CN117078324A - Data processing method, device, equipment and medium for provider rating - Google Patents
Data processing method, device, equipment and medium for provider rating Download PDFInfo
- Publication number
- CN117078324A CN117078324A CN202311342838.4A CN202311342838A CN117078324A CN 117078324 A CN117078324 A CN 117078324A CN 202311342838 A CN202311342838 A CN 202311342838A CN 117078324 A CN117078324 A CN 117078324A
- Authority
- CN
- China
- Prior art keywords
- data
- rating
- provider
- rating data
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title claims abstract description 33
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 48
- 238000012423 maintenance Methods 0.000 claims abstract description 36
- 238000011156 evaluation Methods 0.000 claims abstract description 17
- 238000000034 method Methods 0.000 claims abstract description 16
- 238000012545 processing Methods 0.000 claims description 21
- 238000004891 communication Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 13
- 230000008859 change Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 abstract description 10
- 230000006870 function Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 238000010606 normalization Methods 0.000 description 6
- 238000012790 confirmation Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 239000006185 dispersion Substances 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000012356 Product development Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 235000019800 disodium phosphate Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0282—Rating or review of business operators or products
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/018—Certifying business or products
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Human Resources & Organizations (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a data processing method, a device, equipment and a medium for provider rating, wherein the method comprises the following steps: acquiring the rating data of the provider matched with the provider rating maintenance request; calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type; calculating to obtain target rating data according to preset weights of each data type and the calculated intermediate rating data; and determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data. According to the method, corresponding intermediate rating data are calculated according to the obtained provider rating data, and then target rating data are obtained through calculation, so that automatic calculation and grading of the evaluation grades of the providers are achieved, and the management efficiency of the providers is improved.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing method, apparatus, device, and medium for vendor rating.
Background
The supply chain is mainly composed of suppliers, manufacturers (or manufacturers) and sellers, which are connected closely, wherein the suppliers are key to the whole supply chain, and the selection and evaluation of the suppliers are the basis for the effective operation of the supply chain. Firstly, because of scarce resources, the supply and demand parties need to communicate better to improve the utilization efficiency of the resources; second, many businesses invite their suppliers to participate in their early product development to make them better able to bring value to customers themselves. In order to achieve low cost, high quality, and fast response, the business reconfiguration of the enterprise must include vendor selection, which is critical to improving the core competitiveness of the enterprise. However, small and medium enterprises lack a complete automatic scoring and selection system for suppliers under the conditions of low informatization level and limited personnel capacity.
Disclosure of Invention
The embodiment of the invention provides a data processing method, device, equipment and medium for provider rating, which aim to solve the problem that automatic scoring processing cannot be effectively performed on provider rating in the prior art.
In a first aspect, an embodiment of the present invention provides a data processing method for rating suppliers, where the method is applied to a management server, and the method includes:
if a provider rating maintenance request sent by a user is received, obtaining rating data of a provider matched with the provider rating maintenance request, wherein the rating data at least comprises 2 data types;
calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type;
calculating to obtain target rating data according to preset weights of each data type and the calculated intermediate rating data;
and determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data.
In a second aspect, an embodiment of the present invention further provides a data processing apparatus for vendor rating, where the apparatus is configured in a management server, and the apparatus is configured to perform the data processing method for vendor rating according to the first aspect, and the apparatus includes:
a request receiving unit, configured to obtain rating data of a provider matching with a provider rating maintenance request if the provider rating maintenance request sent by a user is received, where the rating data at least includes 2 data types;
the intermediate computing unit is used for computing intermediate rating data corresponding to each data type according to a preset algorithm and the rating data of each data type;
the target calculating unit is used for calculating target rating data according to preset weights of each data type and the calculated intermediate rating data;
and the processing unit is used for determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data.
In a third aspect, an embodiment of the present invention further provides a computer device, where the device includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and a processor, configured to implement the steps of the data processing method for vendor rating according to the first aspect when executing the program stored in the memory.
In a fourth aspect, embodiments of the present invention also provide a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the data processing method for vendor ratings as described in the first aspect above.
