CN117726221A - Determination method and device of evaluation result, storage medium and electronic device - Google Patents
Determination method and device of evaluation result, storage medium and electronic device Download PDFInfo
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Abstract
The application discloses a method and a device for determining an evaluation result, a storage medium and an electronic device, wherein the method comprises the following steps: acquiring multi-dimensional business data corresponding to a target enterprise, wherein the multi-dimensional business data at least comprises internal business data of the target enterprise and external business data of the target enterprise; determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; and determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score. By adopting the technical scheme, the problem that the activity of small micro enterprises cannot be accurately determined is solved.
Description
Technical Field
The present invention relates to the field of data analysis, and in particular, to a method and apparatus for determining an evaluation result, a storage medium, and an electronic apparatus.
Background
At present, along with the rapid development of technology, more and more enterprises are established like spring bamboo shoots after rain. These enterprises need to perform enterprise behavior assessment on multiple levels, for example, the enterprise liveness reflects the survival and development conditions of the enterprise according to the multidimensional information of the enterprise, so as to assess the market behavior of the enterprise.
In the related art, the activity of generating business activities by enterprises is generally calculated by generating various information related to the enterprises in the business departments, tax departments, social security institutions, the internet and the like according to the production business activities of the enterprises. However, the method takes large and medium enterprises as main measurement objects, and can not accurately measure the liveness of small and micro enterprises.
Aiming at the problem that the activity of small micro enterprises cannot be accurately determined in the related technology, no effective solution is proposed at present.
Accordingly, there is a need for improvements in the related art to overcome the drawbacks of the related art.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining an evaluation result, a storage medium and an electronic device, so as to at least solve the problem that the activity of a small micro enterprise cannot be accurately determined.
According to an aspect of the embodiments of the present application, there is provided a method for determining an evaluation result, including: acquiring multi-dimensional business data corresponding to a target enterprise, wherein the multi-dimensional business data at least comprises internal business data of the target enterprise and external business data of the target enterprise; determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index; and determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score.
In an exemplary embodiment, obtaining multidimensional service data corresponding to a target enterprise includes: responding to an evaluation instruction of a target object, and determining all enterprises to be evaluated from the evaluation instruction; determining enterprises to be evaluated, of which the enterprise scale is smaller than a preset scale, from all enterprises to be evaluated, and determining the enterprises to be evaluated, of which the enterprise scale is smaller than the preset scale, as the target enterprise; acquiring internal service data when the current service type of the target enterprise is internal service and external service data when the current service type of the target enterprise is external service, and determining the internal service data and the external service data as the multidimensional service data.
In an exemplary embodiment, determining, according to a second evaluation index, a second liveness score corresponding to the external service data includes: acquiring a positive index parameter value of the external service data under the positive credit index and acquiring a negative index parameter value of the external service data under the negative credit index; determining a first sum between the positive index parameter value and the negative index parameter value; and under the condition that the first sum value is determined to belong to a preset range, determining the first sum value as a second liveness score corresponding to the external service data.
In an exemplary embodiment, obtaining the forward indicator parameter value of the external service data under the forward credit indicator includes: under the condition that different forward credit indexes exist, acquiring first index parameter values of the external service data under each forward credit index to obtain a plurality of first index parameter values; wherein the different forward credit index comprises at least one of: whether the target enterprise has an enterprise website, whether the target enterprise has a tax payment record, whether the target enterprise has a branch office, whether the target enterprise has an external investment enterprise, whether the target enterprise has an enterprise information change record, and whether the target enterprise has a migration application record; a second sum value between the plurality of first index parameter values is determined as the forward index parameter value.
In an exemplary embodiment, obtaining a negative indicator parameter value of the external service data under the negative credit indicator includes: under the condition that different negative credit indexes exist, acquiring second index parameter values of the external service data under each negative credit index to obtain a plurality of second index parameter values; wherein the different negative credit indicators comprise at least one of: whether the target enterprise has administrative punishment records, whether the target enterprise has illegal records, and whether the target enterprise has enterprise personnel change records; a third sum value between the plurality of second index parameter values is determined as the negative index parameter value.
