be obtained by reversely disassembling in a splicing mode. For another example, the anonymous information of the user is obtained through encryption, and then the user can be decrypted according to the password to obtain the true identity information of the user.

In addition, in one or more embodiments of the present disclosure, to facilitate the user participating in the evaluation with the activity party, the synthesizing the user anonymous identity information of the user and the activity code of the activity to generate an activity feature code and assign the activity feature code to the activity party when the user participates in the activity may include:

synthesizing user anonymous identity information of the user and activity codes of the activity according to a preset user activity code generation rule under the condition that the user participates in the activity, generating a user activity feature code, and giving the user activity feature code to the user;

And under the condition that the user participates in the activity, synthesizing the user anonymous identity information of the user and the activity code of the activity according to a preset activity code generation rule of the activity party, generating an activity characteristic code of the activity party, and endowing the activity characteristic code of the activity party to the activity party.

Wherein, the preset user activity code generation rule is different from the preset activity party activity code generation rule. For example, in one embodiment, the preset user activity code generation rule and the activity party activity code generation rule are that after splicing the anonymous identity information of the user and the activity code, different symbols are respectively and correspondingly added to distinguish the two activity feature codes. For another embodiment, the preset user activity code generation rule and the activity party activity code generation rule splice the anonymous identity information of the user and the activity code according to different sequences.

Step 106: and responding to the initial scores submitted by any one of the activity participants for other activity participants by using the activity feature codes, and acquiring the reputation coefficients of the any one of the activity participants.

It can be understood that the activity feature code is the exclusive information given to the activity participant by the server, and the activity participant can submit the score using the activity feature code only after being given the activity feature code, so that other users cannot score using the activity feature code.

For example, in the case where any of the active parties is a user, the reputation coefficient of the user may be obtained in response to the user submitting a first score for the active party using the user activity feature code.

For another example, in the case where any of the active participants is an active party, the reputation coefficient of the active party may be obtained in response to the active party submitting a second score for the user using the active party feature code.

Wherein the reputation coefficient may be determined from historical rating data of the any of the active participants.

The initial score can be expressed as any form of evaluation information with high and low score meanings such as numbers, letters and characters. For example: in the application scenario that the score ranges from low to high to 0 to 9, the initial score may be any number from 0 to 9. For another example, in an application scenario where the score ranges from low to high as a to G, the initial score may be any of letters a to G. For another example, in the application scenario where the score ranges from poor, generally, medium, good to excellent, the initial score may be any score from poor, generally, medium, good to excellent.

Wherein the reputation coefficient, which may also be understood as a scoring confidence, is determined based on the historical rating data of the user. For example, the initial value of the reputation coefficient for each user may be the same, defaulting to 1 or 100%. Each time a user publishes a score or is scored, it may be correspondingly recorded in the user's historical rating data. When the reputation coefficient needs to be updated, the latest reputation coefficient of the user can be calculated by using a preset reputation evaluation algorithm and records affecting the reputation coefficient of the user in historical evaluation data on the basis of the current reputation coefficient. For example, when the user has a scored score lower than the lower score limit, a certain point number can be reduced based on the current reputation coefficient to reduce the reputation of the user, and when the user has a scored score higher than the upper score limit, a certain point number can be increased based on the current reputation coefficient to improve the reputation of the user. For another example, when the user has a malicious score for another person, a certain point number may be reduced based on the current reputation coefficient, so that the reputation thereof is reduced.

It will be appreciated that when any of the active participants submits a score, the corresponding statement facts may be submitted simultaneously. Stating facts helps to improve the understanding of public and rated parties in restoring facts and scoring, therefore, in one or more embodiments of the present description, the obtaining reputation coefficients of any of the active participants in response to any of the active participants submitting an initial score for other active participants using the activity feature code may comprise: in response to the any one of the active participants submitting a statement fact for the other active participants using the activity feature code, an initial score of the any one of the active participants submitting the statement fact is received, and a reputation coefficient of the any one of the active participants is obtained.

Wherein said statement fact is to be understood as an information carrier submitted by said any one of the active participants for explaining the fact and reason, and may comprise any form of information carrier such as text, images, video, audio, etc. For example, if a user purchases a commodity on an online platform, a score for the commodity and a piece of fact-indicating text for the quality of the commodity may be submitted in a review area of the commodity on the online platform. It should be noted that the fact may require that any of the active participants as the primary score (which may be understood as the actual presenters) submit each time the score reaches a certain preset range, or may require that the score be submitted when it reaches a preset range. For example, the any active participant may be required to have to state facts when submitted scores are outside of 50 to 70 scores.

Step 108: and calculating the initial scores by using the credit coefficients of any activity participants, and calculating the credibility scores of any activity participant on the other activity participants.

For example, in combination with the above example, in the case where any active party is a user, the first score may be calculated using the reputation coefficient of the user, and a trusted score for the user for the active party may be calculated;

In the case where any of the active participants is an active party, the reputation coefficient of the active party may be used to calculate the second score, and a trusted score of the active party for the user may be calculated.

The specific algorithm for calculating the initial score by using the reputation coefficient is not limited, and the reliability of the score can be increased only after the reputation coefficient is converted.

For example, when the reputation coefficient of any active participant is higher than the average of the reputation coefficients of the platform, the initial score submitted by any active participant can be understood as being trusted, and the initial score is directly taken as the trusted score.

