CN111369301A - Transaction evaluation method, device and terminal - Google Patents
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Abstract
The invention discloses a method and a device for evaluating transaction and a readable storage medium, wherein the method comprises the following steps: step A: receiving current grading data sent by a grading user side; the current scoring data carries a scoring user identifier and a scored user identifier; and B: extracting first historical scoring data of scoring users and second historical scoring data of scored users and/or products; and C: calculating the current grading data and the first historical grading data to obtain first comprehensive grading data; calculating the current grading data and second historical grading data to obtain second comprehensive grading data; step D: and storing, outputting and displaying the current grading data, the first comprehensive grading data and the second comprehensive grading data. The scoring of the scoring user can be analyzed, processed, stored and recorded through the first historical scoring data of the scoring user, and the scoring of the scoring user and the scoring user can be analyzed, processed, stored and recorded, so that bidirectional data analysis and recording of the scoring user and the scoring user are achieved.
Description
Technical Field
The invention relates to the field of evaluation devices for evaluating various text data mechanically, in particular to a transaction evaluation method, a transaction evaluation device and a transaction evaluation terminal.
Background
In the network transaction, the consumer evaluates the goods and services of the seller, helps other consumers to strengthen the cognition of the merchant, and finally determines whether to purchase the goods and services. The evaluation is a summary of the consumption experience by inheriting the concept of 'i being a person and a person-to-me', and aims to promote a seller to improve service and ensure the quality of goods, and meanwhile, the evaluation is used as a third party to provide own consumption experience for subsequent consumers and help the consumers to make judicious choices.
However, the existing evaluation systems are generally 5-point scoring, so that the evaluation systems are too wide, some evaluation modes, such as conceptual choices of ' driver's character is good ', ' customer service attitude is good ' and the like are too fuzzy, scores higher than the quality of the object can be made due to the influence of subjective reasons, the data degree is insufficient, and the judgment of subsequent consumers is influenced by misguidance. The differences between stores are not obvious, and in areas where stores are many, it is difficult to determine the ranking of the stores by scoring.
Moreover, there are individual preference differences among consumers, and different scoring ranks cannot be provided for different preferences of consumers. The existing evaluation systems are generally in comprehensive ordering or sales ordering, and cannot reflect the importance ratio of 'people' and 'things' in transactions or services and the subdivision angles contained in the 'people' or the 'things'.
Moreover, the existing evaluation systems are unilateral, the consumers evaluate the merchants, the public praise of the merchants is only reflected, the consumers are not restricted, and the malicious bad comments of the consumers and the false good comments of the merchants asking for water army can not be logically avoided, so that the evaluation systems are unfair to the third-party consumers and the merchants.
Therefore, the prior art needs to be improved.
Disclosure of Invention
The invention mainly aims to provide a transaction evaluation method and a transaction evaluation device, and aims to solve and inhibit the technical problems of insufficient grading datamation, wide and inaccurate grading data, malicious poor evaluation and the like in the prior art.
To achieve the above object, the present invention provides a method for transaction evaluation, comprising:
step A: receiving current grading data sent by a grading user side; the current scoring data comprises a scoring user identifier and a scored user identifier;
and B: extracting historical scoring data; the historical scoring data comprises first historical scoring data of scoring users and second historical scoring data of scored users;
and C: processing the current grading data and the historical grading data to obtain a grading result; the scoring result comprises current scoring data, first comprehensive scoring data and second comprehensive scoring data;
step D: and outputting the grading result to the graded user side and the storage module.
Preferably, the current scoring data is composed of at least two sub current scoring data and a first total data, the sub current scoring data is a product of a first sub scoring value and a first percentage, and the first percentage is a percentage of the sub current scoring data in the current scoring data; the historical score data is composed of at least two items of sub-historical score data and second total data, the sub-historical score data is the product of a second score value and a second percentage, and the second percentage is the percentage of the sub-historical score data in the historical score data. Preferably, step a further includes step a 0: inputting at least two of the first score values and the first percentage.
Preferably, the sub current scoring data at least comprises sub current scoring data a of the human and sub current scoring data b of the object; the sub-historical score data at least comprises sub-historical score data c of the human and sub-historical score data d of the object.
Preferably, said step C further comprises the step of,
performing mean value calculation according to the first historical scoring data of the scoring user and the current scoring data to obtain first comprehensive scoring data of the scoring user;
and carrying out mean value calculation according to the second historical scoring data of the scored user and the current scoring data to obtain second comprehensive scoring data of the scored user.