In an exemplary embodiment, determining, according to a first evaluation index, a first liveness score corresponding to the internal service data includes: determining other enterprises which do not exchange virtual resources with the target enterprise, and acquiring first internal index parameter values of internal service data of the other enterprises under the first evaluation indexes; wherein the first internal index parameter value includes at least one of: a first service object index parameter value corresponding to the service object index, a first service type index parameter value corresponding to the service type index, and a first service time index parameter value corresponding to the service time index; acquiring a second internal index parameter value of the internal business data of the target enterprise under the first evaluation index; wherein the second internal index parameter value comprises at least one of: a second service object index parameter value corresponding to the service object index, a second service type index parameter value corresponding to the service type index, and a second service time index parameter value corresponding to the service time index; determining a first sum of squares between the first traffic object indicator parameter value and the second internal indicator parameter value, a second sum of squares between the first traffic type indicator parameter value and the second traffic type indicator parameter value, and a third sum of squares between the first traffic time indicator parameter value and the second traffic time indicator parameter value; and determining a weighted sum value between the first square sum, the second square sum and the third square sum as the first liveness score.
In an exemplary embodiment, determining the evaluation result of the multi-dimensional service data based on the first liveness score and/or the second liveness score includes: under the condition that the second liveness score is determined to belong to a preset score range, acquiring a weighted sum value between the first liveness score and the second liveness score; if the weighted sum value is determined to be larger than a preset threshold value, determining that the target enterprise is an active enterprise; if the weighted sum value is smaller than a preset threshold value, determining that the target enterprise is an inactive enterprise; and/or determining that the target enterprise is an inactive enterprise under the condition that the second liveness score is determined not to belong to a preset score range.
According to another aspect of the embodiments of the present application, there is also provided a device for determining an evaluation result, including: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring multi-dimensional service data corresponding to a target enterprise, and the multi-dimensional service data at least comprises internal service data of the target enterprise and external service data of the target enterprise; the score determining module is used for determining a first liveness score corresponding to the internal service data according to a first evaluation index and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index; and the result determining module is used for determining an evaluation result of the multi-dimensional service data based on the first liveness score and/or the second liveness score.
According to yet another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium having stored therein a computer program, wherein the computer program is configured to perform the above-described method of determining an evaluation result when run.
According to still another aspect of the embodiments of the present application, there is further provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the method for determining the evaluation result by the computer program.
According to the method and the device, the multidimensional service data corresponding to the target enterprise can be obtained, wherein the multidimensional service data at least comprise the internal service data of the target enterprise and the external service data of the target enterprise; determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; and determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score. By adopting the technical scheme, the problem that the activity of the small micro-enterprises cannot be accurately determined in the related technology is solved, and the activity of the small micro-enterprises can be accurately determined.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 is a hardware block diagram of a computer terminal that performs a method of determining an evaluation result according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of determining an evaluation result according to an embodiment of the present application;
fig. 3 is a block diagram (a) of the configuration of the determination device of the evaluation result according to the embodiment of the present application;
fig. 4 is a block diagram (two) of the configuration of the determination device of the evaluation result according to the embodiment of the present application.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms and "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The method embodiments provided in the embodiments of the present application may be executed in a computer terminal or similar computing device. Taking the operation on a computer terminal as an example, fig. 1 is a block diagram of the hardware configuration of a computer terminal that performs the method of determining the evaluation result according to the embodiment of the present application. As shown in fig. 1, the computer terminal may include one or more processors 102 (only one is shown in fig. 1), which processor 102 may include, but is not limited to, a microprocessor (Microprocessor Unit, abbreviated MPU) or programmable logic device (Programmable logic device, abbreviated PLD) and a memory 104 configured to store data, and in one exemplary embodiment, a transmission device 106 configured to communicate with an input/output device 108.
The memory 104 may be configured to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to a method of determining an evaluation result in the embodiment of the present application, and the processor 102 executes various functional applications and data processing by executing the computer program stored in the memory 104, that is, implements the above-described method. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, which may be connected to the computer terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is arranged to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, simply referred to as NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module configured to communicate wirelessly with the internet.
In this embodiment, a method for determining an evaluation result is provided, and fig. 2 is a flowchart of a method for determining an evaluation result according to an embodiment of the present application, where the flowchart includes the following steps:
step S202, multi-dimensional business data corresponding to a target enterprise is obtained, wherein the multi-dimensional business data at least comprises internal business data of the target enterprise and external business data of the target enterprise;
step S204, determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index;
step S206, determining an evaluation result of the multidimensional service data based on the first liveness score and/or the second liveness score.
Through the steps, the multi-dimensional business data corresponding to the target enterprise is obtained, wherein the multi-dimensional business data at least comprises the internal business data of the target enterprise and the external business data of the target enterprise; determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; and determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score. The method and the device solve the problem that the activity of the small micro-enterprises cannot be accurately determined in the related technology, and further can accurately determine the activity of the small micro-enterprises.
Optionally, the first evaluation index may be understood as an evaluation index (i.e., a service type index, a service object index, a service time index) corresponding to a type of exchange, an exchange object, an exchange time, etc. of virtual resource exchange from an enterprise.
Alternatively, the second evaluation index may be understood as an evaluation index corresponding to public credit information, for example, public credit information such as industry, tax, judicial, credit, etc.
In an exemplary embodiment, in order to better understand how to obtain the multidimensional service data corresponding to the target enterprise in the step S202, the following steps are specifically proposed: responding to an evaluation instruction of a target object, and determining all enterprises to be evaluated from the evaluation instruction; determining enterprises to be evaluated, of which the enterprise scale is smaller than a preset scale, from all enterprises to be evaluated, and determining the enterprises to be evaluated, of which the enterprise scale is smaller than the preset scale, as the target enterprise; acquiring internal service data when the current service type of the target enterprise is internal service and external service data when the current service type of the target enterprise is external service, and determining the internal service data and the external service data as the multidimensional service data.
In an exemplary embodiment, the process of determining the second liveness score corresponding to the external service data according to the second evaluation index in the step S204 is further described with reference to the following technical scheme, and the specific steps include: acquiring a positive index parameter value of the external service data under the positive credit index and acquiring a negative index parameter value of the external service data under the negative credit index; determining a first sum between the positive index parameter value and the negative index parameter value; and under the condition that the first sum value is determined to belong to a preset range, determining the first sum value as a second liveness score corresponding to the external service data.
In an exemplary embodiment, a technical solution for obtaining a forward index parameter value of the external service data under the forward credit index is further provided, including the following steps: under the condition that different forward credit indexes exist, acquiring first index parameter values of the external service data under each forward credit index to obtain a plurality of first index parameter values; wherein the different forward credit index comprises at least one of: whether the target enterprise has an enterprise website, whether the target enterprise has a tax payment record, whether the target enterprise has a branch office, whether the target enterprise has an external investment enterprise, whether the target enterprise has an enterprise information change record, and whether the target enterprise has a migration application record; a second sum value between the plurality of first index parameter values is determined as the forward index parameter value.
In an exemplary embodiment, there is further provided an implementation process for obtaining a negative indicator parameter value of external service data under the negative credit indicator, which specifically includes: under the condition that different negative credit indexes exist, acquiring second index parameter values of the external service data under each negative credit index to obtain a plurality of second index parameter values; wherein the different negative credit indicators comprise at least one of: whether the target enterprise has administrative punishment records, whether the target enterprise has illegal records, and whether the target enterprise has enterprise personnel change records; a third sum value between the plurality of second index parameter values is determined as the negative index parameter value.