For another example, when the reputation coefficient of any active participant is lower than the average of the reputation coefficients of the platform, it may be understood that the reliability of the initial score submitted by any active participant is lower, and the initial score needs to be converted, for example, the following manner may be adopted:

if the initial score is higher than the normal value, calculating a virtual high score based on a conversion formula based on the reputation coefficient, subtracting the virtual high score from the initial score to obtain a trusted score, and if the initial score is lower than the normal value, calculating a virtual low score based on the conversion formula by using the reputation coefficient, and adding the virtual low score to the initial score to obtain the trusted score. For example:

Assuming that the reputation coefficient of any active participant is 0.8, the reputation coefficient of the platform is 0.6 in average value, the score normal value is 5, and under the condition that the initial score submitted by any active participant is 8, the credibility score is 8;

assuming that the user reputation coefficient of any active participant is 0.4, the average value of the reputation coefficients of the platform is 0.6, and under the condition that the initial score submitted by any active participant is 8, the reputation coefficient of 0.4 is utilized to calculate based on a conversion formula: virtual high score = (initial score-score normal value) = (reputation coefficient average-reputation coefficient) = (8-5) = (0.6-0.4) = 0.6, trusted score = initial score-virtual high score = 8-0.6 = 7.4, so after conversion based on reputation coefficient, the trusted score may be 7.4;

assuming that the reputation coefficient of any active participant is 0.4, the average value of the reputation coefficients of the platform is 0.6, and under the condition that the initial score submitted by any active participant is 4, the reputation coefficient of the user of 0.4 is utilized to base on a conversion formula: virtual low score = (score normal value-first score) = (user reputation coefficient average-user reputation coefficient) = (5-4) = (0.6-0.4) = 0.2, trusted score = first score + virtual low score = 4+0.2 = 4.2, and therefore, after conversion based on user reputation coefficient, the trusted score is 4.2.

In addition, after the trusted score is calculated, the trusted score and/or the statement facts may also be posted to a social circle to serve as a reminder to the public. For example, the method may further comprise: and in response to a scoring posting operation of any activity participant on a personal social circle, posting the credible scoring and/or statement facts of the other activity participants by the activity participant on the personal social circle, and synchronizing the credible scoring and/or statement facts to the personal social circles of the other activity participants.

For example, the user may perform a score posting operation on a personal social circle, and the server posts the user's trusted score and/or statement facts for the active party on the user's personal social circle, and synchronizes the trusted score and/or statement facts to the active party social circle of the active party.

The personal social circle refers to a social space under a personal account of any one of the active participants.

In the case that any of the active participants is a user, the personal social circle thereof may be a friend circle of the user, a microblog of the user, or the like. For another example, in the case that any of the active participants is an active party, the personal social circle thereof may be an active discussion area of the active party itself, an active social circle, etc., specifically, a commercial evaluation area of a commercial store, etc.

For example, the user performs a score issuing operation on the friend circle of the user, issues the credible score and/or statement facts of the user on the friend circle of the user, and the service end can synchronize the credible score and/or statement facts to the commodity comment area of the user such as a merchant.

In addition, in order to facilitate the public to know the scoring dynamic in time, the method may further include: and synchronizing the credible scores and/or statement facts issued by any of the active participants in the personal social circle to a preset public social circle. The preset public social circle can be understood as a social area where public-oriented online social platforms disclose posting information for all users.

In order to facilitate the platform server to maintain the reputation of each party of the evaluation, in combination with the embodiment in which the statement facts and the scores are submitted correspondingly, in another or more embodiments of the present specification, the method further comprises: and establishing the corresponding relation among the activity feature codes, the statement facts and the credible scores. The specific manner of establishing the correspondence is not limited, as long as the fact of statement is determined by the active feature code. For example, the correspondence table may be established in various manners by a hash function. Specifically, for example, a statement file to which a hash value of an active feature code calculated by a hash function points may be used to store a corresponding statement fact. By establishing the correspondence, the corresponding statement facts and the confidence scores can be found by the active feature codes.

For example, in the case that the statement facts fail, the credibility scores corresponding to the statement facts fail correspondingly, any one of the active participants submitting scores and other active participants being scored are determined according to the activity feature codes corresponding to the statement facts in the corresponding relation, the reputation coefficients of the other active participants are updated, and the reputation coefficients of the any one of the active participants are reduced.

Under the condition that the statement facts are invalid, the credit of the scored party is restored to a certain extent, and the credit of the scoring party is reduced, so that the fact that the scoring party randomly publishes non-genuine phases can be avoided, the active participants are prevented from randomly deleting, the statement facts are destroyed, and credit damage is brought to the scored party. In the case where the scoring party resubmits the score and the facts of the statement, the original facts of the statement may be retained or deleted, and in order to improve the accuracy of the evaluation information, all derivative evaluations related to the original facts of the statement may be cancelled, and the submitting party of the related derivative evaluation is notified.

In addition, in another or more embodiments of the present disclosure, the method may also utilize the correspondence described above to track and communicate the facts of the statement and the modifications of the score. Specifically, for example, the method may further include: in response to receiving a modification operation of any one of the active participants to the statement facts and/or scores, the corresponding relation is updated accordingly according to the modification operation; under the condition that the modifying operation is to modify the scores, correspondingly updating the credit coefficients of the other active participants according to the updated credibility scores, and correspondingly updating the credibility scores released to the social circles; in the event that the modification operation is a modification to a statement fact, the statement fact posted to the social circle is updated accordingly in accordance with the updated statement fact.

Because the server side of the method obtains the real identity information of the user and generates the anonymous identity information of the user based on the real identity information, under the condition that the user participates in the activity, the anonymous identity information of the user and the activity codes of the activity are synthesized to generate the activity feature codes, the activity feature codes are endowed to the activity participants, the activity participants comprise the user and/or the activity participants of the activity, the initial scores are submitted to other activity participants by responding to any activity participant by using the activity feature codes, the reputation coefficient of any activity participant is obtained, the credibility coefficient of any activity participant is used for calculating the initial scores, and the credibility score of any activity participant is calculated, so that the activity participant needs to submit scores by using the activity feature codes, the party who proposes the scores is the real activity participant of the activity, the authenticity of the scores is ensured, privacy is not exposed, the credibility is ensured, and the privacy requirements are met.

