CN118333730A - Product matching analysis-based wind control system and method - Google Patents
Product matching analysis-based wind control system and method Download PDFInfo
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Abstract
The invention discloses a wind control system and a method based on product matching analysis, which belong to the field of data processing, wherein the obtained product type data issued by a transaction counterpart and the type data of sales commodities of the transaction counterpart are substituted into a product matching degree calculation strategy to calculate the product matching degree, the calculated transaction security value and the product matching degree are imported into a transaction risk value assessment strategy to carry out transaction risk value assessment, and transaction early warning is carried out according to the obtained transaction risk value, so that real-time monitoring, deep analysis and comprehensive risk assessment of cross-border electronic commerce data can be realized, the efficiency of data processing and analysis can be improved, more accurate and timely risk early warning and decision support can be provided for enterprises, and the enterprises can be helped to effectively reduce risks.
Description
Technical Field
The invention belongs to the field of data processing, and particularly relates to a product matching analysis-based wind control system and method.
Background
With the rapid development and expansion of the global cross-border e-commerce industry, business environments facing enterprises are increasingly complex, and traditional e-commerce modes cannot meet the increasing data processing requirements and risk management challenges. Along with the explosive growth of data scale, traditional data processing technology is not attractive, meanwhile, enterprises face new challenges in the aspect of risk management and control due to complexity and diversity of cross-border trade, traditional data management modes are often limited by problems of large data volume, multiple data sources and the like, so that data analysis and risk management efficiency is low, real-time monitoring and quick response cannot be realized, and in addition, because various links and main bodies related to cross-border electronic commerce are numerous, traditional risk management means are often limited to single-dimensional monitoring and analysis, various potential risks are difficult to comprehensively grasp and effectively prevent, and the problems exist in the prior art;
For example, in chinese patent with application publication No. CN116596634a, an information management method and system based on a cross-border e-commerce platform are disclosed, including obtaining actual registration basic information of each current e-commerce consign for sale on commission main body on the cross-border e-commerce platform, obtaining historical registration information of each current e-commerce consign for sale on commission main body, and generating an actual consign for sale on commission main body class fraction; acquiring an E-commerce consign for sale on commission qualified main body, acquiring initial product information and product description characteristics, generating initial product characteristics of the product to be consign for sale on commission, and generating initial product difference characteristics; and generating a difference characteristic uploading guide according to the initial product difference characteristic, acquiring actual product information uploaded by the current E-commerce consign for sale on commission main body, generating actual product characteristics according to the actual product information and the product description characteristic, and displaying the actual product characteristics and the actual product information on an E-commerce information management display interface. The method and the system realize the problem of inconsistent consign for sale on commission information and time products, and realize the safe and reliable management of the information on the cross-border e-commerce platform;
The problems presented in the background art exist in the above patents: due to complexity and diversity of cross-border trade, enterprises face new challenges in the aspect of risk management and control, traditional data management modes are often limited by problems of large data volume, various data sources and the like, so that data analysis and risk management efficiency is low, real-time monitoring and quick response cannot be achieved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a wind control system and a method based on product matching analysis.
In order to achieve the above purpose, the present invention provides the following technical solutions: a wind control method based on product matching analysis comprises the following specific steps:
acquiring historical transaction type data, historical transaction amount data, type of released required products and historical transaction evaluation data issued by a transaction counterpart, and acquiring type data of sales commodities of the transaction counterpart;
the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, the type of the transaction and the transaction amount data issued by the transaction counterpart are imported into a transaction security value calculation strategy to calculate a transaction security value;
Substituting the acquired type data of the product required by the transaction counterpart and the type data of the sales commodity of the transaction counterpart into a product matching degree calculation strategy to calculate the product matching degree;
Leading the calculated transaction security value and the product matching degree into a transaction risk value assessment strategy to carry out transaction risk value assessment;
And carrying out transaction early warning according to the obtained transaction risk value.