In an exemplary embodiment, the process of determining the first liveness score corresponding to the internal service data according to the first evaluation index in the step S204 includes the following steps: determining other enterprises which do not exchange virtual resources with the target enterprise, and acquiring first internal index parameter values of internal service data of the other enterprises under the first evaluation indexes; wherein the first internal index parameter value includes at least one of: a first service object index parameter value corresponding to the service object index, a first service type index parameter value corresponding to the service type index, and a first service time index parameter value corresponding to the service time index; acquiring a second internal index parameter value of the internal business data of the target enterprise under the first evaluation index; wherein the second internal index parameter value comprises at least one of: a second service object index parameter value corresponding to the service object index, a second service type index parameter value corresponding to the service type index, and a second service time index parameter value corresponding to the service time index; determining a first sum of squares between the first traffic object indicator parameter value and the second internal indicator parameter value, a second sum of squares between the first traffic type indicator parameter value and the second traffic type indicator parameter value, and a third sum of squares between the first traffic time indicator parameter value and the second traffic time indicator parameter value; and determining a weighted sum value between the first square sum, the second square sum and the third square sum as the first liveness score.
Alternatively, in one exemplary embodiment, a weighted sum value between the first sum of squares, the second sum of squares, and the third sum of squares may be determined, and a square root of the weighted sum value is determined as the first liveness score.
In an exemplary embodiment, for the process of determining the evaluation result of the multi-dimensional service data based on the first liveness score and/or the second liveness score in the step S206, the method specifically includes the following implementation steps: under the condition that the second liveness score is determined to belong to a preset score range, acquiring a weighted sum value between the first liveness score and the second liveness score; if the weighted sum value is determined to be larger than a preset threshold value, determining that the target enterprise is an active enterprise; if the weighted sum value is smaller than a preset threshold value, determining that the target enterprise is an inactive enterprise; and/or determining that the target enterprise is an inactive enterprise under the condition that the second liveness score is determined not to belong to a preset score range.
It will be apparent that the embodiments described above are only some, but not all, of the embodiments of the present application. In order to better understand the determination method of the evaluation result, the following description will explain the above process with reference to the embodiments, but is not intended to limit the technical solutions of the embodiments of the present application, specifically:
In an alternative embodiment, the implementation process of determining the second liveness score corresponding to the external service data according to the second evaluation index is further described in the following.
The forward index parameter value indicates a positive value of a parameter value when a forward behavior occurs in the process of enterprise production and management. The higher the forward index parameter value, the greater the degree to which the forward behavior corresponding to the forward index parameter value positively affects the profitability of the enterprise.
The negative index parameter value represents the parameter value when negative behaviors are generated in the production and operation process of the enterprise, and is a negative number. The higher the negative index parameter value, the greater the degree to which the negative behavior corresponding to the negative index parameter value has a negative impact on the enterprise's profitability.
In this embodiment, a positive index parameter value of the external service data under the positive credit index is obtained, a negative index parameter value of the external service data under the negative credit index is obtained, and a second liveness score of the external service data is determined according to a sum value of a plurality of first index parameter values of the external service data under different positive credit indexes and second index parameter values of the external service data under different negative credit indexes.
Optionally, the forward credit index corresponding to the external service data is specifically shown in table 1 below,
table 1 forward evaluation index table
The negative credit index corresponding to the external service data is shown in the following table 2:
TABLE 2 negative evaluation index Table
The total liveness score (i.e. the second liveness score) is obtained by adding the positive index parameter value and the negative index parameter value, and the higher the total liveness score is, the better the production and operation conditions of the enterprise are.
When the positive index parameter value and the negative index parameter value are both 0, the enterprise production and operation activities are not active.
In the above embodiment, the index parameter value corresponding to the positive evaluation index and the parameter value corresponding to the negative evaluation index may be formulated by an expert in the industry according to different variable types in combination with self-practice experience.
