Supply chain business opportunity mining system based on big data

Abstract

The invention discloses a supply chain business opportunity mining system based on big data, and belongs to the technical field of supply chain construction, and the system specifically comprises a database which is used for storing enterprise data related to an enterprise supply chain; the data initialization module is used for acquiring enterprise parameters of supply chain application enterprises, calculating technical values of the application enterprises according to the enterprise parameters and rating the application enterprises; the enterprise judgment module is used for calculating the competitive degree of the application enterprise and the enterprise according to the enterprise parameters, measuring the supply value of the application enterprise based on the competitive degree and the technical value, and determining a final rating; the cooperation request module is used for actively sending a supply chain request to an application enterprise according to the final rating; according to the method, supply chain evaluation analysis is carried out on the application enterprises, and the technical values and the similarity degrees of the application enterprises are analyzed, so that the enterprises which are high in technical level and can form supply chain complementation with the enterprises are screened, and an accurate and efficient supply chain system is generated.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain construction, and in particular to a supply chain business opportunity mining system based on big data. Background Art

[0002] The continued growth of all kinds of data on customer preferences is rapidly changing the way supply chain service providers operate and highlighting the strong need for enhanced data management and analysis. The benefits of large and complex data sets are obvious: Big data can completely change the way organizations work, making huge differences in efficiency, cost, visibility and customer satisfaction.

[0003] Based on this, for the supply chain service event data of various supply chain service nodes, how to further share and associate more shared big data, so as to provide associated data support for data integration between enterprises in the supply chain, is an important direction that needs to be urgently studied in this field. Summary of the invention

[0004] The purpose of the present invention is to provide a supply chain business opportunity mining system based on big data to solve the following technical problems:

[0005] Based on this, for the supply chain service event data of various supply chain service nodes, how to further share and associate more shared big data, so as to provide associated data support for data integration between enterprises in the supply chain, is an important direction that needs to be urgently studied in this field.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] Supply chain business opportunity mining system based on big data, including:

[0008] Database, used to store enterprise data related to the enterprise's supply chain;

[0009] The data initialization module is used to obtain the enterprise parameters of the supply chain applicant enterprise, calculate the technical value of the applicant enterprise based on the enterprise parameters, and rate the applicant enterprise;

[0010] An enterprise judgment module is used to calculate the competitiveness of the applicant enterprise and the enterprise according to the enterprise parameters, measure the supply value of the applicant enterprise based on the competitiveness and technical value, and determine the final rating;

[0011] The cooperation request module is used to proactively send a supply chain request to the applicant enterprise based on the final rating.

[0012] As a further solution of the present invention: the types of enterprise parameters collected by the data collection module include the number of patents, patent rankings, the number of projects, project levels, the number of talent titles, title levels and the number of technical contracts.

[0013] As a further solution of the present invention: the enterprise parameters include:

[0014] The transaction information corresponding to each enterprise includes upstream transaction amount, downstream transaction amount, total number of upstream transaction partners and total number of downstream transaction partners.

[0015] As a further solution of the present invention: the process of the data processing module calculating the technical value of the applicant enterprise is:

[0016] Normalize various enterprise parameters of the applicant enterprise, calculate the entropy value of each enterprise parameter after normalization, assign weights to each enterprise parameter according to the entropy value, calculate the technical value of the applicant enterprise based on the weight of each enterprise parameter and actual data, and perform initial rating on the applicant enterprise based on the technical value.

[0017] As a further solution of the present invention: the process of the data processing module performing initial rating on the applicant enterprise is as follows:

[0018] Obtain the technical value of the applicant enterprises, and divide the applicant enterprises into ordinary enterprises, intermediate enterprises and key enterprises; conduct secondary verification on the key enterprises, recalculate the weights of various indicators of the key enterprises, and generate a secondary score for the pending key enterprises, use the results of the secondary score as the final technical value of the key enterprises, and re-rate the key enterprises based on the final technical value.

[0019] As a further solution of the present invention: the cooperation request module includes:

[0020] Obtain the list of preferred enterprises, and proactively initiate cooperation requests only for the preferred enterprises that are finally rated as key enterprises.

[0021] As a further solution of the present invention: the data collection module further includes a pre-screening unit, which is used to obtain the total number of all enterprise parameters of the applicant enterprise and reject the cooperation request of the applicant enterprise whose total number is lower than the preset number.

[0022] Beneficial effects of the present invention:

[0023] The present invention conducts supply chain evaluation and analysis on the applicant enterprises, analyzes the technical value of the applicant enterprises and the degree of similarity between the applicant enterprises and the present enterprise, thereby screening enterprises with high technical level and able to form supply chain complementarity with the present enterprise, so as to generate an accurate and efficient supply chain system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention will be further described below in conjunction with the accompanying drawings.

[0025] Figure 1 It is a module schematic diagram of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] See also Figure 1 As shown, the present invention is a supply chain business opportunity mining system based on big data, comprising:

[0028] Database, used to store enterprise data related to the enterprise's supply chain;

[0029] The data initialization module is used to obtain the enterprise parameters of the supply chain applicant enterprise, calculate the technical value of the applicant enterprise based on the enterprise parameters, and rate the applicant enterprise;

[0030] An enterprise judgment module is used to calculate the competitiveness of the applicant enterprise and the enterprise according to the enterprise parameters, measure the supply value of the applicant enterprise based on the competitiveness and technical value, and determine the final rating;

[0031] The cooperation request module is used to proactively send a supply chain request to the applicant enterprise based on the final rating.

[0032] Based on this, how to further share and associate the supply chain service event data of various supply chain service nodes to configure more shared big data, so as to provide associated data support for the data integration between enterprises in the supply chain, is an important direction that needs to be studied in this field;

[0033] The present invention conducts supply chain evaluation and analysis on the applicant enterprises, analyzes the technical value of the applicant enterprises and the degree of similarity between the applicant enterprises and the present enterprise, thereby screening enterprises with high technical level and able to form supply chain complementarity with the present enterprise, so as to generate an accurate and efficient supply chain system.

[0034] In a preferred embodiment of the present invention, the types of enterprise parameters collected by the data collection module include the number of patents, patent ranking, number of projects, project level, number of talent titles, title level and number of technical contracts.

[0035] In a preferred embodiment of the present invention, the enterprise parameters include:

[0036] The transaction information corresponding to each enterprise includes upstream transaction amount, downstream transaction amount, total number of upstream transaction partners and total number of downstream transaction partners.

[0037] In a preferred embodiment of the present invention, the process of the data processing module calculating the technical value of the applicant enterprise is:

[0038] Normalize various enterprise parameters of the applicant enterprise, calculate the entropy value of each enterprise parameter after normalization, assign weights to each enterprise parameter according to the entropy value, calculate the technical value of the applicant enterprise based on the weight of each enterprise parameter and actual data, and perform initial rating on the applicant enterprise based on the technical value.

[0039] In a preferred embodiment of the present invention, the process of the data processing module performing an initial rating on the applicant enterprise is as follows:

[0040] Obtain the technical value of the applicant enterprises, and divide the applicant enterprises into ordinary enterprises, intermediate enterprises and key enterprises; conduct secondary verification on the key enterprises, recalculate the weights of various indicators of the key enterprises, and generate a secondary score for the pending key enterprises, use the results of the secondary score as the final technical value of the key enterprises, and re-rate the key enterprises based on the final technical value.

[0041] In a preferred embodiment of the present invention, the cooperation request module includes:

[0042] Obtain the list of preferred enterprises, and proactively initiate cooperation requests only for the preferred enterprises that are finally rated as key enterprises.

[0043] In a preferred embodiment of the present invention, the data collection module further includes a pre-screening unit, which is used to obtain the total number of all enterprise parameters of the applicant enterprises and reject cooperation requests from applicant enterprises whose total number is lower than a preset number.

[0044] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. Supply chain business opportunity mining system based on big data, characterized by: include: Database, used to store enterprise data related to the enterprise's supply chain; The data initialization module is used to obtain the enterprise parameters of the supply chain applicant enterprise, calculate the technical value of the applicant enterprise based on the enterprise parameters, and rate the applicant enterprise; An enterprise judgment module is used to calculate the competitiveness of the applicant enterprise and the enterprise according to the enterprise parameters, measure the supply value of the applicant enterprise based on the competitiveness and technical value, and determine the final rating; The cooperation request module is used to proactively send a supply chain request to the applicant enterprise based on the final rating.

2. The supply chain business opportunity mining system based on big data according to claim 1 is characterized in that: The types of enterprise parameters collected by the data collection module include the number of patents, patent rankings, the number of projects, project levels, the number of talent titles, title levels and the number of technical contracts.

3. The supply chain business opportunity mining system based on big data according to claim 1 is characterized in that: The enterprise parameters include: The transaction information corresponding to each enterprise includes the upstream transaction amount, downstream transaction amount, the total number of upstream transaction partners and the total number of downstream transaction partners.

4. The supply chain business opportunity mining system based on big data according to claim 1 is characterized in that: The process of calculating the technical value of the applicant enterprise by the data processing module is as follows: Normalize various enterprise parameters of the applicant enterprise, calculate the entropy value of each enterprise parameter after normalization, assign weights to each enterprise parameter according to the entropy value, calculate the technical value of the applicant enterprise based on the weight of each enterprise parameter and actual data, and perform initial rating on the applicant enterprise based on the technical value.

5. The supply chain business opportunity mining system based on big data according to claim 1 is characterized in that: The process of the data processing module performing initial rating on the applicant enterprise is as follows: Obtain the technical value of the applicant enterprises, and divide the applicant enterprises into ordinary enterprises, intermediate enterprises and key enterprises; conduct secondary verification on the key enterprises, recalculate the weights of various indicators of the key enterprises, and generate a secondary score for the pending key enterprises, use the results of the secondary score as the final technical value of the key enterprises, and re-rate the key enterprises based on the final technical value.

6. The supply chain business opportunity mining system based on big data according to claim 1 is characterized in that: The cooperation request module includes: Obtain the list of preferred enterprises, and proactively initiate cooperation requests only for the preferred enterprises that are finally rated as key enterprises.

7. The supply chain business opportunity mining system based on big data according to claim 1 is characterized in that: The data collection module also includes a pre-screening unit, which is used to obtain the total number of all enterprise parameters of the applicant enterprises and reject cooperation requests from applicant enterprises whose total number is lower than a preset number.

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