The specific steps of obtaining the historical transaction type data, the historical transaction amount data, the type of the released required product and the historical transaction evaluation data issued by the transaction counterpart, and meanwhile obtaining the type data of the sales commodity of the transaction counterpart are as follows:
s11, acquiring category data of transaction objects of historical transaction issued by a transaction counterpart on a transaction platform, simultaneously acquiring amount data of the transaction objects of the historical transaction of the transaction counterpart, and simultaneously acquiring category data and transaction price data of required products of the transaction;
s12, acquiring customer transaction evaluation data information of a transaction counterpart after historical transaction, wherein the transaction evaluation data information is scoring data of the transaction after the transaction, such as receiving goods on a panning and scoring in the using process;
S13, acquiring sales type data of the current sales commodity of the trading party, wherein the type data are types of all sales commodity of the trading party and various types of output of the sales commodity.
The method specifically includes the steps of introducing the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, the type of the transaction and the current transaction amount data issued by the transaction counterpart into a transaction security value calculation strategy to calculate a transaction security value, wherein the method comprises the following specific steps of:
S21, acquiring historical transaction amount data, historical transaction type data, type of the transaction and transaction amount data, substituting the historical transaction amount data, the type of the transaction and the transaction amount data into a transaction first phase difference coefficient calculation formula to calculate a transaction first phase difference coefficient, wherein the transaction first phase difference coefficient calculation formula of the ith historical transaction data and the transaction data is as follows: where s () is the number of elements in brackets, A set of the types of the sales commodity in the ith historical transaction data, k is a set of the types of the sales commodity of the present transaction,In order to aggregate the union sets,For the aggregate intersection, ni is the number of categories of items sold in the ith historical transaction data,For the transaction amount of the j-th sales commodity in the i-th historical transaction data,The transaction amount of the j-th sales commodity of the present transaction,Is a kind of duty factor, wherein,The value range of (2) is 0 to 1;
S22, acquiring all calculated transaction first phase difference coefficients of the historical transaction data and the current transaction data, and substituting the historical transaction evaluation data into a transaction safety value calculation formula to calculate a transaction safety value, wherein the transaction safety value calculation formula is as follows: wherein m is the number of all historical transaction data, and di is transaction evaluation data of the ith historical transaction;
The specific steps of substituting the acquired type data of the product required issued by the transaction counterpart and the type data of the commodity sold by the transaction counterpart into the product matching degree calculation strategy to calculate the product matching degree are as follows:
S31, acquiring the types and the required amounts of the commodities which are required to be produced at the present time and are issued by a transaction partner, and simultaneously acquiring the types of all the sold commodities and the various types of the output of the sold commodities by the transaction partner of the transaction partner;
S32, calculating the product matching degree in a calculation formula of the matching value of the types and the required quantity of the commodities which are required to be produced at the present time and are issued by the transaction opposite side, the types of all the sold commodities by the transaction side of the transaction side, and the various types of the output of the sold commodities, wherein the calculation formula of the product matching degree is as follows: Wherein, the method comprises the steps of, wherein, The method is characterized in that the method comprises the steps that a set formed by all types of sold commodities is used as a transaction party of a transaction party, N is the type number of the commodities which are required to be produced at the present time and are issued by the transaction party, and p () is that if the number in brackets is larger than 0Taking outIf p () is 0 or less in parentheses, thenTaking 0, tc as the yield of the c-th commodity of the trading party, and tcx as the required quantity of the c-th commodity issued by the trading party.
It should be noted that the step of introducing the calculated transaction security value and the product matching degree into the transaction risk value assessment policy to perform the transaction risk value assessment includes the following specific steps:
The transaction risk value of the transaction is calculated by acquiring the calculated transaction safety value and the product matching degree and importing the transaction safety value and the product matching degree into a transaction risk value calculation formula, wherein the transaction risk value is calculated in the following way: multiplying the product matching degree by the product matching duty ratio to obtain a product matching coefficient; multiplying the transaction safety value by the transaction safety duty ratio to obtain a transaction safety coefficient; adding the transaction safety coefficient and the product matching coefficient to obtain a transaction risk value;
The specific content of the transaction early warning according to the obtained transaction risk value is as follows:
Comparing the obtained transaction risk value with a set transaction risk threshold, and if the obtained transaction risk value is smaller than the set transaction risk threshold, carrying out transaction risk early warning on a transaction party; if the obtained transaction risk value is greater than or equal to the set transaction risk threshold value, transaction risk early warning is not carried out on the transaction party.