Optionally, in an embodiment, the "euclidean distance" between the "origin" and the "coordinate point" may be determined as the liveness score of the remaining small micro-enterprises, assuming that the small micro-enterprise with the lowest liveness score (i.e. the target enterprise) is the "origin" of the multidimensional space coordinate system, and the remaining small micro-enterprises are set as the "coordinate points" of the multidimensional space coordinate system based on the liveness algorithm of the euclidean distance.
Alternatively, in one embodiment, outlier processing may be performed on the internal traffic data. That is, when the second internal index parameter value is greater than the preset threshold value, the abnormal value is deleted. Wherein, for example, the 98-bit numerical value in the second internal index parameter value may be set as the preset threshold.
Alternatively, in one embodiment, the internal traffic data may be normalized.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk), comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the embodiments of the present application.
The embodiment also provides a device for determining an evaluation result, which is used for implementing the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware, are also possible and contemplated.
Fig. 3 is a block diagram (a) of a configuration of an evaluation result determination apparatus according to an embodiment of the present application, the apparatus including:
the data acquisition module 302 is configured to acquire multi-dimensional service data corresponding to a target enterprise, where the multi-dimensional service data at least includes internal service data of the target enterprise and external service data of the target enterprise;
the score determining module 304 is configured to determine a first liveness score corresponding to the internal service data according to a first evaluation index, and determine a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index;
the result determining module 306 is configured to determine an evaluation result of the multi-dimensional service data based on the first liveness score and/or the second liveness score.
Through the determining device of the evaluation result in the embodiment of the present application, multidimensional service data corresponding to a target enterprise may be obtained, where the multidimensional service data at least includes internal service data of the target enterprise and external service data of the target enterprise; determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; and determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score. The method solves the problem that the activity of the small micro-enterprises cannot be accurately determined in the related technology, and further can accurately determine the activity of the small micro-enterprises.
In an exemplary embodiment, the data acquisition module 302 is further configured to: responding to an evaluation instruction of a target object, and determining all enterprises to be evaluated from the evaluation instruction; determining enterprises to be evaluated, of which the enterprise scale is smaller than a preset scale, from all enterprises to be evaluated, and determining the enterprises to be evaluated, of which the enterprise scale is smaller than the preset scale, as the target enterprise; acquiring internal service data when the current service type of the target enterprise is internal service and external service data when the current service type of the target enterprise is external service, and determining the internal service data and the external service data as the multidimensional service data.
In an exemplary embodiment, the score determining module 304 is further configured to further implement the following steps: acquiring a positive index parameter value of the external service data under the positive credit index and acquiring a negative index parameter value of the external service data under the negative credit index; determining a first sum between the positive index parameter value and the negative index parameter value; and under the condition that the first sum value is determined to belong to a preset range, determining the first sum value as a second liveness score corresponding to the external service data.
In an exemplary embodiment, the score determination module 304 is further configured to perform the following steps: under the condition that different forward credit indexes exist, acquiring first index parameter values of the external service data under each forward credit index to obtain a plurality of first index parameter values; wherein the different forward credit index comprises at least one of: whether the target enterprise has an enterprise website, whether the target enterprise has a tax payment record, whether the target enterprise has a branch office, whether the target enterprise has an external investment enterprise, whether the target enterprise has an enterprise information change record, and whether the target enterprise has a migration application record; a second sum value between the plurality of first index parameter values is determined as the forward index parameter value.
In an exemplary embodiment, the score determination module 304 is further configured to: under the condition that different negative credit indexes exist, acquiring second index parameter values of the external service data under each negative credit index to obtain a plurality of second index parameter values; wherein the different negative credit indicators comprise at least one of: whether the target enterprise has administrative punishment records, whether the target enterprise has illegal records, and whether the target enterprise has enterprise personnel change records; a third sum value between the plurality of second index parameter values is determined as the negative index parameter value.
