Merchant screening method, device and equipment and storage medium
By analyzing merchant business information using the merchant classification model and automatically determining the merchant type, the problems of complex indicators and low efficiency during manual screening of bank personnel are solved, and fast and accurate screening of high-quality merchants is achieved.
Patent Information
- Application Number
- CN202411965807.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-30
- Publication Date
- 2025-04-25
AI Technical Summary
In the existing technology, when bank personnel manually screen high-quality merchants, they encounter the problem of complex indicator dimensions and inaccurate thresholds of various indicators, resulting in too large data volume that cannot be quickly and in real time.
By obtaining the business information of each merchant, using the pre-trained merchant classification model, the merchant type is determined based on multiple business indicators in the business information (such as establishment time, rating information, number of operator replacements, operating income, transaction volume, and return rate), and automatic screening is achieved.
The efficiency and accuracy of merchant type determination are improved, merchant screening based on unified standards is realized, and the problem of insufficient efficiency and accuracy of manual screening is overcome.
Smart Images
Figure CN119884872A_ABST
Abstract
Description
Technical Field
[0001] Embodiments of the present invention relate to the field of artificial intelligence technology, and in particular, to a merchant screening method, device, equipment and storage medium. Background Art
[0002] In the context of promoting financial digitalization, bank staff need to actively screen high-quality merchants for business marketing.
[0003] In the prior art, bank staff are usually required to screen high-quality merchants based on the merchant data of the merchants. Specifically, multiple indicators can be determined based on the merchant data, and whether the user belongs to a high-quality merchant can be determined based on each indicator, so as to screen high-quality merchants based on multiple dimensions.
[0004] However, the standards for manual screening are difficult to unify and the efficiency is poor. Summary of the invention
[0005] The present invention provides a merchant screening method, device, equipment and storage medium to achieve screening of high-quality merchants based on unified standards.
[0006] In a first aspect, an embodiment of the present invention provides a merchant screening method, the method comprising:
[0007] Acquire business information of each merchant, wherein the business information includes at least one business indicator;
[0008] Inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant;
[0009] The high-quality merchants are determined as target merchants.
[0010] The technical solution of an embodiment of the present invention provides a merchant screening method, comprising: obtaining business information of each merchant, wherein the business information includes at least one business indicator; inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant; and determining the merchants of high-quality types as target merchants. The above technical solution can first obtain merchants to be screened and business information of merchants from multiple channels, specifically, multiple business indicators of merchants can be obtained. Secondly, multiple business indicators corresponding to each merchant can be input into a pre-trained merchant classification model. The merchant classification model can determine the merchant's scoring information according to the multiple business indicators corresponding to the merchant and the indicator threshold and weight information corresponding to each business indicator, and then determine the merchant's type according to the merchant's scoring information and the preset scoring threshold, so as to quickly determine the merchant's more accurate type, improve the efficiency and accuracy of determining the merchant's type, and determine high-quality merchants from merchants in multiple channels based on the unified merchant classification standard built into the merchant classification model, and then determine high-quality merchants as target merchants for business marketing, realize automatic screening of target merchants, and further improve the efficiency and accuracy of marketing. It overcomes the shortcomings of the existing technology that bank personnel encounter when manually screening high-quality merchants, such as complex indicator dimensions and inaccurate thresholds of various indicators, and the large amount of data that cannot be quickly and real-time screened.
[0011] Furthermore, the business indicators include establishment time, scoring information, number of operator changes within a preset period, business income within a preset period, transaction volume within a preset period, and return rate within a preset period.
[0012] Furthermore, the training process of the merchant classification model includes:
[0013] Obtain business information of high-quality merchants in the historical period;
[0014] Input the business information and quality types of the plurality of quality merchants as training data into a logistic regression model, and determine a loss function;
[0015] For each of the business indicators, determining an indicator threshold and weight information corresponding to the business indicator when it is determined that the loss function converges;
[0016] A merchant classification standard is determined according to the indicator threshold and the weight information of each of the business indicators, and the merchant classification model is determined according to the merchant classification standard and the logistic regression model.
[0017] Furthermore, the loss function is composed of a linear regression function and a sigmoid function.