The wind control system based on the product matching analysis is realized based on the wind control method based on the product matching analysis, and specifically comprises a data acquisition module, a transaction safety value calculation module, a product matching degree calculation module, a risk value evaluation module, a transaction early warning module and a control module, wherein the data acquisition module is used for acquiring historical transaction type data, historical transaction amount data, type of a required product and historical transaction evaluation data issued by a transaction counterpart, and meanwhile acquiring type data of a sales commodity of the transaction counterpart, and the transaction safety value calculation module is used for importing the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, type of a transaction and current transaction amount data issued by the transaction counterpart into a transaction safety value calculation strategy to calculate a transaction safety value.
The risk value evaluation module is used for importing the calculated transaction security value and the product matching degree into the transaction risk value evaluation strategy to evaluate the transaction risk value, and the transaction early warning module is used for carrying out transaction early warning according to the obtained transaction risk value.
The control module is used for controlling the operation of the data acquisition module, the transaction security value calculation module, the product matching degree calculation module, the risk value assessment module and the transaction early warning module.
An electronic device, comprising: a processor and a memory, wherein the memory stores a computer program for the processor to call;
The processor executes the wind control method based on the product matching analysis by calling the computer program stored in the memory.
A computer readable storage medium storing instructions that when executed on a computer cause the computer to perform a product matching analysis based wind control method as described above.
Compared with the prior art, the invention has the beneficial effects that:
According to the method, historical transaction type data, historical transaction amount data, type of the released required products and historical transaction evaluation data which are released by the transaction counterpart are obtained, meanwhile, the type data of the sold goods of the transaction counterpart is obtained, the obtained historical transaction type data, historical transaction amount data, historical transaction evaluation data, type of the transaction and current transaction amount data are imported into a transaction security value calculation strategy to calculate transaction security values, the obtained type data of the required products and the type data of the sold goods of the transaction counterpart are substituted into the product matching degree calculation strategy to calculate product matching degree, the transaction security values and the product matching degree obtained by calculation are imported into a transaction risk value evaluation strategy to evaluate transaction risk values, and transaction early warning is carried out according to the obtained transaction risk values, so that the efficiency of data processing and analysis can be improved, more accurate and timely risk early warning and decision support can be provided for enterprises, and enterprises can be helped to effectively reduce risks.
Drawings
FIG. 1 is a schematic diagram of the overall flow of a wind control method based on product matching analysis;
FIG. 2 is a schematic flow chart of a data acquisition step of a wind control method based on product matching analysis;
FIG. 3 is a schematic diagram of an overall framework of a wind control system based on product matching analysis.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
Example 1
The technical problems solved by the present embodiment are: due to complexity and diversity of cross-border trade, enterprises face new challenges in the aspect of risk management and control, traditional data management modes are often limited by problems of large data volume, various data sources and the like, so that data analysis and risk management efficiency is low, real-time monitoring and quick response cannot be realized, and in addition, due to the fact that various links and main bodies related to cross-border electronic commerce are numerous, traditional risk management means are often limited to single-dimension monitoring and analysis, and various potential risks are difficult to comprehensively grasp and effectively prevent;
to solve the above problems, please refer to fig. 1 and 2, the present invention provides a preferred embodiment: a wind control method based on product matching analysis comprises the following specific steps:
acquiring historical transaction type data, historical transaction amount data, type of released required products and historical transaction evaluation data issued by a transaction counterpart, and acquiring type data of sales commodities of the transaction counterpart;
the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, the type of the transaction and the transaction amount data issued by the transaction counterpart are imported into a transaction security value calculation strategy to calculate a transaction security value;
Substituting the acquired type data of the product required by the transaction counterpart and the type data of the sales commodity of the transaction counterpart into a product matching degree calculation strategy to calculate the product matching degree;
Leading the calculated transaction security value and the product matching degree into a transaction risk value assessment strategy to carry out transaction risk value assessment;