In an exemplary embodiment, the score determination module 304 is further configured to: determining other enterprises which do not exchange virtual resources with the target enterprise, and acquiring first internal index parameter values of internal service data of the other enterprises under the first evaluation indexes; wherein the first internal index parameter value includes at least one of: a first service object index parameter value corresponding to the service object index, a first service type index parameter value corresponding to the service type index, and a first service time index parameter value corresponding to the service time index; acquiring a second internal index parameter value of the internal business data of the target enterprise under the first evaluation index; wherein the second internal index parameter value comprises at least one of: a second service object index parameter value corresponding to the service object index, a second service type index parameter value corresponding to the service type index, and a second service time index parameter value corresponding to the service time index; determining a first sum of squares between the first traffic object indicator parameter value and the second internal indicator parameter value, a second sum of squares between the first traffic type indicator parameter value and the second traffic type indicator parameter value, and a third sum of squares between the first traffic time indicator parameter value and the second traffic time indicator parameter value; and determining a weighted sum value between the first square sum, the second square sum and the third square sum as the first liveness score.
In an exemplary embodiment, fig. 4 is a block diagram (two) of a structure of an apparatus for determining an evaluation result according to an embodiment of the present application, and as shown in fig. 4, the above result determining module 306 further includes:
an obtaining unit 401, configured to obtain a weighted sum value between the first liveness score and the second liveness score when it is determined that the second liveness score belongs to a preset score range;
a first determining unit 402, configured to determine that the target enterprise is an active enterprise if it is determined that the weighted sum value is greater than a preset threshold;
a second determining unit 403, configured to determine that the target enterprise is an inactive enterprise if it is determined that the weighted sum value is less than a preset threshold;
and/or, a third determining unit 404, configured to determine that the target enterprise is an inactive enterprise if it is determined that the second liveness score does not belong to the preset score range.
The embodiment of the present application also provides a storage medium including a stored program, where any one of the embodiments described above is executed when the program is executed.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
S1, acquiring multi-dimensional business data corresponding to a target enterprise, wherein the multi-dimensional business data at least comprises internal business data of the target enterprise and external business data of the target enterprise;
s2, determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index;
s3, determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score.
In one exemplary embodiment, the computer readable storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
Specific examples in this embodiment may refer to the examples described in the foregoing embodiments and the exemplary implementation, and this embodiment is not described herein.
Embodiments of the present application also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, acquiring multi-dimensional business data corresponding to a target enterprise, wherein the multi-dimensional business data at least comprises internal business data of the target enterprise and external business data of the target enterprise;
s2, determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index;
s3, determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score.
In an exemplary embodiment, the electronic apparatus may further include a transmission device connected to the processor, and an input/output device connected to the processor.
Specific examples in this embodiment may refer to the examples described in the foregoing embodiments and the exemplary implementation, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may be implemented in program code executable by computing devices, so that they may be stored in a storage device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps of them may be fabricated into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method for determining an evaluation result, comprising:
acquiring multi-dimensional business data corresponding to a target enterprise, wherein the multi-dimensional business data at least comprises internal business data of the target enterprise and external business data of the target enterprise;
determining a first liveness score corresponding to the internal service data according to a first evaluation index, and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index;
and determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score.
2. The method for determining an evaluation result according to claim 1, wherein obtaining multidimensional service data corresponding to a target enterprise comprises:
responding to an evaluation instruction of a target object, and determining all enterprises to be evaluated from the evaluation instruction;
determining enterprises to be evaluated, of which the enterprise scale is smaller than a preset scale, from all enterprises to be evaluated, and determining the enterprises to be evaluated, of which the enterprise scale is smaller than the preset scale, as the target enterprise;
acquiring internal service data when the current service type of the target enterprise is internal service and external service data when the current service type of the target enterprise is external service, and determining the internal service data and the external service data as the multidimensional service data.