The evaluation method provided in the present specification will be further described below with reference to fig. 2 by taking an application of the evaluation method to mutual evaluation of a user and an active party as an example. Specifically, for example, fig. 2 shows a flowchart of a processing procedure of an evaluation method provided in an embodiment of the present specification, and specifically includes the following steps.

Step 202: acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information.

Step 204: and under the condition that the user participates in the activity, synthesizing the user anonymous identity information of the user and the activity code of the activity according to a preset user activity code generation rule to generate a user activity feature code, and giving the user activity feature code to the user.

Step 206: synthesizing the user anonymous identity information of the user and the activity codes of the activities according to a preset activity code generation rule of the activity party, generating activity feature codes of the activity party, and endowing the activity feature codes of the activity party to the activity party.

The user activity feature code is different from the activity feature code of the active party. For example, to distinguish a user activity feature code from an active party activity feature code, the user activity feature code may include a generic symbol that represents a user (e.g., only identified as a user, not a specific user identity), and the active party feature code may include a generic symbol that represents an active party (e.g., only identified as an active party, not a specific active party identity). For example, the anonymous identity information of the user and the activity code of the activity may be directly spliced, and a common symbol representing the active party is added to obtain the feature code of the active party. For another example, the anonymous identity information of the user and the activity code of the activity may be mixed according to a preset rule, and a common symbol representing the active party may be added to obtain the feature code of the active party.

Step 208: and responding to the user submitting a first score for the active party by using the user activity feature code, and acquiring the reputation coefficient of the user.

For example, a first score submitted by the user for the first facts may be received and reputation coefficients of the user may be obtained in response to the user submitting a first statement fact for the active party using the user activity feature code.

Step 210: and calculating the first score by using the reputation coefficient of the user, and calculating the credibility score of the user on the active party.

The specific algorithm for calculating the first score by using the reputation coefficient is not limited, and the reliability of the score can be increased only after the reputation coefficient based on the user is converted. Details of the calculation of the initial score may be found in the description of the calculation of the initial score, and will not be described in detail herein.

Step 212: and responding to the action party to submit a second score for the user by using the action party feature code, and acquiring the reputation coefficient of the action party.

For example, a second score submitted by the active party for a second statement fact may be received and reputation coefficients of the active party may be obtained in response to the active party submitting the second statement fact for the user using the active party feature code.

In connection with the previous example, for example, a user purchased a good on an online platform and submitted a first score for the good and a piece of fact explanatory text for the quality of the good at a review area of the good on the online platform. The actionable party may reply to the actionable party's second score for the user and the second statement fact below the statement fact submitted by the user so that the public knows the truth from the respective scores of the parties and the statement fact.

Step 214: and calculating the second score by using the credit coefficient of the active party, and calculating the credibility score of the active party to the user.

The specific algorithm for calculating the second score by using the reputation coefficient is not limited, and the reliability of the score can be increased only after the reputation coefficient of the active party is converted. Details of the calculation of the initial score may be found in the description of the calculation of the initial score, and will not be described in detail herein.

In the embodiment, the user submits the first score by using the user activity feature code and submits the second score by using the activity feature code based on the activity party, so that the user and the activity party can ensure that the user and the activity party can mutually propose the score to be the real participants participating in the activity, the authenticity of the score can be ensured, the privacy can not be exposed, the score is calculated by the credit coefficient, the reliability of the score is ensured, and the requirements of protecting privacy, authenticity and reliability in multiple aspects are met.

The evaluation method provided in the present specification will be further described below by taking an application of the evaluation method to multiparty evaluation as an example. In this embodiment, the method may further obtain a user reputation coefficient for the other user in response to the other user browsing the activity submitting a third score to the user and/or the active party; and calculating the third score by using the user credit coefficient of the other user, and calculating the credibility score of the other user to the user and/or the active party. And determining the user reputation coefficients of the other users according to the historical evaluation data of the other users.

And the trust scores of any activity participant and other users can be comprehensively calculated, and finally the comprehensive trust scores of the scored other activity participants in the activity are determined. For example, in the case where the other users participating in the scoring are multiple people, the aggregate average confidence score may be taken as the confidence score for the other users as a whole based on the number of scores, the submitted score, and the reputation coefficient. And adding the credibility score of any activity participant and the overall credibility score of other users according to a certain duty ratio to obtain the comprehensive credibility score of the scored other activity participants in the activity. For example, any of the active participants may be primary scoring parties with a score of 80% and the other users may be secondary scoring parties with a score of 20%. Assuming that the principal scoring party has a reduced determined confidence score of 8, overall confidence score for the other users was 9, then overall confidence score = 8 x 80% +9 x 20% = 8 2.

Specifically, for example, fig. 3 shows a flowchart of a processing procedure of an evaluation method provided in an embodiment of the present specification, and specifically includes the following steps.

Step 302: acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information.

Step 304: and responding to the user participation activity, synthesizing the user anonymous identity information of the user and the activity code of the activity, generating a user activity feature code, and endowing the user with the user activity feature code.

Step 306: and responding to the participation of the user in the activity, synthesizing the anonymous identity information of the user and the activity code of the activity, generating an activity party feature code, and endowing the activity party feature code to an activity party of the activity.

Step 308: and responding to the user to submit a first score for the active party by using the user activity feature code, and acquiring a reputation coefficient of the user, wherein the reputation coefficient is determined according to the historical evaluation data of the user.

Step 310: and calculating the first score by using the reputation coefficient of the user, and calculating the credibility score of the user on the active party.

Step 312: and responding to the action party to submit a second score for the user by using the action party feature code, and acquiring the reputation coefficient of the action party, wherein the reputation coefficient of the action party is determined according to the historical evaluation data of the action party.

Step 314: and calculating the second score by using the credit coefficient of the active party, and calculating the credibility score of the active party to the user.