carrying out transaction early warning according to the obtained transaction risk value;
in one implementation manner of this embodiment, the specific steps of obtaining the historical transaction type data, the historical transaction amount data, the type of the released required product and the historical transaction evaluation data issued by the transaction counterpart, and obtaining the type data of the sales commodity of the transaction counterpart are as follows:
s11, acquiring category data of transaction objects of historical transaction issued by a transaction counterpart on a transaction platform, simultaneously acquiring amount data of the transaction objects of the historical transaction of the transaction counterpart, and simultaneously acquiring category data and transaction price data of required products of the transaction;
s12, acquiring customer transaction evaluation data information of a transaction counterpart after historical transaction, wherein the transaction evaluation data information is scoring data of the transaction after the transaction, such as receiving goods on a panning and scoring in the using process;
s13, acquiring sales type data of the current sales commodity of the trading party, wherein the type data are types of all sales commodity of the trading party and various types of output of the sales commodity;
In one implementation manner of this embodiment, the method for importing the obtained historical transaction type data, the historical transaction amount data, the historical transaction evaluation data, the type of the present transaction and the current transaction amount data issued by the transaction counterpart into the transaction security value calculation policy to calculate the transaction security value includes the following specific steps:
S21, acquiring historical transaction amount data, historical transaction type data, type of the transaction and transaction amount data, substituting the historical transaction amount data, the type of the transaction and the transaction amount data into a transaction first phase difference coefficient calculation formula to calculate a transaction first phase difference coefficient, wherein the transaction first phase difference coefficient calculation formula of the ith historical transaction data and the transaction data is as follows: where s () is the number of elements in brackets, A set of the types of the sales commodity in the ith historical transaction data, k is a set of the types of the sales commodity of the present transaction,In order to aggregate the union sets,For the aggregate intersection, ni is the number of categories of items sold in the ith historical transaction data,For the transaction amount of the j-th sales commodity in the i-th historical transaction data,The transaction amount of the j-th sales commodity of the present transaction,Is a kind of duty factor, wherein,The value range of (2) is 0 to 1;
S22, acquiring all calculated transaction first phase difference coefficients of the historical transaction data and the current transaction data, and substituting the historical transaction evaluation data into a transaction safety value calculation formula to calculate a transaction safety value, wherein the transaction safety value calculation formula is as follows: wherein m is the number of all historical transaction data, and di is transaction evaluation data of the ith historical transaction;
In one implementation manner of the embodiment, the specific steps of substituting the acquired type data of the product required to be issued by the transaction counterpart and the type data of the sales commodity of the transaction counterpart into the product matching degree calculation strategy to calculate the product matching degree are as follows:
S31, acquiring the types and the required amounts of the commodities which are required to be produced at the present time and are issued by a transaction partner, and simultaneously acquiring the types of all the sold commodities and the various types of the output of the sold commodities by the transaction partner of the transaction partner;
S32, calculating the product matching degree in a calculation formula of the matching value of the types and the required quantity of the commodities which are required to be produced at the present time and are issued by the transaction opposite side, the types of all the sold commodities by the transaction side of the transaction side, and the various types of the output of the sold commodities, wherein the calculation formula of the product matching degree is as follows: Wherein, the method comprises the steps of, wherein, The method is characterized in that the method comprises the steps that a set formed by all types of sold commodities is used as a transaction party of a transaction party, N is the type number of the commodities which are required to be produced at the present time and are issued by the transaction party, and p () is that if the number in brackets is larger than 0Taking outIf p () is 0 or less in parentheses, thenTaking 0, tc as the yield of the c-th commodity of the transaction party, and tcx as the required quantity of the c-th commodity issued by the transaction party;
in one implementation manner of the embodiment, the method for conducting transaction risk value assessment by importing the calculated transaction security value and the product matching degree into a transaction risk value assessment policy includes the following specific steps:
The transaction risk value of the transaction is calculated by acquiring the calculated transaction safety value and the product matching degree and importing the transaction safety value and the product matching degree into a transaction risk value calculation formula, wherein the transaction risk value is calculated in the following way: multiplying the product matching degree by the product matching duty ratio to obtain a product matching coefficient; multiplying the transaction safety value by the transaction safety duty ratio to obtain a transaction safety coefficient; adding the transaction safety coefficient and the product matching coefficient to obtain a transaction risk value;