Preferably, the step D includes:
storing the first comprehensive grading data and the current grading data corresponding to the grading user;
and updating, displaying and storing the second comprehensive scoring data of the scored user, and storing and displaying the current scoring data corresponding to the scored user.
Preferably, the comprehensive scoring data of the scoring users comprises sub-scoring data and sum data of the sub-scoring data; the comprehensive scoring data of the scored users comprises sub-historical scoring data and sum data of the sub-historical scoring data.
Preferably, the method further comprises the following steps: step H: receiving a sorting request of the evaluation user side, wherein the sorting request comprises sorting conditions;
and calling the historical scored data of at least two evaluated users according to the sorting request.
Preferably, before the step a, the method further includes:
step E: receiving a transaction request initiated by a grading user side; the transaction request carries user identification information; extracting account fund information of the user corresponding to the user identification information, correspondingly freezing fund, and generating a first bill; and sending the first bill to the scored user terminal.
Preferably, step E is followed by:
step F: receiving a first document and providing transaction service;
the transaction is completed by thawing the frozen funds and allocating the thawed funds to the user funds account to be scored.
Preferably, step E further comprises, before step E, step G: receiving a limiting request sent by the evaluated user side, wherein the limiting request carries limiting conditions;
and setting the limit of the evaluation user according to the limit condition.
In addition, to achieve the above object, the present invention provides a transaction evaluation device, including: memory, processor and computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, carries out the steps of the method according to any one of claims 1 to 11.
The invention can realize the following beneficial effects:
according to the transaction evaluation method provided by the embodiment of the invention, through the steps A to D, after the current scoring data is received, by extracting, processing, outputting and displaying the historical scoring data of the scoring user and the scored user, the scoring and recording of the scored user can be carried out, the scoring of the scoring user can be analyzed, processed, stored and recorded through the first historical scoring data of the scoring user, and the bidirectional data analysis and recording of the scoring user and the scored user are realized.
Through the step A0, the user sets and inputs the at least two first scoring values and the first percentage value, so that the current scoring data can be more accurate, the selection and reference of different people to different requirements can be met, and the information transmission is more definite.
Step H, the ordering request is combined with the second historical scoring data in the invention, the ordering can be selected according to the personal preference weight preference of the scoring user, the importance ratio of the 'people' and the 'things' in the transaction or service can be reflected, the segmentation angles contained in the 'people' or the 'things' are reflected, and the data transformation is more accurate.
Step G, through the limitation request of the evaluated user to the evaluating user, the extracting module extracts the first historical evaluation data of the evaluating user, and the evaluating user is evaluated according to the limitation condition; the method can eliminate and limit some malicious evaluation users and the bill-swiping evaluation users, further protect the rights and interests of the evaluated party, and can also reduce misleading to other evaluation users.
The device of the invention can realize the functions in the steps and further produce the beneficial effects.
Drawings
FIG. 1 is a schematic diagram of a terminal \ device structure of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of embodiment 1 of the transaction evaluation method of the present invention;
FIG. 3 is a schematic flow chart illustrating a detailed process of the transaction evaluation method of FIG. 2;
FIG. 4 is a schematic structural diagram of a transaction evaluation device according to embodiment 2 of the present invention;
FIG. 5 is a schematic diagram of a partial module structure according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of another part of a module according to another embodiment of the present invention;
fig. 7 is a schematic structural diagram of another part of the module according to the embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Reference numerals:
1. the system comprises an application environment, 10, a scoring client, 110, a scoring user, 11, a scored client, 110, a scored user, 12, an evaluation server, 13, a network, 3, a transaction processing module, 4, a limitation receiving module, 40, a limitation permission module, 41, a limitation condition module, 42, a limitation processing module, 5, a sorting receiving module, 50, a sorting condition module, 52, a sorting processing module, 6, a data processing module, 7, an extraction module, 8, a storage module, 30, a receiving module, 300, a first-order personal preference weight input module, 301, a first-order data input module, 9 and an output module.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Fig. 1 is a diagram of an application environment of an evaluation system in an embodiment, which includes a scoring client, a scored client, and an evaluation server, all connected to a network.
Specifically, the scoring user side includes a plurality of scoring users, the scored user side includes a plurality of scored users, the number of the scoring user side and the scored user side is not specifically limited, the scoring user side and the scoring user side may be PCs, or smart phones, tablet computers, electronic book readers, MP3(Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard Audio Layer 3) players, MP4(Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard Audio Layer 3) players, portable computers, and other mobile terminal devices having a display function. The grading user can establish communication connection with the grading server through at least one user side.