The embodiment of the invention provides a data processing method, a device, equipment and a medium for provider rating, wherein the method comprises the following steps: if a provider rating maintenance request sent by a user is received, obtaining rating data of a provider matched with the provider rating maintenance request, wherein the rating data at least comprises 2 data types; calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type; calculating to obtain target rating data according to preset weights of each data type and the calculated intermediate rating data; and determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data. According to the data processing method for the supplier rating, corresponding intermediate rating data is calculated according to the obtained supplier rating data, and then the target rating data is obtained through calculation, so that automatic calculation and grading of the evaluation grade of the supplier are realized, and the efficiency of supplier management is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for data processing for vendor ratings provided by an embodiment of the present invention;
FIG. 2 is a schematic diagram of an application scenario of a data processing method for vendor rating according to an embodiment of the present invention;
FIG. 3 is a schematic block diagram of a data processing apparatus for vendor ratings provided in an embodiment of the present invention;
fig. 4 is a schematic block diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1 and 2, as shown in the drawings, an embodiment of the present invention provides a data processing method for vendor rating, which is applied to a management server 10, a user enters a maintenance interface 21 for vendor rating through a vendor management client 20, and the management server 10 can update vendor rating data to the maintenance interface 21 for the user to add, modify and delete related information. By the data processing method for the supplier rating, the management server can realize multi-dimensional automatic rating of the suppliers, and provides more comprehensive and effective supplier management basis for users. For example, a vendor management system may be designed, according to which a user may perform unified management on vendors, i.e., initiate a request for a vendor's provisioning ratings, and present relevant ratings data updates to the user for user selection operations via the maintenance interface of the client 20. As shown in FIG. 1, the method includes steps S110 to S140.
Step S110, if a provider rating maintenance request sent by a user is received, obtaining rating data of a provider matched with the provider rating maintenance request, wherein the rating data at least comprises 2 data types.
In this embodiment, if the management server receives the vendor rating maintenance request sent by the user, the vendor rating maintenance request may be parsed to determine a target vendor, and obtain relevant rating data of the target vendor. The rating data of the suppliers can be classified generally, and in order to realize more accurate control of the ratings of the suppliers, the types of the rating data at least comprise two types, so that comprehensive evaluation management of the suppliers is realized according to the rating data of different types.
In a specific embodiment, the step S110 of obtaining the rating data of the provider matching the provider rating maintenance request includes the following sub-steps: analyzing the vendor rating maintenance request to determine whether to update the corresponding vendor's rating data; if yes, retrieving the rating data of the currently confirmed provider.
After analyzing the provider rating maintenance request, the management server can determine whether to update the corresponding provider rating data according to the requirement of the user, if the user sends an update request to the management server, the currently confirmed provider rating data is dropped, and if the user selects not to update, the non-updated provider rating data is obtained for rating.
In a specific embodiment, the step of retrieving the rating data of the currently confirmed provider includes the sub-steps of: if a new information request of a user is received, the corresponding new information is taken as the rating data of the currently confirmed provider according to the new information request; or (b)
If a user's change information request is received, corresponding changed information is used as the currently confirmed rating data of the provider according to the change information request; or (b)
And if a deleting information request of the user is received, deleting corresponding information from the provider rating data according to the deleting information request so as to obtain the currently confirmed provider rating data.
And determining that when a new information request of the user is received according to the supplier rating maintenance request, at this time, the corresponding new information can be used as currently confirmed rating data of the supplier together according to the new information request, so as to realize the new updating of the rating data of the supplier. And if the user's request for changing the information is received, the related information is modified, so that the corresponding changed information is used as the rating data of the currently confirmed provider. If the request for deleting the information of the user is received, deleting the corresponding information from the provider rating data, and taking the rest information as the currently confirmed provider rating data.
Step S120, calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type;
in this embodiment, the management server may calculate the corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type. The preset algorithm may be a dispersion normalization, which is also called Min-max normalization (Min-Max Normalization), which is a linear transformation of the original data, and the result value is mapped between (0-1), and the conversion function is as follows:
where max is the maximum value of the sample data, and min is the minimum value of the sample data.
In a specific embodiment, the data type of the rating data includes at least a payment days in advance and an application amount, and the step S120 includes the sub-steps of: calculating first intermediate rating data corresponding to the early payment days according to a preset deviation standardization algorithm; and calculating second intermediate rating data corresponding to the application amount according to a preset deviation standardization algorithm.