In one implementation manner of this embodiment, the specific content of performing transaction early warning according to the obtained transaction risk value is:
comparing the obtained transaction risk value with a set transaction risk threshold, and if the obtained transaction risk value is smaller than the set transaction risk threshold, carrying out transaction risk early warning on a transaction party; if the obtained transaction risk value is greater than or equal to the set transaction risk threshold value, transaction risk early warning is not carried out on a transaction party;
in one implementation manner of this embodiment, the set transaction risk threshold, category duty factor, product matching duty ratio and transaction security duty ratio take the following values: the method comprises the steps of obtaining transaction type data, transaction amount data, type of released products required to be evaluated, transaction evaluation data and type data of sales commodities of a transaction party of at least 5000 groups of cross-border electronic commerce historical transaction opponents, extracting abnormal behaviors of 5000 groups of cross-border electronic commerce historical transaction, importing the obtained transaction type data, transaction amount data, type of released products required to be evaluated, transaction evaluation data and type data of sales commodities of the transaction party into a transaction risk value evaluation strategy to obtain a calculated transaction risk value, importing the calculated transaction risk value and abnormal behavior judgment result into fitting software, and outputting a transaction risk threshold, a type ratio coefficient, a product matching ratio and a transaction safety ratio which are set to meet the highest abnormal behavior judgment accuracy.
In this embodiment, it should be noted that, compared with the prior art, the benefits of this embodiment are: the method comprises the steps of obtaining historical transaction type data, historical transaction amount data, type of products required to be released and historical transaction evaluation data issued by a transaction counterpart, obtaining the type data of sales commodities of the transaction counterpart, importing the obtained historical transaction type data, historical transaction amount data, historical transaction evaluation data, type of the transaction and current transaction amount data into a transaction security value calculation strategy to calculate transaction security values, substituting the obtained type data of the products required to be released by the transaction counterpart and the type data of the sales commodities of the transaction counterpart into the product matching degree calculation strategy to calculate product matching degree, importing the calculated transaction security values and product matching degree into a transaction risk value evaluation strategy to evaluate transaction risk values, and carrying out transaction early warning according to the obtained transaction risk values, so that the efficiency of data processing and analysis can be improved, more accurate and timely risk early warning and decision support can be provided for enterprises, and enterprises can be helped to effectively reduce risks.
Example 2
As shown in fig. 3, a product matching analysis-based wind control system is implemented based on the product matching analysis-based wind control method, and specifically includes a data acquisition module, a transaction security value calculation module, a product matching degree calculation module, a risk value evaluation module, a transaction early warning module and a control module, where the data acquisition module is configured to acquire historical transaction type data, historical transaction amount data, type of a product required to be issued and historical transaction evaluation data issued by a transaction counterpart, and acquire type data of a commodity sold by the transaction counterpart, and the transaction security value calculation module is configured to import the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, type of a transaction and current transaction amount data issued by the transaction counterpart into a transaction security value calculation policy to perform calculation of a transaction security value; the product matching degree calculation module is used for substituting the acquired product type data required by the transaction opponent and the type data of the sales commodity of the transaction opponent into the product matching degree calculation strategy to calculate the product matching degree, the risk value evaluation module is used for importing the calculated transaction security value and the product matching degree into the transaction risk value evaluation strategy to evaluate the transaction risk value, and the transaction early warning module is used for carrying out transaction early warning according to the obtained transaction risk value; the control module is used for controlling the operation of the data acquisition module, the transaction security value calculation module, the product matching degree calculation module, the risk value evaluation module and the transaction early warning module.
Example 3
The present embodiment provides an electronic device including: a processor and a memory, wherein the memory stores a computer program for the processor to call;
The processor executes the wind control method based on the product matching analysis by calling the computer program stored in the memory.
The electronic device may have a relatively large difference due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, where at least one computer program is stored in the memories, and the computer program is loaded and executed by the processors to implement a wind control method based on product matching analysis provided by the above method embodiments. The electronic device can also include other components for implementing the functions of the device, for example, the electronic device can also have wired or wireless network interfaces, input-output interfaces, and the like, for inputting and outputting data. The present embodiment is not described herein.
Example 4
The present embodiment proposes a computer-readable storage medium having stored thereon an erasable computer program;
the computer program, when executed on the computer device, causes the computer device to perform a method of wind control based on product matching analysis as described above.
For example, the computer readable storage medium can be Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), compact disk Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM), magnetic tape, floppy disk, optical data storage device, and the like.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
It should be understood that determining B from a does not mean determining B from a alone, but can also determine B from a and/or other information.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions in accordance with embodiments of the present invention are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by way of wired or/and wireless networks from one website site, computer, server, or data center to another. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc. that contain one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Claims (10)
1. The wind control method based on the product matching analysis is characterized by comprising the following specific steps of:
acquiring historical transaction type data, historical transaction amount data, type of released required products and historical transaction evaluation data issued by a transaction counterpart, and acquiring type data of sales commodities of the transaction counterpart;
the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, the type of the transaction and the transaction amount data issued by the transaction counterpart are imported into a transaction security value calculation strategy to calculate a transaction security value;
Substituting the acquired type data of the product required by the transaction counterpart and the type data of the sales commodity of the transaction counterpart into a product matching degree calculation strategy to calculate the product matching degree;
Leading the calculated transaction security value and the product matching degree into a transaction risk value assessment strategy to carry out transaction risk value assessment;
And carrying out transaction early warning according to the obtained transaction risk value.
2. The method for air control based on product matching analysis according to claim 1, wherein the specific steps of obtaining historical transaction type data, historical transaction amount data, type of the released required product and historical transaction evaluation data issued by the transaction counterpart, and obtaining type data of the sales commodity of the transaction counterpart are as follows:
s11, acquiring category data of transaction objects of historical transaction issued by a transaction counterpart on a transaction platform, simultaneously acquiring amount data of the transaction objects of the historical transaction of the transaction counterpart, and simultaneously acquiring category data and transaction price data of required products of the transaction;
S12, acquiring customer transaction evaluation data information of a transaction counterpart after historical transaction, wherein the transaction evaluation data information is scoring data of the transaction after the transaction;
S13, acquiring sales type data of the current sales commodity of the trading party, wherein the type data are types of all sales commodity of the trading party and various types of output of the sales commodity.
3. The method for wind control based on product matching analysis according to claim 2, wherein the step of introducing the obtained historical transaction type data, historical transaction amount data, historical transaction evaluation data, type of the present transaction and the present transaction amount data issued by the transaction counterpart into the transaction security value calculation policy to calculate the transaction security value comprises the following specific steps:
S21, acquiring historical transaction amount data, historical transaction type data, type of the transaction and transaction amount data, substituting the historical transaction amount data, the type of the transaction and the transaction amount data into a transaction first phase difference coefficient calculation formula to calculate a transaction first phase difference coefficient, wherein the transaction first phase difference coefficient calculation formula of the ith historical transaction data and the transaction data is as follows: where s () is the number of elements in brackets, A set of the types of the sales commodity in the ith historical transaction data, k is a set of the types of the sales commodity of the present transaction,In order to aggregate the union sets,For the aggregate intersection, ni is the number of categories of items sold in the ith historical transaction data,For the transaction amount of the j-th sales commodity in the i-th historical transaction data,The transaction amount of the j-th sales commodity of the present transaction,Is a kind of duty factor, wherein,The value range of (2) is 0 to 1;
S22, acquiring all calculated transaction first phase difference coefficients of the historical transaction data and the current transaction data, and substituting the historical transaction evaluation data into a transaction safety value calculation formula to calculate a transaction safety value, wherein the transaction safety value calculation formula is as follows: where m is the number of all historical transaction data, and di is the transaction evaluation data of the ith historical transaction.