3. The method for determining an evaluation result according to claim 1, wherein determining a second liveness score corresponding to the external service data according to a second evaluation index comprises:
acquiring a positive index parameter value of the external service data under the positive credit index and acquiring a negative index parameter value of the external service data under the negative credit index;
Determining a first sum between the positive index parameter value and the negative index parameter value;
and under the condition that the first sum value is determined to belong to a preset range, determining the first sum value as a second liveness score corresponding to the external service data.
4. The method for determining an evaluation result according to claim 3, wherein obtaining the forward index parameter value of the external service data under the forward credit index comprises:
under the condition that different forward credit indexes exist, acquiring first index parameter values of the external service data under each forward credit index to obtain a plurality of first index parameter values;
wherein the different forward credit index comprises at least one of: whether the target enterprise has an enterprise website, whether the target enterprise has a tax payment record, whether the target enterprise has a branch office, whether the target enterprise has an external investment enterprise, whether the target enterprise has an enterprise information change record, and whether the target enterprise has a migration application record;
a second sum value between the plurality of first index parameter values is determined as the forward index parameter value.
5. The method for determining an evaluation result according to claim 3, wherein obtaining a negative index parameter value of the external service data under the negative credit index comprises:
under the condition that different negative credit indexes exist, acquiring second index parameter values of the external service data under each negative credit index to obtain a plurality of second index parameter values;
wherein the different negative credit indicators comprise at least one of: whether the target enterprise has administrative punishment records, whether the target enterprise has illegal records, and whether the target enterprise has enterprise personnel change records;
a third sum value between the plurality of second index parameter values is determined as the negative index parameter value.
6. The method for determining an evaluation result according to claim 1, wherein determining a first liveness score corresponding to the internal service data according to a first evaluation index comprises:
determining other enterprises which do not exchange virtual resources with the target enterprise, and acquiring first internal index parameter values of internal service data of the other enterprises under the first evaluation indexes; wherein the first internal index parameter value includes at least one of: a first service object index parameter value corresponding to the service object index, a first service type index parameter value corresponding to the service type index, and a first service time index parameter value corresponding to the service time index;
Acquiring a second internal index parameter value of the internal business data of the target enterprise under the first evaluation index; wherein the second internal index parameter value comprises at least one of: a second service object index parameter value corresponding to the service object index, a second service type index parameter value corresponding to the service type index, and a second service time index parameter value corresponding to the service time index;
determining a first sum of squares between the first traffic object indicator parameter value and the second internal indicator parameter value, a second sum of squares between the first traffic type indicator parameter value and the second traffic type indicator parameter value, and a third sum of squares between the first traffic time indicator parameter value and the second traffic time indicator parameter value;
and determining a weighted sum value between the first square sum, the second square sum and the third square sum as the first liveness score.
7. The method for determining an evaluation result according to claim 1, wherein determining an evaluation result of the multi-dimensional business data based on the first liveness score and/or the second liveness score comprises:
Under the condition that the second liveness score is determined to belong to a preset score range, acquiring a weighted sum value between the first liveness score and the second liveness score;
if the weighted sum value is determined to be larger than a preset threshold value, determining that the target enterprise is an active enterprise;
if the weighted sum value is smaller than a preset threshold value, determining that the target enterprise is an inactive enterprise;
and/or determining that the target enterprise is an inactive enterprise under the condition that the second liveness score is determined not to belong to a preset score range.
8. A determination device of an evaluation result, characterized by comprising:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring multi-dimensional service data corresponding to a target enterprise, and the multi-dimensional service data at least comprises internal service data of the target enterprise and external service data of the target enterprise;
the score determining module is used for determining a first liveness score corresponding to the internal service data according to a first evaluation index and determining a second liveness score corresponding to the external service data according to a second evaluation index; wherein the first evaluation index at least comprises one of the following: the second evaluation index at least comprises one of the following: positive credit index, negative credit index;
And the result determining module is used for determining an evaluation result of the multi-dimensional service data based on the first liveness score and/or the second liveness score.
9. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored program, wherein the program when run performs the method of any of the preceding claims 1 to 7.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of the claims 1 to 7 by means of the computer program.
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