The data type of the rating data may include payment days in advance, an application amount, and the like. At this time, the first intermediate rating data corresponding to the payment days in advance can be calculated according to a preset deviation standardization algorithm, the second intermediate rating data corresponding to the application amount can be calculated according to the preset deviation standardization algorithm, and corresponding processing calculation can be performed according to the first intermediate rating data and the second intermediate rating data.
In a specific embodiment, the data type of the rating data may further include an application date, a bid discount rate, and a interest amount, and the step S120 further includes the sub-steps of:
calculating third intermediate rating data corresponding to the application date according to a preset deviation standardization algorithm;
calculating fourth intermediate rating data corresponding to the bid discount rate according to a preset deviation standardization algorithm;
and calculating fifth intermediate rating data corresponding to the interest sum according to a preset deviation standardization algorithm.
The data types of the rating data may include an application date, a bid discount rate, a total interest amount, and the like. At this time, the third intermediate rating data corresponding to the application date can be calculated according to a preset deviation standardization algorithm, the fourth intermediate rating data corresponding to the bid discount rate can be calculated according to a preset deviation standardization algorithm, and the fifth intermediate rating data corresponding to the interest total can be calculated according to a preset deviation standardization algorithm.
In a specific embodiment, the data type of the rating data further includes a custom data type, and the step S120 further includes the sub-steps of:
and calculating sixth intermediate rating data corresponding to the custom data type according to a preset custom algorithm.
In summary, if the data types of the rating data include payment days in advance, application amount, application date, bid discount rate, interest total, custom data types, and the like, for each data type, corresponding first intermediate rating data, second intermediate rating data, third intermediate rating data, fourth intermediate rating data, fifth intermediate rating data, sixth rating data, and the like can be calculated according to a preset self-response algorithm. The multi-dimensional management of the suppliers can be realized through the result of integrating and calculating the first intermediate rating data to the sixth intermediate rating data.
Step S130, calculating target rating data according to preset weights of each data type and the calculated intermediate rating data.
In this embodiment, the management server may preset a corresponding weight for each data type according to an actual situation, and assign the weight to the intermediate rating data of each data type, so as to calculate and obtain a corresponding target rating data. Wherein the weight value addition for all data types is equal to 1.
In a specific embodiment, the weight occupied by the data types such as the payment days in advance, the application amount, the application date, the bid discount rate, the custom data type and the like is 15%, and the weight occupied by the interest sum is 25%. Of course, the specific weight allocation may be adjusted and changed according to the needs of the user, which is not limited in this embodiment.
Step S140, determining an evaluation level of the provider according to the preset rating interval and the calculated target rating data.
In this embodiment, the management server further sets a rating interval in advance, and matches the calculated target rating data with a corresponding rating interval, thereby determining the rating level of the provider. For example, a vendor rating of 90 or greater is assigned a, a vendor rating of less than 90 and 80 or greater is assigned B, a vendor rating of less than 80 and 70 or greater is assigned C, a vendor rating of less than 70 and 60 or greater is assigned D, and a vendor rating of less than 60 is assigned E. If the target rating data is 95 points, the provider is a class A provider, and is an excellent provider. If the target rating data is 82 points, it indicates that the provider is a class B provider, and so on.
The method can realize the processing of the related data of the suppliers, automatically realize the rating management of the suppliers and improve the management efficiency; meanwhile, the variety of the rating data of the suppliers can be adjusted according to the requirements of the users, and the applicability is improved.
The data processing method, device, equipment and medium for provider rating provided by the embodiment of the invention comprise the following steps: if a provider rating maintenance request sent by a user is received, obtaining rating data of a provider matched with the provider rating maintenance request, wherein the rating data at least comprises 2 data types; calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type; calculating to obtain target rating data according to preset weights of each data type and the calculated intermediate rating data; and determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data. According to the data processing method for the supplier rating, corresponding intermediate rating data is calculated according to the obtained supplier rating data, and then the target rating data is obtained through calculation, so that automatic calculation and grading of the evaluation grade of the supplier are realized, and the efficiency of supplier management is improved.
The embodiment of the invention also provides a data processing device for vendor rating, which is configured in the charging management terminal and is used for executing any embodiment of the data processing method for vendor rating. In particular, referring to FIG. 3, FIG. 3 is a schematic block diagram of a data processing apparatus for vendor ratings according to an embodiment of the present invention.