[0018] Further, determining the indicator threshold and weight information corresponding to the business indicator when determining that the loss function converges includes:
[0019] When it is determined that the loss function converges, determining the indicator value corresponding to the business indicator and the correlation coefficient of the degree of association between the business indicator and the high-quality type;
[0020] The indicator value corresponding to the business indicator is determined as the indicator threshold corresponding to the business indicator, and the correlation coefficient of the degree of association between the business indicator and the high-quality type is determined as the weight information corresponding to the business indicator.
[0021] Furthermore, the business information of each merchant is input as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant, including:
[0022] The business information of each of the merchants is input as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each of the merchants according to the business indicators contained in the business information of each of the merchants and the merchant classification standard.
[0023] In a second aspect, an embodiment of the present invention further provides a merchant screening device, the device comprising:
[0024] An acquisition module, used to acquire business information of each merchant, wherein the business information includes at least one business indicator;
[0025] A determination module, used for inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant;
[0026] An execution module is used to determine the high-quality merchants as target merchants.
[0027] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:
[0028] at least one processor; and a memory communicatively coupled to the at least one processor;
[0029] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the merchant screening method as described in any one of the first aspects.
[0030] In a fourth aspect, an embodiment of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, are used to execute the merchant screening method as described in any one of the first aspects.
[0031] In a fifth aspect, the present application provides a computer program product, which includes computer instructions. When the computer instructions are executed on a computer, the computer executes the merchant screening method provided in the first aspect.
[0032] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium, wherein the computer-readable storage medium may be packaged together with the processor of the merchant screening device, or may be packaged separately from the processor of the merchant screening device, which is not limited in this application.
[0033] The description of the second, third, fourth and fifth aspects in this application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third, fourth and fifth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.
[0034] In this application, the name of the above-mentioned merchant screening device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. As long as the functions of each device or functional module are similar to those of this application, they fall within the scope of the claims of this application and their equivalent technologies.
[0035] These and other aspects of the present application will become more apparent from the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0037] Figure 1 A flowchart of a merchant screening method provided by an embodiment of the present invention;
[0038] Figure 2 A schematic diagram of the structure of a merchant screening device provided by an embodiment of the present invention;
[0039] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.
[0041] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.
[0042] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.
[0043] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.
[0044] It should be mentioned before discussing exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe various operations (or steps) as sequential processes, many operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of various operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to methods, functions, procedures, subroutines, subprograms, etc. In addition, the embodiments in the present invention and the features in the embodiments can be combined with each other without conflict.
[0045] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.
[0046] In the description of the present application, unless otherwise specified, “plurality” means two or more.
[0047] Figure 1A flowchart of a merchant screening method provided by an embodiment of the present invention is provided. This embodiment can be applied to situations where high-quality merchants need to be screened based on unified standards to improve the efficiency of high-quality merchant screening. The method can be executed by a merchant screening device, such as Figure 1 As shown, the specific steps include:
[0048] Step 110: Obtain business information of each merchant.
[0049] Among them, the business information includes at least one business indicator, and the business indicator includes establishment time, scoring information, the number of times the operator is changed within a preset period, business income within a preset period, transaction volume within a preset period, and return rate within a preset period.
[0050] The preset time period can be set according to actual needs, for example, it can be within three months before the current time.
[0051] Specifically, the business information of merchants in the channel can be obtained through multiple channels. For example, merchants settled in these platforms and their business information can be obtained through review platforms, food delivery platforms, and navigation platforms. These merchants are the merchants to be screened. The business information of merchants may include at least one of the establishment time, rating information, the number of changes of operators within three months before the current time, the operating income within three months before the current time, the transaction volume within three months before the current time, and the return rate within three months before the current time.
[0052] In the embodiment of the present invention, merchants to be screened and their business information are obtained through multiple channels, thereby determining the merchants and their business information required for merchant screening.
[0053] Step 120: Input the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant.
[0054] Among them, the merchant classification model is obtained by training a logistic regression model based on the business information of merchants that have been determined to be high-quality merchants. The merchant can be determined as a high-quality type or an ordinary type based on the specific values of each business indicator in the merchant's business information and the merchant classification standards.
[0055] In one implementation, step 120 may specifically include:
[0056] The business information of each of the merchants is input as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each of the merchants according to the business indicators contained in the business information of each of the merchants and the merchant classification standard.
[0057] Specifically, after obtaining the business information of the merchants to be screened, the business information of each merchant can be input into the merchant classification model. The merchant classification model can determine whether the merchant is a high-quality type or an ordinary type by analyzing the specific values of each business indicator in the merchant's business information and referring to the merchant classification standards built into the merchant classification model.
[0058] In one implementation, the training process of the merchant classification model includes:
[0059] Obtain the business information of high-quality merchants in a historical period; input the business information and high-quality types of multiple high-quality merchants as training data into a logistic regression model, and determine a loss function; for each business indicator, determine the indicator threshold and weight information corresponding to the business indicator when determining that the loss function converges; determine a merchant classification standard based on the indicator threshold and the weight information of each business indicator, and determine the merchant classification model based on the merchant classification standard and the logistic regression model.
[0060] Further, determining the indicator threshold and weight information corresponding to the business indicator when determining that the loss function converges includes:
[0061] When determining that the loss function has converged, determine the indicator value corresponding to the business indicator and the correlation coefficient of the degree of association between the business indicator and the high-quality type; determine the indicator value corresponding to the business indicator as the indicator threshold corresponding to the business indicator, and determine the correlation coefficient of the degree of association between the business indicator and the high-quality type as the weight information corresponding to the business indicator.
[0062] Specifically, it is possible to obtain high-quality merchants in a historical period and business information of each high-quality merchant through multiple channels, and split the business information according to indicator dimensions to obtain multiple business indicators of each high-quality merchant, such as the establishment time, scoring information, the number of operator changes in the past three months, the operating income in the past three months, the transaction volume in the past three months, and the return rate in the past three months.
[0063] After determining the high-quality merchants and the multi-dimensional business information of each high-quality merchant, the multi-dimensional business information of the high-quality merchants and the high-quality types are input into the logistic regression model as training data, and the logistic regression model is trained and the loss function is calculated at the same time. The loss function is composed of the linear regression function and the sigmoid function, which is the superposition of the linear regression function and the sigmoid function. The general expression is
[0064] Furthermore, for each business indicator, the loss function is fitted on the business indicator, and the change of the function value is observed. If the loss function converges when the indicator value of the business indicator is greater than or less than a certain value, that is, the function value fluctuation tends to be stable and the trend is close to parallel, the indicator value corresponding to the business indicator can be determined as the indicator threshold corresponding to the business indicator. At the same time, the correlation coefficient of the degree of correlation between the business indicator and the type can be determined, and the correlation coefficient of the degree of correlation between the business indicator and the high-quality type can be determined as the weight information corresponding to the business indicator.
[0065] By fitting the loss function on each business indicator, the more accurate indicator threshold and weight information of each business indicator can be determined. The indicator threshold of each business indicator is determined by historical high-quality merchants, which effectively improves the accuracy and interpretability of the indicator threshold. In addition, the indicator threshold with significant risk identification effect and business guidance significance can be used as a risk prevention and control rule. After determining the indicator threshold and weight information of each business indicator, the merchant classification standard can be determined according to the indicator threshold and weight information of each business indicator. The merchant classification standard is built into the logistic regression model to obtain the merchant classification model.
[0066] Of course, merchants, business information and types obtained randomly from multiple channels can also be used as test data. During the model training process, the loss value can be calculated on the test data. If the loss value is large, the model training needs to be continued until the loss value converges to a smaller value, and the merchant classification model can be obtained.
[0067] In actual applications, the merchant classification standard also includes a preset scoring threshold. After the merchant's business information is input into the merchant classification model, the merchant classification standard can first compare the business indicators in the business information with the corresponding indicator thresholds, determine the size relationship between the business indicators and the indicator thresholds and the specific difference, and then compare the merchant's scoring information with the preset scoring threshold based on the specific difference and the corresponding weight information. If the merchant's scoring information is greater than the preset scoring threshold, it can be determined that the merchant's type is a high-quality type. If the merchant's scoring information is not greater than the preset scoring threshold, it can be determined that the merchant's type is an ordinary type.
[0068] In the embodiment of the present invention, by inputting the business information of the merchant into the merchant classification model, the merchant classification model can quickly determine the type of the merchant according to the business information of the merchant, thereby improving the efficiency and accuracy of determining the type of the merchant.
[0069] Step 130: Determine the high-quality merchants as target merchants.
[0070] Specifically, after determining the type of each merchant, merchants of high-quality type may be determined as target merchants for business marketing.
[0071] In the embodiment of the present invention, after determining high-quality merchants among merchants in multiple channels based on the unified merchant classification standard built into the merchant classification model, the high-quality merchants are determined as target merchants for business marketing, thereby realizing automatic screening of target merchants.