Step 316: and responding to the third scores submitted by other users browsing the activities to the users and/or the active parties, and acquiring the reputation coefficients of the other users.

Wherein the other users can be understood as other users on the online platform than the users participating in the activity. The other users may also be registered users of the online platform. The identity used by other users to submit the third score is not limited, either a true or anonymous identity may be used. The reputation coefficients of other users may be understood by referring to the description of the reputation coefficients in the previous embodiments, and will not be described herein.

Step 318: and calculating the third score by using the reputation coefficient of the other user, and calculating the credibility score of the other user on the user and/or the active party.

The specific algorithm for calculating the third score by using the reputation coefficient is not limited, and the reliability of the score can be increased only after the score is converted based on the reputation coefficient. For specific calculation, reference may be made to the conversion modes mentioned in the foregoing embodiments, and detailed descriptions thereof are omitted herein.

It will be appreciated that according to the above embodiments, the parties to an activity, the parties to the activity, and the parties to other users who browse the activity may all score each other. To better maintain reputation of parties, in one or more embodiments of the present specification, the method may further comprise:

recording the credibility score of the user on the active party to historical evaluation data of the active party, and updating an active party reputation coefficient of the active party based on the credibility score of the user on the active party;

recording the credibility score of the active party to the user to historical evaluation data of the user, and updating the user credit coefficient of the user based on the credibility score of the active party to the user;

recording the credibility scores of the other users for the users to the historical evaluation data of the users, and correspondingly updating the user credit coefficients of the users based on the credibility scores of the other users for the users;

And recording the credibility scores of the other users on the active party to the historical evaluation data of the active party, and correspondingly updating the active party reputation coefficient of the active party based on the credibility scores of the other users on the active party.

The evaluation method provided in the present specification will be further described below by taking an application of adding a decision of an evaluation criterion to the evaluation method as an example. In one embodiment, the method may further comprise: receiving judgment information submitted by an evaluation judgment party aiming at the scoring behavior of any activity participant; and updating the reputation coefficient of any active participant based on the decision information.

Wherein, the scoring action can be understood as action of submitting a score by any of the active participants. The decision made by the evaluation judgment party can be based on the statement facts submitted by the respective active participants and the score synthesis. The decision information may be made by referees of the evaluation judgment and uploaded to the platform. The decision information may include decision text, revised score, etc. The evaluation criterion may in particular be embodied as an official institution or a folk institution with a certain public confidence.

The action of the evaluation and judgment party for judging can be started by the application of the evaluation or the evaluated party, can be started by the report of the masses, or can be automatically started by the evaluation and judgment party according to the preset starting rule, and the method provided by the embodiment of the specification is not limited.

For example: the server may respond to receiving the evaluation authentication request submitted by the other activity participants for the scoring behavior of any activity participant, and correspondingly send the evaluation request for the scoring behavior of any activity participant to the evaluation participant, so that the evaluation participant makes a decision for the scoring behavior of any activity participant.

For example, a user purchased an A commodity online, and after using the A commodity, the A commodity was considered to be of poor quality, a description of the fact of poor quality was submitted in the review area of the A commodity of the platform and a lower score was given, for example 2 points. After the commercial tenant B selling the commodity A sees the comment and scores, the user is considered to have malicious evaluation, and then a comment authentication request can be submitted to the platform. The platform server responds to the received judgment authentication request, the comments and the scores 2 of the user on the commodity A are sent to an evaluation and judgment party, and the evaluation and judgment party can judge according to the facts after fully investigating the facts and upload judgment information to the platform server. For example, if the evaluation and judgment party recognizes that there is a malicious evaluation of the user that is not in agreement with the fact, the recognition may be interpreted in the judgment information, and the evaluation and judgment party may be given a relatively fair score, for example, 5 points, for the commodity a. After receiving the judgment information, the server can determine that the user has a credit violation action, so that the credit coefficient of the user is reduced, and the judgment information given by the evaluation judgment party is published in the comment area of the commodity so as to provide the public with reference.

Specifically, for example, fig. 4 shows a flowchart of a processing procedure of an evaluation method provided in an embodiment of the present specification, and specifically includes the following steps.

Step 402: acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information.

Step 404: and responding to the user participation activity, synthesizing the user anonymous identity information of the user and the activity code of the activity, generating a user activity feature code, and endowing the user with the user activity feature code.

Step 406: and generating an activity party feature code by responding to the synthesis of the user anonymous identity information of the user and the activity code of the activity, and giving the activity party feature code to the activity party.

Step 408: and responding to the user submitting a first score for the active party by using the user activity feature code, and acquiring the reputation coefficient of the user.

Step 410: and calculating the first score by using the reputation coefficient of the user, and calculating the credibility score of the user on the active party.

Step 412: and responding to the action party to submit a second score for the user by using the action party feature code, and acquiring the reputation coefficient of the action party.

Step 414: and calculating the second score by using the credit coefficient of the active party, and calculating the credibility score of the active party to the user.

Step 416: and receiving first judgment information submitted by the evaluation judgment party aiming at the first score, and/or receiving second judgment information submitted by the evaluation judgment party aiming at the second score.

Step 418: the reputation coefficient of the user is updated based on the first decision information, and/or the reputation coefficient of the active party is updated based on the second decision information.

Wherein the content of the first decision information and the second decision information may be the same or different. For example, the first decision information and the second decision information may both include decision information for both parties, or may include decision information for each decision recipient, which is not limited in this specification.

The application of the assessment method in combination with the above embodiments in consumer activities is further described below with reference to fig. 5. Specifically, for example, fig. 5 shows a schematic flow chart of an evaluation method provided in an embodiment of the present disclosure. As shown in fig. 5, after a consumer, service (or product), other users have registered identities after having registered with the platform, and after having registered identities, scoring actions can be performed. The server side can be provided with a password platform and an evaluation platform, and the password platform and the evaluation platform are used for realizing the evaluation method provided by the embodiment of the specification. The scoring process and related processing shown in fig. 5 are schematically illustrated below:

The password platform encrypts the real identity information of the consumer by utilizing the password set by the consumer, and generates the anonymous identity information of the user. The password platform encrypts the real characteristic data of the service such as the product by utilizing the password set by the service party, and generates an activity code. And the password platform synthesizes the anonymous identity information of the user and the activity code to respectively generate a user activity feature code and an activity party activity feature code. Wherein, for the user activity feature code and the activity party activity feature code, the following characteristics are provided for both:

the method is obtained by synthesizing anonymous identity information and activity codes of the users;

reversible, traceable, and the true identities of the two parties can be obtained after the traceability;

authorized by both parties;

both the consumer and the service party are unaware of the other party's activity feature code.

Based on the evaluation platform, the consumer may score and state facts using the user activity feature code, and the server may score and state facts using the activity feature code. For scoring and/or statement facts of both parties, the facts can be disclosed on the evaluation platform and are seen by the scoring double-shot and the public. The credit scores submitted by the consumer and the service side are converted by the credit coefficients to obtain the credible scores, and the scores can be counted to participate in the updating calculation of the credit coefficients of the opposite side, so that the credit coefficients of the opposite side are influenced.

Both the consumer and the server can comment whether the credible score participating in the updating calculation of the reputation coefficient of the user is approved or not when the evaluation platform records the score. For example, if approved, the reputation coefficient is directly participated in the calculation, and if not approved, positive authentication may be performed by submitting a judge authentication request.

In addition, the evaluation platform can also set an average value of the credibility scores and a warning line. Wherein the average value and the warning line can be updated as required. Based on the average value of the credible scores and the warning line, the rationality of the credible scores can be timely detected and authenticated.

For other users, the evaluation platform may browse the service records of the service party, browse facts stated by the consumer and/or the service party, and give a score based on the stated facts. Of course, scores submitted by other users are also converted by the reputation coefficients to obtain credible scores. The evaluation platform participates the credibility scores of the other users in the updating calculation of the credit coefficients of the scored parties such as consumers and service parties.

For an evaluation reviewer, a review authentication request may be received from the review platform and a score for decision text and corrections given based on facts stated by the consumer and/or the server. It can be understood that, according to the application scene requirement, the reputation coefficient can be set for the evaluation and judgment party, or the reputation coefficient can be set by default as the credibility of the evaluation and judgment party. The evaluation of the critique corrected score may be involved in the updated calculation of reputation coefficients for the consumer and/or server associated with the request for authentication.

Through the scoring flow and the related processing process, privacy people with privacy protection requirements can be provided through the password platform, and the sealing effect shown in fig. 6 can be achieved through the processing of the password platform, so that the privacy people on the evaluation platform can not be identified. The cryptographic platform is understood to be a platform on which a cryptographic engine or a sealed library is provided. The encryption machine or the sealed library can be understood as a functional module which is provided with an encryption and decryption algorithm and can encrypt and decrypt information. For example, by evaluating the platform, an ambient person a using an activity feature code and an ambient person B using an activity feature code, the respective activity feature code may be used to submit scores and statement facts to their opposing parties involved in the activity. In addition, the trust scores and statement facts obtained after the reputation factor conversion may be posted to respective personal social circles (e.g., also known as self-territories) and synchronized to personal social circles evaluating to each other (e.g., also known as counterparties) and to public social circles (e.g., also known as public territories).

Corresponding to the method embodiment, the present disclosure further provides an evaluation device embodiment, and fig. 7 shows a schematic structural diagram of an evaluation device provided in one embodiment of the present disclosure. As shown in fig. 7, the apparatus includes:

The information protection component 702 may be configured to obtain the true identity information of the user and generate anonymous identity information of the user based on the true identity information.

The feature code generation component 704 may be configured to synthesize user anonymous identity information of the user and an activity code of the activity in case the user participates in the activity, generate an activity feature code, and assign the activity feature code to an activity participant, the activity participant comprising the user and/or an activity party of the activity.

The ratings response component 706 may be configured to obtain reputation coefficients of any of the active participants in response to the any of the active participants submitting an initial score for the other active participants using the activity feature code.

Score computation component 708 may be configured to compute the initial score using reputation coefficients of the any of the active participants, computing a trusted score of the any of the active participants for the other active participants.

The device acquires the real identity information of the user, generates the anonymous identity information of the user based on the real identity information, synthesizes the anonymous identity information of the user and the activity codes of the activity under the condition that the user participates in the activity, generates an activity feature code, and endows the activity feature code to an activity participant, wherein the activity participant comprises the user and/or the activity participant, and responds to the fact that any activity participant uses the activity feature code to submit initial scores for other activity participants, acquires the reputation coefficient of any activity participant, calculates the initial scores by using the reputation coefficient of any activity participant, calculates the credible scores of any activity participant for the other activity participants, so that the activity participant needs to submit scores by using the activity feature code, the fact that one party who proposes the scores is the real activity participant of the activity is ensured, the scores are not exposed, the scores are calculated by the reputation coefficient, and the credible privacy requirements of the user are met, and the credibility requirements of the privacy and the credibility are met.

In one or more embodiments, the feature code generating component 704 may be configured to, in a case where the user participates in an activity, synthesize user anonymous identity information of the user and an activity code of the activity according to a preset user activity code generation rule, generate a user activity feature code, and assign the user activity feature code to the user; and

Accordingly, the evaluation correspondence component 706 may be configured to obtain reputation coefficients of the user in response to the user submitting a first score for the active party using the user activity feature code; the method comprises the steps of,

and responding to the action party to submit a second score for the user by using the action party feature code, and acquiring the reputation coefficient of the action party.

Accordingly, the score computation component 708 may be configured to compute the first score using the user's reputation coefficient, computing a trustworthy score of the user for the active party; the method comprises the steps of,

And calculating the second score by using the credit coefficient of the active party, and calculating the credibility score of the active party to the user.

In one or more embodiments of the present disclosure, the information protection component 702 may be further configured to obtain real feature data of the activity, and encrypt the real feature data to generate the activity code using encryption information set by the active party. Accordingly, the method may be configured to encrypt the true identity information using the encryption information set by the user to generate the user anonymous identity information.

In one or more embodiments of the present disclosure, the evaluation response component 706 can be further configured to obtain reputation coefficients of other users browsing the activity in response to the other users submitting third scores to the user and/or the active party. Accordingly, the score computation component 708 may be further configured to compute the third score using the reputation coefficients of the other users, and to compute the trusted scores of the other users for the users and/or the active parties.

In one or more embodiments of the present disclosure, the apparatus may further include: a score recording component may be configured to record a confidence score of the user for the active party to historical ratings data of the active party and update a reputation coefficient of the active party based on the confidence score of the user for the active party; and recording a confidence score of the active party for the user to historical evaluation data of the user, and updating a reputation coefficient of the user based on the confidence score of the active party for the user; recording the credibility scores of the other users to the user to the historical evaluation data of the user, and correspondingly updating the reputation coefficient of the user based on the credibility scores of the other users to the user; and recording the credibility scores of the other users on the active party to the historical evaluation data of the active party, and correspondingly updating the reputation coefficient of the active party based on the credibility scores of the other users on the active party.

In one or more embodiments of the present specification, the evaluation response component 706 may be configured to receive an initial score of the statement fact submission by the any active participant and obtain a reputation coefficient of the any active participant in response to the any active participant submitting the statement fact for other active participants using the activity feature code.

In one or more embodiments of the present specification, the apparatus further comprises: the evaluation judgment component is configured to receive judgment information submitted by an evaluation judgment party for the scoring action of any one of the active participants; a reputation coefficient updating component configured to update reputation coefficients of the any active participant based on the decision information.

In one or more embodiments of the present disclosure, the apparatus may further include: and the authentication request component is configured to respond to receiving a judgment authentication request submitted by the other activity participants for the scoring behavior of any activity participant, and correspondingly send a judgment request for the scoring behavior of any activity participant to the evaluation participant, so that the evaluation participant makes a judgment for the scoring behavior of any activity participant.

In one or more embodiments of the present disclosure, the apparatus may further include: the traceability component can be configured to acquire the activity feature code of any activity participant submitting the initial score, analyze the activity feature code to trace back to obtain the user anonymous identity information of the user and the activity code, analyze the user anonymous identity information to trace back to obtain the real identity information of the user, analyze the activity code to trace back to obtain the real feature data of the activity, determine the user based on the real identity information, and determine the activity party based on the real feature data.

In one or more embodiments of the present disclosure, the apparatus may further include: an authorization confirmation component configured to determine whether authorization of the user with the active party is obtained, and if so, to allow generation of the active feature code.

In one or more embodiments of the present disclosure, the apparatus may further include: a scoring posting component configured to post the trusted scoring and/or statement facts of the other activity participants at the personal social circle by the any activity participant in response to a scoring posting operation of the any activity participant at the personal social circle, and synchronize the trusted scoring and/or statement facts to the personal social circles of the other activity participants.

In one or more embodiments of the present specification, the scoring distribution component is further configured to synchronize the trusted scoring and/or statement facts posted by the any active participant at the personal social circle to a preset public social circle.

In one or more embodiments of the present disclosure, the apparatus further includes: and the corresponding relation establishing component is configured to establish the corresponding relation among the activity feature codes, the statement facts and the credibility scores.

In one or more embodiments of the present disclosure, the apparatus further includes: and the statement invalidation processing component is configured to determine any one of the active participants submitting scores and other active participants to be scored according to the activity feature codes corresponding to the statement facts in the corresponding relation, update the reputation coefficients of the other active participants and reduce the reputation coefficients of the any one of the active participants under the condition that the statement facts are invalidated.

In one or more embodiments of the present disclosure, the apparatus further includes: and a modification tracking component configured to respond to the received modification operation of any activity participant on the statement facts and/or scores, correspondingly update the corresponding relation according to the modification operation, correspondingly update the reputation coefficients of other activity participants according to the updated credibility scores when the modification operation is the score modification, and correspondingly update the credibility scores posted to the social circle, and correspondingly update the statement facts posted to the social circle according to the updated statement facts when the modification operation is the statement facts modification.

The above is a schematic configuration of an evaluation apparatus of the present embodiment. It should be noted that, the technical solution of the evaluation device and the technical solution of the above-mentioned evaluation method belong to the same concept, and details of the technical solution of the evaluation device, which are not described in detail, can be referred to the description of the technical solution of the above-mentioned evaluation method.

Corresponding to the method embodiment, the present disclosure further provides an evaluation system embodiment, and fig. 8 shows a schematic structural diagram of an evaluation system provided in one embodiment of the present disclosure. As shown in fig. 8, the system includes:

the server 802 may be configured to obtain real identity information of a user, generate user anonymous identity information based on the real identity information, synthesize the user anonymous identity information of the user and an activity code of the activity in the event that the user participates in the activity, generate an activity feature code, and assign the activity feature code to an activity participant, where the activity participant includes the user and/or the activity participant, and in response to any one of the activity participants submitting an initial score for other activity participants using the activity feature code, obtain a reputation coefficient of any one of the activity participants, calculate the initial score using the reputation coefficient of any one of the activity participants, and calculate a trusted score of any one of the activity participants for the other activity participants.

The first client 804 may be configured to submit an initial score for the other active participants using the activity feature code by the any active participant.

Optionally, fig. 9 shows a schematic structural diagram of an evaluation system according to another embodiment of the present disclosure. As shown in fig. 9, in this embodiment:

the server 802 may be configured to synthesize user anonymous identity information of the user and an activity code of the activity according to a preset user activity code generation rule under the condition that the user participates in the activity, generate a user activity feature code, assign the user activity feature code to the user, synthesize user anonymous identity information of the user and an activity code of the activity according to a preset activity party activity code generation rule, generate an activity party activity feature code, assign the activity party activity feature code to the activity party, submit a first score for the activity party by using the user activity feature code to the user, obtain a reputation coefficient of the user, submit a second score for the user by using the activity party feature code to the user to obtain a reputation coefficient of the activity party by using the activity party, calculate the first score by using the reputation coefficient of the user, calculate the credible score of the activity party by using the reputation coefficient of the activity party to calculate the credible score of the activity party.

Accordingly, the first client may include:

a first user client 8042 configured to submit a first score for an active party using a user activity feature code.

The actor client 8044 is configured to submit a second score to the user using the actor activity feature code.

In another or more embodiments, the server 802 may be further configured to, in response to submitting a third score to the user and/or the active party by another user browsing the activity, obtain a user reputation coefficient of the other user, calculate the third score using the user reputation coefficient of the other user, and calculate a trust score of the other user to the user and/or the active party.

Accordingly, as shown in fig. 9, the system may further include: the second user client 806 may be configured to browse the activity, submit a third score for the activity.

Fig. 10 illustrates a block diagram of a computing device 1000 provided in accordance with one embodiment of the present description. The components of the computing device 1000 include, but are not limited to, a memory 1010 and a processor 1020. Processor 1020 is coupled to memory 1010 via bus 1030 and database 1050 is used to store data.

Computing device 1000 also includes access device 1040, which access device 1040 enables computing device 1000 to communicate via one or more networks 1060. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 1040 may include one or more of any type of network interface, wired or wireless (e.g., a Network Interface Card (NIC)), such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.

In one embodiment of the present description, the above-described components of computing device 1000, as well as other components not shown in FIG. 10, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device illustrated in FIG. 10 is for exemplary purposes only and is not intended to limit the scope of the present description. Those skilled in the art may add or replace other components as desired.

Computing device 1000 may be any type of stationary or mobile computing device including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smart phone), wearable computing device (e.g., smart watch, smart glasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 1000 may also be a mobile or stationary server.

Wherein the processor 1020 is configured to execute computer-executable instructions that, when executed by the processor, perform the steps of the evaluation method described above. For example, it includes:

acquiring real identity information of a user, and generating anonymous identity information of the user based on the real identity information;

synthesizing user anonymous identity information of the user and activity codes of the activities under the condition that the user participates in the activities, generating activity feature codes, and endowing the activity feature codes to activity participators, wherein the activity participators comprise the user and/or the activity party of the activities;

responding to the initial scores submitted by any one of the activity participants for other activity participants by using the activity feature codes, and obtaining the reputation coefficient of any one of the activity participants;

and calculating the initial scores by using the credit coefficients of any activity participants, and calculating the credibility scores of any activity participant on the other activity participants.

The foregoing is a schematic illustration of a computing device of this embodiment. It should be noted that, the technical solution of the computing device and the technical solution of the above-mentioned evaluation method belong to the same concept, and the details of the technical solution of the computing device, which are not described in detail, can be referred to the description of the technical solution of the above-mentioned evaluation method. For example, it includes:

An embodiment of the present specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described evaluation method. For example, it includes:

The above is an exemplary version of a computer-readable storage medium of the present embodiment. It should be noted that, the technical solution of the storage medium and the technical solution of the above-mentioned evaluation method belong to the same concept, and details of the technical solution of the storage medium which are not described in detail can be referred to the description of the technical solution of the above-mentioned evaluation method.

An embodiment of the present specification also provides a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-described evaluation method. For example, it includes:

The above is an exemplary version of a computer program of the present embodiment. It should be noted that, the technical solution of the computer program and the technical solution of the above-mentioned evaluation method belong to the same concept, and details of the technical solution of the computer program, which are not described in detail, can be referred to the description of the technical solution of the above-mentioned evaluation method.

The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The computer instructions include computer program code that may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the embodiments are not limited by the order of actions described, as some steps may be performed in other order or simultaneously according to the embodiments of the present disclosure. Further, those skilled in the art will appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily all required for the embodiments described in the specification.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to the related descriptions of other embodiments.

The preferred embodiments of the present specification disclosed above are merely used to help clarify the present specification. Alternative embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the teaching of the embodiments. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. This specification is to be limited only by the claims and the full scope and equivalents thereof.

Claims

1. An evaluation method, comprising:

Responding to the initial scores submitted by any one of the activity participants for other activity participants by using the activity feature codes, and obtaining the reputation coefficient of any one of the activity participants; and calculating the initial scores by using the credit coefficients of any activity participants, and calculating the credibility scores of any activity participant on the other activity participants.

2. The method as recited in claim 1, further comprising:

acquiring real characteristic data of the activity, and encrypting the real characteristic data by utilizing encryption information set by the activity party to generate the activity code;

the generating user anonymous identity information based on the true identity information comprises the following steps:

and encrypting the true identity information by using the encryption information set by the user to generate the anonymous identity information of the user.

3. The method as recited in claim 1, further comprising:

responding to the submission of a third score to the user and/or the active party by other users browsing the activity, and obtaining the reputation coefficient of the other users;

and calculating the third score by using the reputation coefficient of the other user, and calculating the credibility score of the other user on the user and/or the active party.

4. A method according to claim 3, further comprising:

recording the credibility score of the user on the active party to historical evaluation data of the active party, and updating the reputation coefficient of the active party based on the credibility score of the user on the active party;

recording the credibility score of the active party to the user to historical evaluation data of the user, and updating the credit coefficient of the user based on the credibility score of the active party to the user;

recording the credibility scores of the other users for the users to the historical evaluation data of the users, and correspondingly updating the reputation coefficient of the users based on the credibility scores of the other users for the users;

and recording the credibility scores of the other users on the active party to the historical evaluation data of the active party, and correspondingly updating the reputation coefficient of the active party based on the credibility scores of the other users on the active party.

5. The method as recited in claim 1, further comprising:

receiving judgment information submitted by an evaluation judgment party aiming at the scoring behavior of any activity participant;

and updating the reputation coefficient of any active participant based on the decision information.

6. The method as recited in claim 5, further comprising:

and responding to receiving a judgment authentication request submitted by the other activity participants for the scoring behavior of any activity participant, and correspondingly sending a judgment request for the scoring behavior of any activity participant to the evaluation participant, so that the evaluation participant makes a judgment for the scoring behavior of any activity participant.

7. The method as recited in claim 2, further comprising:

acquiring an activity feature code of any one of the activity participants submitting the initial score;

analyzing the activity feature code to trace back to obtain user anonymous identity information of the user and the activity code;

analyzing the anonymous identity information of the user to trace back to obtain the real identity information of the user;

analyzing the activity codes to trace back to obtain real characteristic data of the activity;

determining the user based on the true identity information;

the active party is determined based on the real characteristic data.

8. The method as recited in claim 1, further comprising:

in response to a scoring posting operation of the any one of the activity participants on a personal social circle, posting trusted scoring and/or statement facts of the other activity participants by the any one of the activity participants on the personal social circle, and synchronizing the trusted scoring and/or statement facts to the personal social circles of the other activity participants;

And synchronizing the credible scores and/or statement facts issued by any of the active participants in the personal social circle to a preset public social circle.

9. The method as recited in claim 1, further comprising:

and establishing a corresponding relation among the activity feature codes, the statement facts and the credible scores, wherein the statement facts are the statement facts which are correspondingly submitted by any activity participant when submitting the initial scores.

10. The method as recited in claim 9, further comprising:

in the case that the stated facts fail, the credibility scores corresponding to the stated facts fail correspondingly;

determining any one of the activity participants submitting the scores and other activity participants to be scored according to the activity feature codes corresponding to the statement facts in the corresponding relation;

and updating the reputation coefficients of the other active participants, and reducing the reputation coefficient of any active participant.

11. The method as recited in claim 9, further comprising:

in response to receiving a modification operation of any one of the active participants to the statement facts and/or scores, the corresponding relation is updated accordingly according to the modification operation;

Under the condition that the modifying operation is to modify the scores, correspondingly updating the credit coefficients of the other active participants according to the updated credibility scores, and correspondingly updating the credibility scores released to the social circles;

in the event that the modification operation is a modification to a statement fact, the statement fact posted to the social circle is updated accordingly in accordance with the updated statement fact.

12. An evaluation device, comprising:

the information protection component is configured to acquire real identity information of a user and generate anonymous identity information of the user based on the real identity information;

a feature code generation component configured to synthesize user anonymous identity information of the user and an activity code of the activity in case the user participates in the activity, generate an activity feature code, and assign the activity feature code to an activity participant, the activity participant comprising the user and/or an activity party of the activity;

an evaluation response component configured to obtain reputation coefficients of any one of the active participants in response to the active participant submitting an initial score for the other active participants using the activity feature code;

And a score calculating component configured to calculate the initial score by using the reputation coefficient of any one of the activity participants, and calculate the credibility scores of the other activity participants by the any one of the activity participants.

13. An evaluation system, comprising:

the server side is configured to acquire real identity information of a user, generate user anonymous identity information based on the real identity information, synthesize the user anonymous identity information of the user and an activity code of the activity under the condition that the user participates in the activity, generate an activity feature code, and endow the activity feature code to an activity participant, wherein the activity participant comprises the user and/or the activity participant, and respond to the fact that any activity participant submits initial scores for other activity participants by using the activity feature code, acquire reputation coefficients of any activity participant, calculate the initial scores by using the reputation coefficients of any activity participant, and calculate the credible scores of any activity participant on the other activity participants;

a first client configured for the any one of the active participants to submit initial scores for the other active participants using the activity feature code.

14. The evaluation system of claim 13, wherein the server is configured to synthesize user anonymity identity information of the user and an activity code of the activity according to a preset user activity code generation rule in the event that the user participates in the activity, generate a user activity feature code, assign the user activity feature code to the user, synthesize user anonymity identity information of the user and an activity code of the activity according to a preset activity party activity code generation rule, generate an activity party activity feature code, assign the activity party activity feature code to the activity party, submit a first score for the activity party in response to the user using the user activity feature code, obtain a reputation coefficient of the user in response to the activity party submitting a second score for the user using the activity party feature code, calculate a confidence score for the activity party using the reputation coefficient of the user, calculate a confidence score for the activity party using the reputation coefficient of the activity party;

Accordingly, the first client includes:

a first user client configured to submit a first score for an active party using a user activity feature code;

an active-party client configured to submit a second score for the user using the active-party activity feature code.

15. The rating system of claim 13, wherein the server is further configured to, in response to submitting a third score to the user and/or the active party by another user browsing the activity, obtain a user reputation coefficient of the other user, calculate the third score using the user reputation coefficient of the other user, calculate a trust score of the other user to the user and/or the active party;

accordingly, the evaluation system further comprises:

a second user client configured to browse the activity, submitting a third score for the activity.

16. A computing device, comprising:

a memory and a processor;

the memory is configured to store computer executable instructions, the processor being configured to execute the computer executable instructions, which when executed by the processor, implement the steps of the evaluation method according to any one of claims 1 to 11.

17. A computer-readable storage medium storing computer-executable instructions which, when executed by a processor, implement the steps of the assessment method of any one of claims 1 to 11.