As shown in fig. 3, the data processing apparatus 100 for vendor ratings includes a request receiving unit 110, an intermediate calculating unit 120, a target calculating unit 130, and a processing unit 140.
The request receiving unit 110 is configured to obtain rating data of a provider matching with a provider rating maintenance request if the provider rating maintenance request sent by a user is received, where the rating data includes at least 2 data types.
In this embodiment, if the management server receives the vendor rating maintenance request sent by the user, the vendor rating maintenance request may be parsed to determine a target vendor, and obtain relevant rating data of the target vendor. The rating data of the suppliers can be classified generally, and in order to realize more accurate control of the ratings of the suppliers, the types of the rating data at least comprise two types, so that comprehensive evaluation management of the suppliers is realized according to the rating data of different types.
In a specific embodiment, the request receiving unit 110 obtains the rating data of the provider matching the provider rating maintenance request, and includes a subunit: a request analysis unit, configured to analyze the vendor rating maintenance request to determine whether to update the rating data of the corresponding vendor; and the data calling unit is used for calling the rating data of the currently confirmed provider if the data is yes.
After analyzing the provider rating maintenance request, the management server can determine whether to update the corresponding provider rating data according to the requirement of the user, if the user sends an update request to the management server, the currently confirmed provider rating data is dropped, and if the user selects not to update, the non-updated provider rating data is obtained for rating.
In a specific embodiment, the data retrieving unit includes a subunit: the first confirmation unit is used for taking corresponding newly-added information as the rating data of the currently confirmed provider according to the newly-added information request if the newly-added information request of the user is received;
the second confirmation unit is used for taking the corresponding changed information as the rating data of the currently confirmed provider according to the change information request if the change information request of the user is received;
and the third confirmation unit is used for deleting corresponding information from the provider rating data according to the deletion information request if the deletion information request of the user is received, so as to obtain the currently confirmed provider rating data.
And determining that when a new information request of the user is received according to the supplier rating maintenance request, at this time, the corresponding new information can be used as currently confirmed rating data of the supplier together according to the new information request, so as to realize the new updating of the rating data of the supplier. And if the user's request for changing the information is received, the related information is modified, so that the corresponding changed information is used as the rating data of the currently confirmed provider. If the request for deleting the information of the user is received, deleting the corresponding information from the provider rating data, and taking the rest information as the currently confirmed provider rating data.
The intermediate computing unit 120 is configured to compute intermediate rating data corresponding to each data type according to a preset algorithm and the rating data of each data type.
In this embodiment, the management server may calculate the corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type. The preset algorithm may be a dispersion normalization, which is also called Min-max normalization (Min-Max Normalization), which is a linear transformation of the original data, and the result value is mapped between (0-1), and the conversion function is as follows:
where max is the maximum value of the sample data, and min is the minimum value of the sample data.
In a specific embodiment, the data type of the rating data includes at least a payment days in advance and an application amount, and the intermediate computing unit 120 includes the following sub-units: the first calculating unit is used for calculating first intermediate rating data corresponding to the early payment days according to a preset deviation standardization algorithm; the second calculating unit is used for calculating second intermediate rating data corresponding to the application amount according to a preset deviation standardization algorithm.
The data type of the rating data may include payment days in advance, an application amount, and the like. At this time, the first intermediate rating data corresponding to the payment days in advance can be calculated according to a preset deviation standardization algorithm, the second intermediate rating data corresponding to the application amount can be calculated according to the preset deviation standardization algorithm, and corresponding processing calculation can be performed according to the first intermediate rating data and the second intermediate rating data.
In a specific embodiment, the data types of the rating data may further include an application date, a bid discount rate, and a interest total, and the intermediate computing unit 120 further includes the following sub-units: the third computing unit is used for computing third intermediate rating data corresponding to the application date according to a preset deviation standardization algorithm; the fourth calculating unit is used for calculating fourth intermediate rating data corresponding to the bid discount rate according to a preset deviation standardization algorithm; and the fifth calculating unit is used for calculating fifth intermediate rating data corresponding to the interest sum according to a preset deviation standardization algorithm.