[0072] The merchant screening method provided by an embodiment of the present invention includes: obtaining business information of each merchant, wherein the business information includes at least one business indicator; inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant; and determining the high-quality type of the merchant as the target merchant. The above technical solution can first obtain merchants to be screened and business information of merchants from multiple channels, specifically, multiple business indicators of merchants can be obtained. Secondly, multiple business indicators corresponding to each merchant can be input into a pre-trained merchant classification model. The merchant classification model can determine the merchant's scoring information according to the multiple business indicators corresponding to the merchant and the indicator threshold and weight information corresponding to each business indicator, and then determine the merchant's type according to the merchant's scoring information and the preset scoring threshold, so as to quickly determine the merchant's more accurate type, improve the efficiency and accuracy of determining the merchant's type, and determine high-quality merchants from merchants in multiple channels based on the unified merchant classification standard built into the merchant classification model, and then determine high-quality merchants as target merchants for business marketing, realize automatic screening of target merchants, and further improve the efficiency and accuracy of marketing. It overcomes the shortcomings of the existing technology that bank personnel encounter when manually screening high-quality merchants, such as complex indicator dimensions and inaccurate thresholds of various indicators, and the large amount of data that cannot be quickly and real-time screened.
[0073] Figure 2 This is a schematic diagram of the structure of a merchant screening device provided by an embodiment of the present invention, which can be applied to situations where high-quality merchants need to be screened based on unified standards, thereby improving the efficiency of high-quality merchant screening. The device can be implemented by software and / or hardware, and is generally integrated in an electronic device, such as a computer device.
[0074] like Figure 2 As shown, the device comprises:
[0075] The acquisition module 210 is used to acquire the business information of each merchant, wherein the business information includes at least one business indicator;
[0076] A determination module 220, configured to input the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant;
[0077] The execution module 230 is used to determine the high-quality merchants as target merchants.
[0078] The merchant screening device provided in this embodiment obtains business information of each merchant, wherein the business information includes at least one business indicator; inputs the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant; and determines the merchants of high-quality type as target merchants. The above technical solution can first obtain merchants to be screened and business information of merchants from multiple channels, specifically, multiple business indicators of merchants can be obtained. Secondly, multiple business indicators corresponding to each merchant can be input into a pre-trained merchant classification model. The merchant classification model can determine the merchant's scoring information according to the multiple business indicators corresponding to the merchant and the indicator threshold and weight information corresponding to each business indicator, and then determine the merchant's type according to the merchant's scoring information and the preset scoring threshold, so as to quickly determine the merchant's more accurate type, improve the efficiency and accuracy of determining the merchant's type, and determine high-quality merchants from merchants in multiple channels based on the unified merchant classification standard built into the merchant classification model, and then determine high-quality merchants as target merchants for business marketing, realize automatic screening of target merchants, and further improve the efficiency and accuracy of marketing. It overcomes the shortcomings of the existing technology that bank personnel encounter when manually screening high-quality merchants, such as complex indicator dimensions and inaccurate thresholds of various indicators, and the large amount of data that cannot be quickly and real-time screened.
[0079] In one embodiment, the business indicators include establishment time, scoring information, the number of operator changes within a preset period, business income within a preset period, transaction volume within a preset period, and return rate within a preset period.
[0080] Based on the above embodiment, the device further includes:
[0081] A training module is used to obtain business information of high-quality merchants in a historical period; input the business information and high-quality types of multiple high-quality merchants as training data into a logistic regression model, and determine a loss function; for each business indicator, determine the indicator threshold and weight information corresponding to the business indicator when determining that the loss function converges; determine a merchant classification standard based on the indicator threshold and weight information of each business indicator, and determine the merchant classification model based on the merchant classification standard and the logistic regression model.
[0082] The loss function is composed of a linear regression function and a sigmoid function.
[0083] In one implementation, determining the indicator threshold and weight information corresponding to the business indicator when determining that the loss function converges includes:
[0084] When determining that the loss function has converged, determine the indicator value corresponding to the business indicator and the correlation coefficient of the degree of association between the business indicator and the high-quality type; determine the indicator value corresponding to the business indicator as the indicator threshold corresponding to the business indicator, and determine the correlation coefficient of the degree of association between the business indicator and the high-quality type as the weight information corresponding to the business indicator.
[0085] Based on the above embodiment, the determination module 220 is specifically configured to:
[0086] The business information of each of the merchants is input as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each of the merchants according to the business indicators contained in the business information of each of the merchants and the merchant classification standard.
[0087] The merchant screening device provided in the embodiment of the present invention can execute the merchant screening method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the merchant screening method.
[0088] It is worth noting that in the embodiment of the above-mentioned merchant screening device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.
[0089] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 3 A block diagram of an exemplary electronic device 3 suitable for implementing embodiments of the present invention is shown. Figure 3 The electronic device 3 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.
[0090] like Figure 3 As shown, the electronic device 3 is in the form of a general-purpose computing electronic device. The components of the electronic device 3 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).
[0091] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.
[0092] The electronic device 3 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 3, including volatile and non-volatile media, removable and non-removable media.
[0093] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 3 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 3 not shown, usually called a "hard drive"). Although Figure 3 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.
[0094] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.
[0095] The electronic device 3 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the electronic device 3, and / or any device that enables the electronic device 3 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 3 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. Figure 3 As shown, the network adapter 20 communicates with other modules of the electronic device 3 via the bus 18. It should be understood that although Figure 3 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 3, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.
[0096] The processing unit 16 executes various functional applications and page displays by running the programs stored in the system memory 28, for example, implementing the merchant screening method provided in the embodiment of the present invention, which includes:
[0097] Acquire business information of each merchant, wherein the business information includes at least one business indicator;
[0098] Inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant;
[0099] The high-quality merchants are determined as target merchants.
[0100] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the merchant screening method provided by any embodiment of the present invention.
[0101] An embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, for example, a merchant screening method provided by an embodiment of the present invention is implemented. The method includes:
[0102] Acquire business information of each merchant, wherein the business information includes at least one business indicator;
[0103] Inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant;
[0104] The high-quality merchants are determined as target merchants.
[0105] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.
[0106] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.
[0107] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
[0108] Computer program code for performing the operations of the present invention may be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0109] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
[0110] In addition, the acquisition, storage, use, and processing of data in the technical solution of the present invention are in compliance with the relevant provisions of national laws and regulations.
[0111] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims
1. A merchant screening method, characterized in that: include: Acquire business information of each merchant, wherein the business information includes at least one business indicator; Inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant; The high-quality merchants are determined as target merchants.
2. The merchant screening method according to claim 1, characterized in that: The business indicators include establishment time, scoring information, number of changes of operators within a preset period, business income within a preset period, transaction volume within a preset period and return rate within a preset period.
3. The merchant screening method according to claim 1, characterized in that: The training process of the merchant classification model includes: Obtain business information of high-quality merchants in the historical period; Input the business information and quality types of the plurality of quality merchants as training data into a logistic regression model, and determine a loss function; For each of the business indicators, determining an indicator threshold and weight information corresponding to the business indicator when it is determined that the loss function converges; A merchant classification standard is determined according to the indicator threshold and the weight information of each of the business indicators, and the merchant classification model is determined according to the merchant classification standard and the logistic regression model.
4. The merchant screening method according to claim 3, characterized in that: The loss function is composed of a linear regression function and a sigmoid function.
5. The merchant screening method according to claim 3, characterized in that: Determining the indicator threshold and weight information corresponding to the business indicator when determining that the loss function converges includes: When it is determined that the loss function converges, determining the indicator value corresponding to the business indicator and the correlation coefficient of the degree of association between the business indicator and the high-quality type; The indicator value corresponding to the business indicator is determined as the indicator threshold corresponding to the business indicator, and the correlation coefficient of the degree of association between the business indicator and the high-quality type is determined as the weight information corresponding to the business indicator.
6. The merchant screening method according to claim 1, characterized in that: Inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant, including: The business information of each of the merchants is input as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each of the merchants according to the business indicators contained in the business information of each of the merchants and the merchant classification standard.
7. A merchant screening device, characterized in that: include: An acquisition module, used to acquire business information of each merchant, wherein the business information includes at least one business indicator; A determination module, used for inputting the business information of each merchant as input information into a pre-trained merchant classification model, so that the merchant classification model determines the type of each merchant according to the business information of each merchant; An execution module is used to determine the high-quality merchants as target merchants.
8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the merchant screening method as described in any one of claims 1 to 6.
9. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the merchant screening method according to any one of claims 1 to 6 when executed by a computer processor.
10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the merchant screening method according to any one of claims 1 to 6.