Example 1
As described with reference to fig. 2 to 3, in the present embodiment, a method for transaction evaluation is provided, and the present embodiment is illustrated by applying the method to an evaluation system in the scoring system of fig. 1.
The main solution of the embodiment of the invention is as follows:
s200, step A: receiving current scoring data sent by a scoring user; the current scoring data comprises a scoring user identifier and a scored user identifier.
Specifically, the scoring user terminal may establish a communication connection with the evaluation system through a browser, or may communicate with the scoring server through an evaluation application installed on the scoring user terminal. The scoring user side receives current scoring data input by a scoring user, when the scoring user corresponds to a certain product to be scored or the scoring user inputs scoring data, identification information of the product/user is transmitted to a scoring server together with the current scoring data through the browser or scoring application, and the input current scoring data is input through the scoring user side and carries the identification information of the scoring user. The current scoring data comprises a scoring user identifier and a scored user identifier. The scoring user comprises identification information corresponding to respective identities, and specifically can be one of a mobile phone number, a user name and the like; the scored user identification carries information of the scored user and/or information of products of the scored user and the like.
S201, step B: and extracting first historical scoring data of the scoring users and second historical scoring data of the scored users and/or products.
Specifically, the first historical scoring data is accumulated statistical data corresponding to respective scoring data of each scoring user, the second historical scoring data is accumulated statistical data corresponding to scored data of each scored user and/or product, the accumulated statistical data correspond to each scoring user and the scored user and are stored in a storage module, and the evaluation server extracts the first historical scoring information and the second historical scoring information according to the scoring user identification and the scored user identification.
And C: calculating the mean value of the current grading data and the first historical grading data to obtain first comprehensive grading data; and calculating the mean value of the current grading data and the second historical grading data to obtain second comprehensive grading data.
Step D: and storing and displaying the current grading data, the first comprehensive grading data and the second comprehensive grading data.
Specifically, the current rating data includes at least two first-order current rating data and first-order personal preference weight data corresponding to each first-order current rating data;
the first order personal preference weight data comprises a percentage of each of the first order current score data. The sum of the first-order personal preference weight data is 1, in the embodiment, the first-order current scoring data comprises quality evaluation data, price evaluation data and total data, and the first-order personal preference weight data is the percentage of the score proportion of the two scoring items in the scoring user center relative to the people and the objects. The client may enter the data through the client.
The composition structure of the first historical scoring data and the second historical scoring data is the same as that of the current scoring data. The first historical scoring data comprises at least two first-order first historical scoring data corresponding to the current scoring data and first-order personal preference weight first historical data corresponding to each first-order first historical scoring data; the first-order personal preference weight first historical data is the percentage of each first-order first historical scoring data.
The second historical scoring data corresponding to the current scoring data comprises at least two first-order second historical scoring data and first-order personal preference weight second historical data corresponding to each first-order second historical scoring data, and the first-order personal preference weight second historical data is the percentage of each item of the first-order second historical scoring data.
Specifically, the first-order current scoring data includes at least two second-order current scoring data and second-order personal preference weight data corresponding to the second-order current scoring data;
the first-order first historical scoring data corresponding to the first-order current scoring data comprises at least two items of second-order first historical scoring data and second-order personal preference weight second historical data corresponding to the second-order first historical scoring data;
the first-order second historical scoring data corresponding to the first-order current scoring data comprises at least two items of second-order second historical scoring data and second-order personal preference weight second historical data corresponding to the second-order second historical scoring data.
The second-order current scoring data can be evaluation data of people, evaluation data of environment, evaluation data of professionalism and the like, wherein the second-order current scoring data and the first-order current scoring data are identical in composition structure, and the second-order first historical scoring data and the second-order second historical scoring data are identical in composition structure with the second-order current scoring data.
Further, the step C further includes:
step C comprises calculating the mean value of the first-order current scoring data and the first-order first historical scoring data to obtain a first-order first scoring data mean value; calculating the average value of the first-order personal preference weight data and the first historical data of the first-order personal preference weight to obtain the average value of the first-order first personal preference weight data;
calculating the mean value of the first-order current scoring data and the first-order second historical scoring data to obtain a first-order second scoring data mean value; and calculating the average value of the first-order personal preference weight data and the second historical data of the first-order personal preference weight to obtain the average value of the first-order second personal preference weight data.
The first-order first-grade data mean value comprises a mean value of each corresponding item of current scoring data and first-order first-historical scoring data, and a mean value of each sum of the first-order current scoring data and each sum of the first-order first-historical scoring data;
the first-order second scoring data mean value comprises a mean value of each corresponding item of current scoring data and first-order second historical scoring data, and a mean value of the sum of each item of the first-order current scoring data and the sum of each item of the first-order second historical scoring data.
Specifically, each item of first-order current rating data and the first-order personal preference weight data may be input by a rating user through the rating user terminal.
In this embodiment, the current rating data (1 digit after the decimal point) and the first-order personal preference weight data are input for 10 minutes through a cursor bar input module displayed on the rating user side, each item of first-order current rating data is multiplied by the corresponding first-order personal preference weight data to calculate a current cost performance value 2 digits (currently set and adjustable) after the decimal point, and finally, each item of first-order current rating data is added to collect rating values of all transactions to calculate the current 'comprehensive cost performance' of the merchant, so that the merchant is accurately ranked by the value.
Specifically, the first composite score data includes: a first order first score data mean, and a first order first person preference weight data mean; the second composite score data comprises: a first order second score data mean, and a first order second person preference weight data mean; the step D also comprises the following steps:
storing the current grading data and the first comprehensive grading data corresponding to the grading user; displaying the first comprehensive grading data corresponding to the grading user;
and storing and displaying the current grading data and the second comprehensive grading data corresponding to the graded user.
The first comprehensive grading data is displayed on a homepage of the grading user side, so that the grading user can better understand the transaction requirements of the grading user, can more clearly understand the preference and the requirements of the grading user, and can more accurately understand the selection direction of the grading user when the transaction is selected, and better transaction experience can be realized. The first composite score data may be invisible or visible to other users, and the present invention is not particularly limited.
The evaluation server sends the first comprehensive grading data of the grading user and the current grading data to a storage module to be stored corresponding to the grading user. And the evaluation server displays the current grading data corresponding to the graded user or product. The memory can be a conventional memory card, or a mobile phone memory, a computer memory and the like.
Specifically, still include: step H: receiving a sorting request of the evaluation user side, wherein the sorting request comprises a sorting condition and a first extraction instruction;
extracting sequencing information corresponding to the first extracting instruction;
ranking the evaluated users according to the ranking conditions and the ranking information; obtaining a sequencing result;
and displaying the sequencing result corresponding to the evaluation user side.
The evaluation user can input a sorting request through a sorting request module displayed by the evaluation user side, and the sorting request module can be used for ranking the first-order first historical scoring data of different scored users in a high-low mode or ranking the first-order first historical scoring data of different scored users in a high-low mode.
And displaying the sorting result corresponding to the scoring user requesting sorting.
Specifically, an evaluated user inputs a sorting request through an evaluation user side, the sorting request includes a sorting condition and a first extraction instruction, the sorting condition is a screening/comparison condition for the evaluated user, specifically, the sorting condition may be a high-low ranking of a certain first-order first historical score data of different scored users of the scored user, the sorting server correspondingly extracts a certain first-order second historical score data of the scored user according to the first extraction instruction, sorts the data, displays a sorting result corresponding to a display screen or other display device of an evaluation client side requesting sorting, and the evaluation user obtains sorting result information.
Further, after step H of S196 and before step a of S200, step E of S197 is further included: step E:
receiving a transaction request initiated by an evaluation user side; the transaction request includes transaction information;
and processing the transaction request, and performing fund transfer and product transfer processing corresponding to the transaction information.
Specifically, the transaction information includes scoring user identification information, scored user identification information and transaction product information;
extracting account fund information corresponding to the grading user identification information, and freezing fund corresponding to the product information; generating a first document;
sending the first bill to a user side corresponding to the scored user identification information;
receiving the first bill and providing a service corresponding to the product;
and recovering the first bill, unfreezing the frozen fund of the scoring user and allocating the unfrozen fund to a fund account of the scored user terminal.
Specifically, the evaluation user inputs a transaction request through a browser or an evaluation application of the user side, the evaluation server receives the transaction request sent by the evaluation user side, an input module of the transaction request is generally connected with information of a transaction product, the extraction module extracts account fund information of the user corresponding to the user identification information and other personal basic information, the personal basic information comprises address information, a user name and the like, and a first bill is generated according to the account fund information corresponding to the frozen fund; the first bill comprises basic information of both transaction parties, product information and the like, the basic information can comprise an ID number, an address and the like, the product information further comprises information of product price, product name, type and the like, and the evaluation server sends the first bill to the scored user side. The grading user side provides goods and or services, the grading user side or the grading user side initiates a transaction completion request, and the grading server receives the request for unfreezing funds and transfers the funds to a fund account or a bank account of the grading user.
The transaction request carries user identification information, the transaction request comprises product information, and the product information carries evaluated user information.
Specifically, for an evaluation user and an evaluated user, when the evaluation user accesses the evaluation server through a browser or an evaluation application of an evaluation user side for the first time, registration information needs to be input on a registration page provided by the evaluation server, where the registration information includes evaluation user identification information and detailed information, the evaluation user identification information may specifically be a unique user name or a telephone number, and the detailed information further includes bank card information, fund account information, identity information, address information, and the like; on the other hand, when the evaluated user accesses the evaluation server through the browser or the evaluation application of the evaluated user end for the first time, registration information needs to be input in a registration page provided by the evaluation server, the registration information includes product/service information, evaluated user identification information, evaluated user detailed information and the like, the evaluated user identification information is the same as the evaluated user, and the product/service information is bound by the evaluated user identification information.
Further, before the step E, the method further includes:
s195, step G: receiving a restriction request sent by the evaluated user side, wherein the restriction request comprises a restriction condition;
evaluating the evaluation user according to the limiting conditions to generate a limiting result;
and sending the limiting result to an evaluation user side.
Specifically, the evaluation server receives a restriction request sent by an evaluated user side, where the restriction condition may be a query request of one or more first-order first-history score data of the scoring user, for example, the excluded evaluation user cannot query the evaluated user who initiates the restriction request at the evaluation user side, and the restriction module performs partial exclusion on the scoring user according to the restriction condition and sends the exclusion result to a corresponding evaluation user side; the restriction request includes a restriction condition for the evaluation user; the method comprises the steps of limiting, preventing a user from being swiped or maliciously scored, wherein the limiting condition can be that a certain item or certain items of first-order historical scoring data of a rating user is not visible or other conditions are set for the rating user when the certain item or certain items of first-order historical scoring data of a specific rating user is lower than a certain value.
Example 2
According to fig. 4, in one embodiment, a transaction evaluation device is provided, which includes a memory, a processor, and a transaction evaluation program stored in the memory and executable on the processor, and is mainly used for executing the above method, the evaluation device can be installed on a product with a display screen and a networking function for operation, the transaction evaluation program includes a receiving module, and the receiving module receives current scoring data sent by a scoring user terminal; the current scoring data comprises a scoring user identifier and a scored user identifier;
the extraction module extracts first historical scoring data corresponding to the scoring user identification; extracting second historical scoring data corresponding to the scored user identification;
the data processing module calculates the current grading data and the first historical grading data to obtain first comprehensive grading data; carrying out mean value calculation on the current grading data and the second historical grading data to obtain second comprehensive grading data;
and the output module outputs and displays the first comprehensive grading data and the second comprehensive grading data.
A storage module: and storing the current grading data, the first comprehensive grading data and the second comprehensive grading data.
Specifically, the scoring user identifier is a one-to-one correspondence relationship between the user name of the scoring user and the scoring user, and the scored user identifier is a product of the scoring user or product information of the user, and the information is attached when scoring data is input.
In the embodiment, by extracting, processing, outputting and displaying the historical scoring data of both the scoring user and the scored user, the scoring of the scored user can be not only scored and recorded, but also analyzed, processed, stored and recorded through the first historical scoring data of the scoring user, so that bidirectional data analysis and recording of the scoring user and the scored user are realized.
Specifically, the receiving module further includes a first order data input module and a first order personal preference weight input module, and optionally further includes a second order data input module and a second order personal preference weight input module.
The input modules correspond to different evaluated users and/or consumed products to be displayed at the evaluation user side, and the grading users input the current grading data through the input modules.
Further, according to fig. 5, the system further includes a sorting receiving module and a sorting processing module, the sorting receiving module receives a sorting request of the evaluation user terminal for the evaluated user and/or product, the sorting processing module sorts the evaluated user and/or product according to the sorting request, and displays the sorting result corresponding to the evaluation user.
Specifically, the sorting request module comprises a sorting condition module, the scoring user only needs to click the sorting condition module displayed by the scoring user side to perform single click or multiple click combination to realize sorting request input, the sorting condition module is provided with an extraction instruction for extracting corresponding data, the sorting condition module sends the sorting condition and the extraction instruction to the sorting module, and the sorting module sorts the evaluated user according to the sorting condition and the extraction information; and obtaining a sorting result and displaying the sorting result on the grading user side corresponding to the sorting request.
Further, according to fig. 6, the system further includes a transaction receiving module, which receives a transaction request initiated by the scoring user side; the transaction request carries user identification information and transaction product information;
the suggestion extraction module extracts account fund information of the user corresponding to the user identification information;
the transaction processing module freezes funds corresponding to the account fund information to generate a first bill; and sending the first bill to the scored client corresponding to the transaction product information.
The transaction receiving module receives a transaction completion request sent by a grading user side or a graded user side, and the transaction processing module unfreezes the frozen fund according to the transaction completion request and allocates the unfrozen fund to a graded user fund account.
Specifically, the input module of the specific transaction request is generally linked with information of a transaction product, the extraction module extracts account fund information of a user corresponding to the user identification information and other personal basic information, the personal basic information includes address information, a user name and the like, and generates a first bill according to the account fund information corresponding to the frozen fund information; and the evaluation server sends the first bill to the scored client. The grading user side provides goods and or services, the grading user side or the grading user side initiates a transaction completion request, and the grading server receives the request for unfreezing funds and transfers the funds to a fund account or a bank account of the grading user.
The transaction request carries user identification information, the transaction request comprises product information, and the product information carries evaluated user information.
Further, the system further comprises a limitation receiving module, wherein the limitation receiving module receives a limitation request for the evaluation user sent by the evaluated user side, and the limitation request comprises a limitation condition for the evaluation user;
the limiting processing module limits the evaluation user according to the limiting conditions; and sending the limiting result to a corresponding evaluation user side.
Specifically, according to fig. 7, the limitation receiving module includes a limitation condition module and a limitation allowance module, the limiting condition module is a limiting condition module corresponding to the first historical scoring data of each order, the limiting condition module comprises a data setting module, inputting a set value through the data setting module to generate a limiting condition, wherein the limiting period permission is invisible, order placing unavailable and the like, the scored user only needs to click and set through the sorting condition module and the sorting permission module displayed by the scoring user end to realize the input of the limit request, the limiting condition module is provided with an extracting instruction for extracting corresponding data, the limiting condition module sends a limiting request and the extracting instruction to the sequencing module, the limiting module extracts and limits data of the evaluated user according to the limiting request and the extracting instruction; and displaying the obtained limiting result on the limited scoring user side, for example, if the limited scoring user side meets the limiting request condition initiated by the evaluated user, the scoring user will not place an order for the scored user or query the scored user corresponding to the term of the scored user.
The benefits of the two parties are guaranteed to the maximum extent.
Example 3
A computer-readable storage medium, characterized in that it stores a computer program for use by the method of any one of claims 1-8. .
Through steps S200, A to S203, after the current scoring data is received, the historical scoring data of both the scoring user and the scored user are extracted, processed, output and displayed, so that the scoring of the scoring user can be scored and recorded, the scoring of the scoring user can be analyzed, processed, stored and recorded through the first historical scoring data of the scoring user, and the bidirectional data analysis and recording of the scoring user and the scored user are realized.
And through the step A0 of S199, the user sets and inputs the at least two first scoring values and the first percentage value, so that the current scoring data can be more accurate, the selection and reference of different people to different requirements can be met, and the information transmission is more definite.
Step S196, in combination with the second historical score data in the present invention, the ranking request can select ranking according to the personal preference weight preference of the scoring user, so that the importance ratio of "person" and "thing" in the transaction or service can be reflected, and the segmentation angles included in the "person" or "thing" respectively can be reflected, and the data can be more accurately digitized.
S195, in step G, through the limit request of the evaluated user to the evaluating user, the extracting module extracts the first historical evaluation data of the evaluating user, and evaluates the evaluating user according to the limit condition; the method can eliminate and limit some malicious evaluation users and the bill-swiping evaluation users, further protect the rights and interests of the evaluated party, and can also reduce misleading to other evaluation users.
In the above description, the technical features of the embodiments may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments are not described, but should be considered as the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
Further, the terminal may further include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
Optionally, the terminal may further include a camera, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. Such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that may turn off the display screen and/or the backlight when the mobile terminal is moved to the ear. As one of the motion sensors, the gravity acceleration sensor may detect the magnitude of acceleration in each direction (generally, three axes), and may detect the magnitude and direction of gravity when the mobile terminal is stationary, and may be used for applications of recognizing the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration recognition related functions (such as pedometer and tapping), and the like, which are not described herein again.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (12)
1. A method of transaction evaluation, comprising:
step A: receiving current grading data sent by a grading user side; the current scoring data comprises a scoring user identifier and a scored user identifier;
and B: extracting first historical scoring data of a scoring user and second historical scoring data of a scored user product;
and C: calculating the mean value of the current grading data and the first historical grading data to obtain first comprehensive grading data;
calculating the mean value of the current grading data and the second historical grading data to obtain second comprehensive grading data;
step D: and storing and displaying the current grading data, the first comprehensive grading data and the second comprehensive grading data.
2. The method of transaction evaluation according to claim 1,
the current scoring data comprises at least two items of first-order current scoring data and first-order personal preference weight data corresponding to each item of the first-order current scoring data;
the first historical scoring data comprises at least two first-order first historical scoring data corresponding to the current scoring data and first-order personal preference weight first historical data corresponding to each first-order first historical scoring data;
the second historical scoring data comprises at least two first-order second historical scoring data corresponding to the current scoring data and first-order personal preference weight second historical data corresponding to each first-order second historical scoring data;
step C comprises calculating the mean value of the first-order current scoring data and the first-order first historical scoring data to obtain a first-order first scoring data mean value; calculating the average value of the first-order personal preference weight data and the first historical data of the first-order personal preference weight to obtain the average value of the first-order first personal preference weight data;
calculating the mean value of the first-order current scoring data and the first-order second historical scoring data to obtain a first-order second scoring data mean value; and calculating the average value of the first-order personal preference weight data and the second historical data of the first-order personal preference weight to obtain the average value of the first-order second personal preference weight data.
3. The method of transaction evaluation according to claim 2,
the first-order current scoring data comprises at least two items of second-order current scoring data and second-order personal preference weight data corresponding to the second-order current scoring data;
the first-order first historical scoring data corresponding to the first-order current scoring data comprises at least two items of second-order first historical scoring data and second-order personal preference weight second historical data corresponding to the second-order first historical scoring data;
the first-order second historical scoring data corresponding to the first-order current scoring data comprises at least two items of second-order second historical scoring data and second-order personal preference weight second historical data corresponding to the second-order second historical scoring data.
4. The method of transaction evaluation according to claim 2,
the first composite score data comprises: a first order first score data mean, and a first order first person preference weight data mean;
the second composite score data comprises: a first order second score data mean, and a first order second person preference weight data mean;
the step D also comprises the following steps:
storing the current grading data and the first comprehensive grading data corresponding to the grading user; displaying the first comprehensive grading data corresponding to the grading user;
and storing and displaying the current grading data and the second comprehensive grading data corresponding to the graded user.
5. The method of transaction evaluation according to claim 1 or 4, further comprising:
step H: receiving a sorting request of the evaluation user side, wherein the sorting request comprises a sorting condition and a first extraction instruction;
extracting sequencing information corresponding to the first extracting instruction;
ranking the evaluated users according to the ranking conditions and the ranking information; obtaining a sequencing result;
and displaying the sequencing result corresponding to the evaluation user side.
6. The method of transaction evaluation according to claim 1, wherein said step a is preceded by the steps of:
step E: receiving a transaction request initiated by an evaluation user side; the transaction request includes transaction information;
and processing the transaction request, and performing fund transfer and product transfer processing corresponding to the transaction information.
7. The method of transaction valuation of claim 6 further comprising prior to said step E:
step G: receiving a restriction request sent by the evaluated user terminal, wherein the restriction request comprises a restriction condition and a restriction permission;
limiting the evaluation user according to the limiting conditions and the limiting permission to generate a limiting result;
and feeding back the limiting result corresponding to the evaluation user side.
8. An apparatus for transaction evaluation comprising a memory, a processor, and a transaction evaluation program stored in the memory and executable on the processor, the transaction evaluation program comprising: the receiving module receives the current grading data sent by the grading user side; the current scoring data comprises a scoring user identifier and a scored user identifier;
the extraction module is used for extracting first historical scoring data corresponding to the scoring user identification; extracting second historical scoring data corresponding to the scored user identification;
the data processing module is used for calculating the current grading data and the first historical grading data to obtain first comprehensive grading data; carrying out mean value calculation on the current grading data and the second historical grading data to obtain second comprehensive grading data;
the output module is used for outputting and displaying the first comprehensive grading data and the second comprehensive grading data;
a storage module: and storing the current grading data, the first comprehensive grading data and the second comprehensive grading data.
9. The transaction evaluating apparatus of claim 8, wherein the receiving module further comprises a first order data input module and a first order personal preference weight data input module.
10. The transaction evaluating apparatus according to claim 8,
the system also comprises a sequencing receiving module for receiving a sequencing request of the evaluation user terminal, wherein the sequencing request comprises a sequencing condition and a first extraction instruction,
the sorting processing module extracts sorting information corresponding to the first extraction instruction; ranking the evaluated users according to the ranking conditions and the ranking information; and obtaining a sequencing result, and displaying the sequencing result corresponding to the evaluation user.
11. The transaction evaluation apparatus of claim 8, further comprising:
a limitation receiving module, configured to receive a limitation request for the evaluation user sent by the evaluated user side, where the limitation request includes a limitation condition and a limitation permission for the evaluation user;
the limiting processing module is used for limiting the evaluation user according to the limiting conditions and the limiting permission; and feeding back the limiting result corresponding to the evaluation user side.
12. A computer-readable storage medium, characterized in that it stores a computer program for use by the method of any one of claims 1-8.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112035569A (en) * | 2020-08-14 | 2020-12-04 | 联动数科(北京)科技有限公司 | Merchant scoring method and system |
| CN112529575A (en) * | 2020-12-14 | 2021-03-19 | 深圳市快付通金融网络科技服务有限公司 | Risk early warning method, equipment, storage medium and device |
| CN113592333A (en) * | 2021-08-07 | 2021-11-02 | 杭州找查科技有限公司 | Internet comprehensive scoring method, system and device and readable storage medium |
| CN117455573A (en) * | 2023-10-26 | 2024-01-26 | 深圳市维卓数字营销有限公司 | Internet data analysis method and system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104376453A (en) * | 2014-10-29 | 2015-02-25 | 中国建设银行股份有限公司 | Online payment method and system |
| CN105005896A (en) * | 2014-04-18 | 2015-10-28 | 腾讯科技（深圳）有限公司 | Data processing method and apparatus |
| CN105205709A (en) * | 2015-08-20 | 2015-12-30 | 上海鸿安能源科技有限公司 | Application method of network transaction platform |
| CN107679887A (en) * | 2017-08-31 | 2018-02-09 | 北京三快在线科技有限公司 | A kind for the treatment of method and apparatus of trade company's scoring |
| CN108897864A (en) * | 2018-07-03 | 2018-11-27 | 常州工学院 | Personalized overall merit arrangement method and system for commercial articles searching |
| CN109801055A (en) * | 2018-12-04 | 2019-05-24 | 广州市昂宇网络科技有限公司 | A kind of payment processing method of network transaction service |
| CN110363550A (en) * | 2018-03-26 | 2019-10-22 | 上海兰豆信息科技有限公司 | A kind of methods of marking and system |
-
2020
- 2020-03-16 CN CN202010182748.3A patent/CN111369301A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105005896A (en) * | 2014-04-18 | 2015-10-28 | 腾讯科技（深圳）有限公司 | Data processing method and apparatus |
| CN104376453A (en) * | 2014-10-29 | 2015-02-25 | 中国建设银行股份有限公司 | Online payment method and system |
| CN105205709A (en) * | 2015-08-20 | 2015-12-30 | 上海鸿安能源科技有限公司 | Application method of network transaction platform |
| CN107679887A (en) * | 2017-08-31 | 2018-02-09 | 北京三快在线科技有限公司 | A kind for the treatment of method and apparatus of trade company's scoring |
| CN110363550A (en) * | 2018-03-26 | 2019-10-22 | 上海兰豆信息科技有限公司 | A kind of methods of marking and system |
| CN108897864A (en) * | 2018-07-03 | 2018-11-27 | 常州工学院 | Personalized overall merit arrangement method and system for commercial articles searching |
| CN109801055A (en) * | 2018-12-04 | 2019-05-24 | 广州市昂宇网络科技有限公司 | A kind of payment processing method of network transaction service |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112035569A (en) * | 2020-08-14 | 2020-12-04 | 联动数科(北京)科技有限公司 | Merchant scoring method and system |
| CN112529575A (en) * | 2020-12-14 | 2021-03-19 | 深圳市快付通金融网络科技服务有限公司 | Risk early warning method, equipment, storage medium and device |
| CN112529575B (en) * | 2020-12-14 | 2023-12-22 | 深圳市快付通金融网络科技服务有限公司 | Risk early warning method, equipment, storage medium and device |
| CN113592333A (en) * | 2021-08-07 | 2021-11-02 | 杭州找查科技有限公司 | Internet comprehensive scoring method, system and device and readable storage medium |
| CN117455573A (en) * | 2023-10-26 | 2024-01-26 | 深圳市维卓数字营销有限公司 | Internet data analysis method and system |
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