The data types of the rating data may include an application date, a bid discount rate, a total interest amount, and the like. At this time, the third intermediate rating data corresponding to the application date can be calculated according to a preset deviation standardization algorithm, the fourth intermediate rating data corresponding to the bid discount rate can be calculated according to a preset deviation standardization algorithm, and the fifth intermediate rating data corresponding to the interest total can be calculated according to a preset deviation standardization algorithm.
In a specific embodiment, the data type of the rating data further includes a custom data type, and the intermediate computing unit 120 further includes a sixth computing unit, configured to compute sixth intermediate rating data corresponding to the custom data type according to a preset custom algorithm.
In summary, if the data types of the rating data include payment days in advance, application amount, application date, bid discount rate, interest total, custom data types, and the like, for each data type, corresponding first intermediate rating data, second intermediate rating data, third intermediate rating data, fourth intermediate rating data, fifth intermediate rating data, sixth rating data, and the like can be calculated according to a preset self-response algorithm. The multi-dimensional management of the suppliers can be realized through the result of integrating and calculating the first intermediate rating data to the sixth intermediate rating data.
The target calculating unit 130 is configured to calculate target rating data according to the preset weight of each data type and the calculated intermediate rating data.
In this embodiment, the management server may preset a corresponding weight for each data type according to an actual situation, and assign the weight to the intermediate rating data of each data type, so as to calculate and obtain a corresponding target rating data. Wherein the weight value addition for all data types is equal to 1.
In a specific embodiment, the weight occupied by the data types such as the payment days in advance, the application amount, the application date, the bid discount rate, the custom data type and the like is 15%, and the weight occupied by the interest sum is 25%. Of course, the specific weight allocation may be adjusted and changed according to the needs of the user, which is not limited in this embodiment.
And the processing unit 140 is configured to determine an evaluation level of the provider according to a preset rating interval and the calculated target rating data.
In this embodiment, the management server further sets a rating interval in advance, and matches the calculated target rating data with a corresponding rating interval, thereby determining the rating level of the provider. For example, a vendor rating of 90 or greater is assigned a, a vendor rating of less than 90 and 80 or greater is assigned B, a vendor rating of less than 80 and 70 or greater is assigned C, a vendor rating of less than 70 and 60 or greater is assigned D, and a vendor rating of less than 60 is assigned E. If the target rating data is 95 points, the provider is a class A provider, and is an excellent provider. If the target rating data is 82 points, it indicates that the provider is a class B provider, and so on.
The device can process related data of the suppliers, automatically realize rating management of the suppliers and improve management efficiency; meanwhile, the variety of the rating data of the suppliers can be adjusted according to the requirements of the users, and the applicability is improved.
The data processing device for provider rating provided by the embodiment of the invention applies the data processing method for provider rating, and if a provider rating maintenance request sent by a user is received, the rating data of the provider matched with the provider rating maintenance request is obtained, wherein the rating data at least comprises 2 data types; calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type; calculating to obtain target rating data according to preset weights of each data type and the calculated intermediate rating data; and determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data. According to the data processing method for the supplier rating, corresponding intermediate rating data is calculated according to the obtained supplier rating data, and then the target rating data is obtained through calculation, so that automatic calculation and grading of the evaluation grade of the supplier are realized, and the efficiency of supplier management is improved.
The data processing apparatus for vendor ratings described above may be implemented in the form of a computer program which may be run on a computer device as shown in fig. 4.
Referring to fig. 4, fig. 4 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device may be a user terminal or a management server for performing a data processing method for vendor ratings.
Referring to fig. 4, the computer device 500 includes a processor 502, a memory, and a network interface 505, which are connected by a communication bus 501, wherein the memory may include a storage medium 503 and an internal memory 504.
The storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, may cause the processor 502 to perform a data processing method for vendor ratings, wherein the storage medium 503 may be a volatile storage medium or a non-volatile storage medium.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the execution of a computer program 5032 in the storage medium 503, which computer program 5032, when executed by the processor 502, may cause the processor 502 to perform a data processing method for vendor ratings.
The network interface 505 is used for network communication, such as providing for transmission of data information, etc. It will be appreciated by those skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting of the computer device 500 to which the present inventive arrangements may be implemented, and that a particular computer device 500 may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The processor 502 is configured to execute a computer program 5032 stored in a memory to implement the corresponding functions in the data processing method for vendor rating.