4. The method for air control based on product matching analysis as claimed in claim 3, wherein the specific steps of substituting the acquired type data of the product required by the transaction counterpart and the type data of the sales commodity of the transaction counterpart into the product matching degree calculation strategy to calculate the product matching degree are as follows:
S31, acquiring the types and the required amounts of the commodities which are required to be produced at the present time and are issued by a transaction partner, and simultaneously acquiring the types of all the sold commodities and the various types of the output of the sold commodities by the transaction partner of the transaction partner;
S32, calculating the product matching degree in a calculation formula of the matching value of the types and the required quantity of the commodities which are required to be produced at the present time and are issued by the transaction opposite side, the types of all the sold commodities by the transaction side of the transaction side, and the various types of the output of the sold commodities, wherein the calculation formula of the product matching degree is as follows: Wherein, the method comprises the steps of, wherein, The method is characterized in that the method comprises the steps that a set formed by all types of sold commodities is used as a transaction party of a transaction party, N is the type number of the commodities which are required to be produced at the present time and are issued by the transaction party, and p () is that if the number in brackets is larger than 0Taking outIf p () is 0 or less in parentheses, thenTaking 0, tc as the yield of the c-th commodity of the trading party, and tcx as the required quantity of the c-th commodity issued by the trading party.
5. The method for air control based on product matching analysis according to claim 4, wherein the step of introducing the calculated transaction security value and the product matching degree into a transaction risk value assessment policy for transaction risk value assessment comprises the following specific steps:
the transaction risk value of the transaction is calculated by acquiring the calculated transaction safety value and the product matching degree and importing the transaction safety value and the product matching degree into a transaction risk value calculation formula, wherein the transaction risk value is calculated in the following way: multiplying the product matching degree by the product matching duty ratio to obtain a product matching coefficient; multiplying the transaction safety value by the transaction safety duty ratio to obtain a transaction safety coefficient; and adding the transaction safety coefficient and the product matching coefficient to obtain a transaction risk value.
6. The method for air control based on product matching analysis according to claim 5, wherein the specific content of the transaction pre-warning according to the obtained transaction risk value is:
Comparing the obtained transaction risk value with a set transaction risk threshold, and if the obtained transaction risk value is smaller than the set transaction risk threshold, carrying out transaction risk early warning on a transaction party; if the obtained transaction risk value is greater than or equal to the set transaction risk threshold value, transaction risk early warning is not carried out on the transaction party.
7. The product matching analysis-based wind control system is realized based on the product matching analysis-based wind control method according to any one of claims 1-6, and is characterized by specifically comprising a data acquisition module, a transaction safety value calculation module, a product matching degree calculation module, a risk value evaluation module, a transaction early warning module and a control module, wherein the data acquisition module is used for acquiring historical transaction type data, historical transaction amount data, type of released required products and historical transaction evaluation data issued by a transaction counterpart, and simultaneously acquiring type data of sales commodities of the transaction counterpart, and the transaction safety value calculation module is used for importing the acquired historical transaction type data, historical transaction amount data, historical transaction evaluation data, type of the transaction and current transaction amount data issued by the transaction counterpart into a transaction safety value calculation strategy to calculate a transaction safety value.
8. The system of claim 7, wherein the product matching degree calculation module is configured to substitute the acquired product type data required by the transaction counterpart and the type data of the sales commodity of the transaction counterpart into a product matching degree calculation policy to perform product matching degree calculation, the risk value evaluation module is configured to introduce the calculated transaction security value and the product matching degree into the transaction risk value evaluation policy to perform transaction risk value evaluation, the transaction early-warning module is configured to perform transaction early-warning according to the obtained transaction risk value, and the control module is configured to control operations of the data acquisition module, the transaction security value calculation module, the product matching degree calculation module, the risk value evaluation module, and the transaction early-warning module.
9. An electronic device, comprising: a processor and a memory, wherein the memory stores a computer program for the processor to call;
-the processor executes a product matching analysis based pneumatic control method as claimed in any one of claims 1-6 by invoking a computer program stored in the memory.
10. A computer readable storage medium storing instructions which, when executed on a computer, cause the computer to perform a product matching analysis based wind control method according to any one of claims 1-6.
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