Those skilled in the art will appreciate that the embodiment of the computer device shown in fig. 4 is not limiting of the specific construction of the computer device, and in other embodiments, the computer device may include more or less components than those shown, or certain components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may include only a memory and a processor, and in such embodiments, the structure and function of the memory and the processor are consistent with the embodiment shown in fig. 4, and will not be described again.
It should be appreciated that in an embodiment of the invention, the processor 502 may be a central processing unit (Central Processing Unit, CPU), the processor 502 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a volatile or nonvolatile computer readable storage medium. The computer readable storage medium stores a computer program which when executed by a processor implements the steps involved in the data processing method for vendor ratings described above.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus, device and unit described above may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein. Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the units is merely a logical function division, there may be another division manner in actual implementation, or units having the same function may be integrated into one unit, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or part of what contributes to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a computer-readable storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned computer-readable storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. A data processing method for vendor ratings, the method being applied to a management server, the method comprising:
if a provider rating maintenance request sent by a user is received, obtaining rating data of a provider matched with the provider rating maintenance request, wherein the rating data at least comprises 2 data types;
calculating corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type;
calculating to obtain target rating data according to preset weights of each data type and the calculated intermediate rating data;
and determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data.
2. The data processing method for provider rating according to claim 1, wherein the acquiring the rating data of the provider matching the provider rating maintenance request includes:
analyzing the vendor rating maintenance request to determine whether to update the corresponding vendor's rating data;
if yes, retrieving the rating data of the currently confirmed provider.
3. The data processing method for vendor ratings according to claim 2, wherein said retrieving currently validated vendor ratings data includes:
if a new information request of a user is received, the corresponding new information is taken as the rating data of the currently confirmed provider according to the new information request; or (b)
If a user's change information request is received, corresponding changed information is used as the currently confirmed rating data of the provider according to the change information request; or (b)
And if a deleting information request of the user is received, deleting corresponding information from the provider rating data according to the deleting information request so as to obtain the currently confirmed provider rating data.
4. The data processing method for rating suppliers according to claim 1, wherein the data types of the rating data at least include a payment number in advance and an application amount, the calculating the corresponding intermediate rating data of each data type according to a preset algorithm and the rating data of each data type includes:
calculating first intermediate rating data corresponding to the early payment days according to a preset deviation standardization algorithm;
and calculating second intermediate rating data corresponding to the application amount according to a preset deviation standardization algorithm.
5. The data processing method for provider ratings according to claim 4, wherein the data types of the ratings data further include a date of application, a rate of discount bid, and a total amount of interest, the calculating the intermediate ratings data corresponding to each data type based on a preset algorithm and the ratings data of each data type further includes:
calculating third intermediate rating data corresponding to the application date according to a preset deviation standardization algorithm;
calculating fourth intermediate rating data corresponding to the bid discount rate according to a preset deviation standardization algorithm;
and calculating fifth intermediate rating data corresponding to the interest sum according to a preset deviation standardization algorithm.
6. The data processing method for rating a provider according to claim 5, wherein the data types of the rating data further include custom data types, the calculating the intermediate rating data corresponding to each data type according to a preset algorithm and the rating data of each data type, further comprising:
and calculating sixth intermediate rating data corresponding to the custom data type according to a preset custom algorithm.
7. The data processing method for vendor ratings according to claim 6, wherein the weight occupied by data types such as the number of payment days in advance, the amount of application, the date of application, the rate of discount bidding, and the custom data type is 15%, and the weight occupied by the interest sum is 25%.
8. A data processing apparatus for vendor ratings, the apparatus being configured in a management server, the apparatus comprising:
a request receiving unit, configured to obtain rating data of a provider matching with a provider rating maintenance request if the provider rating maintenance request sent by a user is received, where the rating data at least includes 2 data types;
the intermediate computing unit is used for computing intermediate rating data corresponding to each data type according to a preset algorithm and the rating data of each data type;
the target calculating unit is used for calculating target rating data according to preset weights of each data type and the calculated intermediate rating data;
and the processing unit is used for determining the evaluation grade of the supplier according to the preset rating interval and the calculated target rating data.
9. A computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the steps of the data processing method for vendor ratings according to any one of claims 1 to 7 when executing a program stored on a memory.
10. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of a data processing method for vendor ratings according to any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311342838.4A CN117078324A (en) | 2023-10-17 | 2023-10-17 | Data processing method, device, equipment and medium for provider rating |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311342838.4A CN117078324A (en) | 2023-10-17 | 2023-10-17 | Data processing method, device, equipment and medium for provider rating |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117078324A true CN117078324A (en) | 2023-11-17 |
Family
ID=88712024
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311342838.4A Pending CN117078324A (en) | 2023-10-17 | 2023-10-17 | Data processing method, device, equipment and medium for provider rating |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117078324A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109242562A (en) * | 2018-08-31 | 2019-01-18 | 万翼科技有限公司 | Ranking method, device and the storage medium of supplier |
| WO2019159322A1 (en) * | 2018-02-16 | 2019-08-22 | 西村 昇 | Mobile terminal device and service providing system |
| CN113222743A (en) * | 2021-06-07 | 2021-08-06 | 浙江财经大学 | Online loan borrower credit rating method based on factor score K-Means clustering |
| CN115965397A (en) * | 2022-12-28 | 2023-04-14 | 国网甘肃省电力公司天水供电公司 | Supplier holographic portrait evaluation system |
| CN116805219A (en) * | 2021-10-19 | 2023-09-26 | 南方电网数字电网研究院有限公司 | Vendor management method and device for realizing classification and grading based on four dimensions |
-
2023
- 2023-10-17 CN CN202311342838.4A patent/CN117078324A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019159322A1 (en) * | 2018-02-16 | 2019-08-22 | 西村 昇 | Mobile terminal device and service providing system |
| CN109242562A (en) * | 2018-08-31 | 2019-01-18 | 万翼科技有限公司 | Ranking method, device and the storage medium of supplier |
| CN113222743A (en) * | 2021-06-07 | 2021-08-06 | 浙江财经大学 | Online loan borrower credit rating method based on factor score K-Means clustering |
| CN116805219A (en) * | 2021-10-19 | 2023-09-26 | 南方电网数字电网研究院有限公司 | Vendor management method and device for realizing classification and grading based on four dimensions |
| CN115965397A (en) * | 2022-12-28 | 2023-04-14 | 国网甘肃省电力公司天水供电公司 | Supplier holographic portrait evaluation system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11176277B2 (en) | Automatic generating analytics from blockchain data | |
| US10452998B2 (en) | Cognitive blockchain automation and management | |
| US7979520B2 (en) | Prescriptive architecture recommendations | |
| US10366085B2 (en) | System, method, and computer program for audit scoring | |
| CN103827908A (en) | Systems and methods for a large-scale credit data processing architecture | |
| CN112328886A (en) | Block chain-based credit recommendation method, equipment and storage medium | |
| CN103250376A (en) | Method and system for carrying out predictive analysis relating to nodes of a communication network | |
| CN112036631A (en) | Purchasing quantity determination method, device, equipment and storage medium | |
| CN117236941A (en) | Enterprise grading-based payment settlement method, device, equipment and medium | |
| CN110633304B (en) | Combined feature screening method, device, computer equipment and storage medium | |
| CN113743968A (en) | Information delivery method, device and equipment | |
| CN110690987B (en) | Account information management method, device and equipment | |
| US20230289692A1 (en) | Risk management system interface | |
| CN117078324A (en) | Data processing method, device, equipment and medium for provider rating | |
| CN111523849A (en) | Resource transaction auditing method and device and server | |
| CN114511313A (en) | Payment channel access method, system, computer equipment and readable storage medium | |
| US20140129513A1 (en) | Subset calculation by identifying calculated values with modified parameters | |
| CN114066644A (en) | Annuity data tail difference processing method and device and electronic equipment | |
| CN113495887A (en) | Data form processing method, device and system | |
| WO2020191338A1 (en) | Resource stabilization in a distributed network | |
| CN110750557A (en) | Management method and device for insurance enterprise channel | |
| CN111915315B (en) | Authentication mode recommendation method and device, electronic equipment and readable storage medium | |
| CN116186046B (en) | Device data modification method and device, computer device and storage medium | |
| CN113392138B (en) | Statistical analysis method, device, server and storage medium for private data | |
| CN109272218B (en) | Method, device, computer equipment and storage medium for batch rating bonds |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |