Supply chain data and model mapping method, integration method and system

Abstract

The invention discloses a supply chain data and model mapping method, integration method and system, and the method comprises the steps: obtaining the business data information of each node of a supply chain, and the business data information comprises the business activity and the data flow direction; constructing a service data flow diagram according to the service data information; constructing a service directed graph according to the service data flow graph, and obtaining a service directed graph set; obtaining a target directed graph of the model, traversing the business directed graph in the business directed graph set, and performing isomorphism judgment on the business directed graph and the target directed graph to obtain an isomorphic business directed graph isomorphic with the target directed graph; generating a data mapping rule according to the target directed graph and the isomorphic business directed graph; and establishing mapping between the supply chain data and the model according to the data mapping rule. The problems of low supply chain data integration processing efficiency, low accuracy and high cost are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of supply chain data mapping, and in particular relates to a mapping method, an integration method and a system for supply chain data and models. Background Art

[0002] In the past, the informatization planning and construction of the supply chain were not perfect, resulting in legacy problems in the informatization planning and construction of various supply chain systems. In the past, supply chain systems were designed and constructed entirely based on the needs of each business segment, with weak overall planning, and no consideration of whether there were duplicate functions or data between different supply chain systems. In addition, each supply chain system was built by different manufacturers and products, resulting in inconsistent data models in the supply chain systems of various companies, contradictory or confusing data definitions, affecting data exchange between different supply chain systems between companies, making data sharing more difficult.

[0003] In the work of data integration construction of supply chain systems of various enterprises, the traditional method is to compare and judge the data and models of different nodes of the supply chain based on manual comparison. This has the problems of long comparison time, low comparison accuracy, high cost, and inability to cope with the increasingly complex data integration requirements. Therefore, there is an urgent need for a faster and more efficient way to automatically compare the data and models of different nodes. Summary of the invention

[0004] The purpose of the present invention is to provide a mapping method, an integration method and a system for supply chain data and models, so as to solve the problems of low efficiency, low accuracy and high cost in supply chain data integration processing.

[0005] The present invention is achieved through the following technical solutions:

[0006] The mapping method of supply chain data and models includes the following steps:

[0007] S1. Obtain business data information of each node in the supply chain, including business activities and data flow;

[0008] S2. Construct a business data flow diagram based on business data information;

[0009] S3. Construct a business directed graph according to the business data flow graph to obtain a business directed graph set;

[0010] S4. Obtain the target directed graph of the model, traverse the business directed graphs in the business directed graph set, determine whether the business directed graph is isomorphic with the target directed graph, and obtain an isomorphic business directed graph that is isomorphic with the target directed graph;

[0011] S5. Generate data mapping rules according to the target directed graph and the isomorphic business directed graph;

[0012] S6. Establish mapping between supply chain data and models according to data mapping rules.

[0013] In some embodiments, step S3 constructs a business directed graph according to the business data flow graph, specifically including:

[0014] The business activities in the business data flow graph are represented as nodes, the relationship between each business activity is represented as an edge, and the data flow between each business activity is represented as the edge direction to construct a business data flow graph.

[0015] In some embodiments, in step S4, traversing the business directed graphs in the business directed graph set, determining the isomorphism between the business directed graph and the target directed graph, and obtaining an isomorphic business directed graph isomorphic to the target directed graph includes the following steps:

[0016] S41. According to the number of nodes of the target directed graph, traverse all business directed graphs in the business directed graph set to obtain an equal-point business directed graph with the same number of nodes as the target directed graph;

[0017] S42, according to the number of edges of the target directed graph, traverse all equal-point business directed graphs to obtain a quasi-isomorphic business directed graph with the same number of edges as the target directed graph;

[0018] S43. According to the corresponding node relationship of the target directed graph, all pseudo-isomorphic business directed graphs are traversed to obtain an isomorphic business directed graph having the same corresponding node relationship as the target directed graph.

[0019] In some embodiments, step S43 includes the steps of:

[0020] S431, constructing a target adjacency matrix and a quasi-isomorphic adjacency matrix respectively according to the target directed graph and the quasi-isomorphic business directed graph;

[0021] S432, exchanging rows or columns of the target adjacency matrix and the quasi-isomorphic adjacency matrix for a limited number of times to obtain a target transformed adjacency matrix and a quasi-isomorphic transformed adjacency matrix;

[0022] Determine whether the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix;

[0023] If the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix, the target directed graph is isomorphic to the quasi-isomorphic business directed graph, and an isomorphic business directed graph is obtained;

[0024] If the target transformation adjacency matrix is ​​not the same as the quasi-isomorphic transformation adjacency matrix, then the target directed graph and the quasi-isomorphic business directed graph are not isomorphic.

[0025] In some embodiments, step S431 constructs a target adjacency matrix and a quasi-isomorphic adjacency matrix according to the target directed graph and the quasi-isomorphic business directed graph, respectively, including:

[0026] If there is an edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j] = 1. If there is no edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j] = 0.

[0027]

[0028] in,<vi,vj> represents an ordered pair, and E represents a directed graph edge set.

[0029] In some embodiments, the method for determining whether the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix in step S432 is:

[0030] When the target transformation adjacency matrix and the quasi-isomorphic transformation adjacency matrix satisfy Then the target transformation adjacency matrix is ​​judged to be the same as the quasi-isomorphic transformation adjacency matrix, otherwise the target transformation adjacency matrix is ​​judged to be different from the quasi-isomorphic transformation adjacency matrix.

[0031] Among them, M 1 is the target transformation adjacency matrix, M 2 is the quasi-isomorphic transformation adjacency matrix, E i is an elementary transformation matrix, i∈(1, 2,…, n).

[0032] In some embodiments, according to the definition of graph isomorphism and the corresponding business activity node positions after exchanging rows or columns, the nodes of the isomorphic business directed graph and the target directed graph are matched one by one to obtain the data mapping rules between the isomorphic business directed graph and the target directed graph.

[0033] The present invention also relates to a supply chain data integration method, which integrates the supply chain data by mapping the supply chain data and the model established by the above-mentioned supply chain data and model mapping method.

[0034] The present invention also relates to a mapping system of supply chain data and models, which uses the mapping method of supply chain data and models in the book "Shua Girl Book" to establish the mapping of supply chain data and models, including:

[0035] The acquisition module is used to obtain the target directed graph of each business data information and model of each node in the supply chain;

[0036] A business data flow graph construction module is used to construct a business data flow graph based on business data information;

[0037] A business directed graph set construction module is used to construct a business directed graph according to the business data flow graph to form a business directed graph set;

[0038] An isomorphic judgment module is used to traverse the business directed graphs in the business directed graph set, perform isomorphic judgment on the business directed graph and the target directed graph, and obtain an isomorphic business directed graph that is isomorphic to the target directed graph;

[0039] The mapping module is used to establish the mapping between the supply chain data and the model according to the data mapping rules generated by the target directed graph and the isomorphic business directed graph.

[0040] The present invention also relates to a supply chain data integration system, comprising:

[0041] A mapping system between the above supply chain data and models;

[0042] The integration module is used to integrate the supply chain data according to the mapping between the supply chain data and the model.

[0043] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0044] 1. The present invention constructs a business directed graph, traverses the business directed graphs in the business directed graph set, makes isomorphism judgment between the business directed graph and the target directed graph of the model, obtains an isomorphic business directed graph isomorphic to the target directed graph, and then establishes a mapping between the supply chain data and the model according to the data mapping rules generated by the target directed graph and the isomorphic business directed graph, thereby improving the efficiency and accuracy of supply chain data integration processing and reducing costs.

[0045] 2. For the target directed graph and the business directed graph in the business directed graph set, the isomorphism method is adopted, which first matches the number of nodes, then matches the number of edges, and then matches the corresponding node relationships through the adjacency matrix. This effectively avoids a lot of repetitive work and improves the isomorphism efficiency, thereby improving the efficiency and accuracy of the mapping between supply chain data and models. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 This is a flow chart of the mapping method between supply chain data and models in Example 1 of the present invention.

[0048] Figure 2 This is a business data flow diagram of each supply chain node in Example 1 of the present invention.

[0049] Figure 3 This is the data flow diagram of the production planning business in Example 2 of the present invention.

[0050] Figure 4 It is a directed graph of production planning business in Example 2 of the present invention.

[0051] Figure 5 It is the target directed graph in Example 2 of the present invention.

[0052] Figure 6 This is a schematic diagram showing that the target directed graph and the production plan business directed graph are isomorphic in Example 2 of the present invention.

[0053] Figure 7 It is a directed graph of homogeneous services in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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.

[0055] Example 1

[0056] The mapping method between supply chain data and models is as follows: Figure 1 , including the steps of:

[0057] S1. Obtain business data information of each node in the supply chain, including business activities and data flow;

[0058] S2. Construct a business data flow diagram based on business data information;

[0059] Among them, the business data flow diagram is centered on the business activity process and describes the complete business and data flow. Figure 2 ,According to the business data information of different businesses in the supply chain nodes, the business data flow diagram of each supply chain node can be obtained.

[0060] S3. Construct a business directed graph according to the business data flow graph to obtain a business directed graph set;

[0061] S4. Obtain the target directed graph of the model, traverse the business directed graphs in the business directed graph set, determine whether the business directed graph is isomorphic with the target directed graph, and obtain an isomorphic business directed graph that is isomorphic with the target directed graph;

[0062] S5. Generate data mapping rules according to the target directed graph and the isomorphic business directed graph;

[0063] S6. Establish mapping between supply chain data and models according to data mapping rules.

[0064] By constructing a business directed graph, traversing the business directed graphs in the business directed graph set, the business directed graph and the target directed graph of the model are judged to be isomorphic, and an isomorphic business directed graph that is isomorphic to the target directed graph is obtained. Then, the mapping between the supply chain data and the model is established according to the data mapping rules generated by the target directed graph and the isomorphic business directed graph, which improves the efficiency and accuracy of supply chain data integration processing and reduces costs.

[0065] In some embodiments, step S3 constructs a business directed graph according to the business data flow graph, specifically including:

[0066] The business activities in the business data flow graph are represented as nodes, the relationship between each business activity is represented as an edge, and the data flow between each business activity is represented as the edge direction to construct a business data flow graph.

[0067] In some embodiments, in step S4, traversing the business directed graphs in the business directed graph set, determining the isomorphism between the business directed graph and the target directed graph, and obtaining an isomorphic business directed graph isomorphic to the target directed graph includes the following steps:

[0068] S41. According to the number of nodes of the target directed graph, traverse all business directed graphs in the business directed graph set to obtain an equal-point business directed graph with the same number of nodes as the target directed graph;

[0069] S42, according to the number of edges of the target directed graph, traverse all equal-point business directed graphs to obtain a quasi-isomorphic business directed graph with the same number of edges as the target directed graph;

[0070] S43. According to the corresponding node relationship of the target directed graph, all pseudo-isomorphic business directed graphs are traversed to obtain an isomorphic business directed graph having the same corresponding node relationship as the target directed graph.

[0071] For the target directed graph and the business directed graph in the business directed graph set, the isomorphism method is adopted, which first matches the number of nodes, then matches the number of edges, and then matches the corresponding node relationships through the adjacency matrix. This effectively avoids a lot of repetitive work and improves the isomorphism efficiency, thereby improving the efficiency and accuracy of the mapping of supply chain data and models.

[0072] In some embodiments, step S43 includes the steps of:

[0073] S431, constructing a target adjacency matrix and a quasi-isomorphic adjacency matrix respectively according to the target directed graph and the quasi-isomorphic business directed graph;

[0074] S432, exchanging rows or columns of the target adjacency matrix and the quasi-isomorphic adjacency matrix for a limited number of times to obtain a target transformed adjacency matrix and a quasi-isomorphic transformed adjacency matrix;

[0075] Determine whether the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix;

[0076] If the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix, the target directed graph is isomorphic to the quasi-isomorphic business directed graph, and an isomorphic business directed graph is obtained;

[0077] If the target transformation adjacency matrix is ​​not the same as the quasi-isomorphic transformation adjacency matrix, then the target directed graph and the quasi-isomorphic business directed graph are not isomorphic.

[0078] In some embodiments, step S431 constructs a target adjacency matrix and a quasi-isomorphic adjacency matrix according to the target directed graph and the quasi-isomorphic business directed graph, respectively, including:

[0079] If there is an edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j] = 1. If there is no edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j] = 0.

[0080]

[0081] in,<vi,vj> represents an ordered pair, and E represents a directed graph edge set.

[0082] In some embodiments, the method for determining whether the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix in step S432 is:

[0083] When the target transformation adjacency matrix and the quasi-isomorphic transformation adjacency matrix satisfy Then the target transformation adjacency matrix is ​​judged to be the same as the quasi-isomorphic transformation adjacency matrix, otherwise the target transformation adjacency matrix is ​​judged to be different from the quasi-isomorphic transformation adjacency matrix.

[0084] Among them, M 1 is the target transformation adjacency matrix, M 2 is the quasi-isomorphic transformation adjacency matrix, E i is an elementary transformation matrix, i∈(1, 2,…, n).

[0085] In some embodiments, according to the definition of graph isomorphism and the corresponding business activity node positions after exchanging rows or columns, the nodes of the isomorphic business directed graph and the target directed graph are matched one by one to obtain the data mapping rules between the isomorphic business directed graph and the target directed graph.

[0086] The present invention also relates to a supply chain data integration method, which integrates the supply chain data by mapping the supply chain data and the model established by the above-mentioned supply chain data and model mapping method.

[0087] The present invention also relates to a mapping system of supply chain data and models, which uses the mapping method of supply chain data and models in the book "Shua Girl Book" to establish the mapping of supply chain data and models, including:

[0088] The acquisition module is used to obtain the target directed graph of each business data information and model of each node in the supply chain;

[0089] A business data flow graph construction module is used to construct a business data flow graph based on business data information;

[0090] A business directed graph set construction module is used to construct a business directed graph according to the business data flow graph to form a business directed graph set;

[0091] An isomorphic judgment module is used to traverse the business directed graphs in the business directed graph set, perform isomorphic judgment on the business directed graph and the target directed graph, and obtain an isomorphic business directed graph that is isomorphic to the target directed graph;

[0092] The mapping module is used to establish the mapping between the supply chain data and the model according to the data mapping rules generated by the target directed graph and the isomorphic business directed graph.

[0093] The present invention also relates to a supply chain data integration system, comprising:

[0094] A mapping system between the above supply chain data and models;

[0095] The integration module is used to integrate the supply chain data according to the mapping between the supply chain data and the model.

[0096] Example 2

[0097] Taking the production planning business of the supply chain as an example, the mapping method of the production planning business data and the model includes the following steps:

[0098] S1. Obtain data information on the production planning business of the supply chain;

[0099] The business activities of production planning business include: business activity A1 representing production plan preparation, business activity B1 representing resource capacity balance, business activity C1 representing plan approval and issuance, business activity D1 representing plan executors, and business activity E1 representing product completion and storage.

[0100] The data flow of each business activity includes: business activity A1 passes the production plan information to business activity B1, that is, there is a data flow from A1 to B1; business activity B1 passes the balanced resource and plan information to business activity C1, that is, there is a data flow from B1 to C1; business activity C1 sends the approved resource and plan information to business activity D1, that is, there is a data flow from C1 to D1; business activity D1 sends the finished product information to business activity E1, that is, there is a data flow from D1 to E1; business activity E1 sends the warehouse information to business activity A1 to realize plan feedback, that is, there is a data flow from E1 to A1.

[0101] S2. Construct a data flow diagram of the production planning business based on the data information of the production planning business;

[0102] Reference Figure 3 The production planning business data flow diagram describes the complete business and data flow with the business activity process as the center.

[0103] S3. Construct a production plan business directed graph according to the production plan business data flow graph;

[0104] Reference Figure 4 , business activity A1 in the production plan business data flow diagram is represented as node A1, business activity B1 is represented as node B1, business activity C1 is represented as node C1, business activity D1 is represented as node D1, and business activity E1 is represented as node E1;

[0105] The relationship between business activity A1 and business activity B1 is represented as an edge, and the data flow from business activity A1 to business activity B1 is represented as the edge direction by an arrow; similarly, the relationship between business activity B1 and business activity C1 is represented as an edge, and the data flow from business activity B1 to business activity C1 is represented as the edge direction by an arrow; the relationship between business activity C1 and business activity D1 is represented as an edge, and the data flow from business activity C1 to business activity D1 is represented as the edge direction by an arrow; the relationship between business activity D1 and business activity E1 is represented as an edge, and the data flow from business activity D1 to business activity E1 is represented as the edge direction by an arrow; the relationship between business activity E1 and business activity A1 is represented as an edge, and the data flow from business activity E1 to business activity A1 is represented as the edge direction by an arrow.

[0106] S4. Obtain the target directed graph of the model, traverse the production plan business directed graph in the generated plan business directed graph set, make isomorphic judgment between the production plan business directed graph and the target directed graph, and obtain an isomorphic business directed graph that is isomorphic to the target directed graph;

[0107] Reference Figure 5 The target directed graph of the model includes nodes A, B, C, D and E. The data flow from node A to node B is represented by an arrow as an edge direction, the data flow from node B to node C is represented by an arrow as an edge direction, the data flow from node C to node D is represented by an arrow as an edge direction, the data flow from node D to node E is represented by an arrow as an edge direction, and the data flow from node E to node A is represented by an arrow as an edge direction.

[0108] First, according to the number of nodes of the target directed graph, all production plan business directed graphs in the production plan business directed graph set are traversed to obtain an equal-point business directed graph with the same number of nodes as the target directed graph;

[0109] Then, according to the number of edges of the target directed graph, all equal-point business directed graphs are traversed to obtain a quasi-isomorphic business directed graph with the same number of edges as the target directed graph;

[0110] Then, if there is an edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j] = 1; if there is no edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j] = 0.

[0111]

[0112] in,<vi,vj> represents an ordered pair, and E represents a directed graph edge set;

[0113] Constructing a target adjacency matrix and a quasi-isomorphic adjacency matrix respectively according to the target directed graph and the quasi-isomorphic business directed graph;

[0114] The target adjacency matrix and the quasi-isomorphic adjacency matrix are exchanged for a limited number of times to obtain the target transformed adjacency matrix M. 1 and the quasi-isomorphic transformation adjacency matrix M 2 ;

[0115] Determine the target transformation adjacency matrix M 1 and the quasi-isomorphic transformation adjacency matrix M 2 Are they the same?

[0116] When satisfied E i is the elementary transformation matrix, i∈(1, 2, ..., n), then the target transformation adjacency matrix M is determined 1 and the quasi-isomorphic transformation adjacency matrix M 2 Same, reference Figure 7 , obtain a directed graph of homogeneous services;

[0117] Otherwise, determine the target transformation adjacency matrix M 1 and the quasi-isomorphic transformation adjacency matrix M 2 No, the target directed graph is not the same as the quasi-isomorphic business directed graph.

[0118] S5. Generate data mapping rules according to the target directed graph and the isomorphic business directed graph;

[0119] Reference Figure 6 ,According to the definition of graph isomorphism and the corresponding business activity node positions after exchanging rows or columns, the nodes of the isomorphic business directed graph and the target directed graph are matched one by one, and the data mapping rules between the isomorphic business directed graph and the target directed graph are obtained, that is, A≈A1, B≈B1, C≈C1, D≈D1, E≈E1, where ≈ represents mapping.

[0120] S6. Establish mapping between supply chain data and models according to data mapping rules.

[0121] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification or equivalent change made to the above embodiment based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A mapping method between supply chain data and models, characterized in that: Includes steps: S1. Acquire business data information of each node in the supply chain, wherein the business data information includes business activities and data flow; S2. Construct a business data flow diagram based on business data information; S3. Construct a business directed graph according to the business data flow graph to obtain a business directed graph set; S4. Obtain the target directed graph of the model, traverse the business directed graphs in the business directed graph set, determine whether the business directed graph is isomorphic with the target directed graph, and obtain an isomorphic business directed graph that is isomorphic with the target directed graph; S5. Generate data mapping rules according to the target directed graph and the isomorphic business directed graph; S6. Establish mapping between supply chain data and models according to data mapping rules.

2. The method for mapping supply chain data and models according to claim 1, characterized in that: The step S3 constructs a business directed graph according to the business data flow graph, specifically including: The business activities in the business data flow graph are represented as nodes, the relationship between each business activity is represented as an edge, and the data flow between each business activity is represented as the edge direction to construct a business data flow graph.

3. The method for mapping supply chain data and models according to claim 2, characterized in that: In the step S4, the business directed graphs in the business directed graph set are traversed, and the business directed graph and the target directed graph are isomorphic to each other to obtain an isomorphic business directed graph isomorphic to the target directed graph, including the steps of: S41. According to the number of nodes of the target directed graph, traverse all business directed graphs in the business directed graph set to obtain an equal-point business directed graph with the same number of nodes as the target directed graph; S42, according to the number of edges of the target directed graph, traverse all equal-point business directed graphs to obtain a quasi-isomorphic business directed graph with the same number of edges as the target directed graph; S43. According to the corresponding node relationship of the target directed graph, all pseudo-isomorphic business directed graphs are traversed to obtain an isomorphic business directed graph having the same corresponding node relationship as the target directed graph.

4. The method for mapping supply chain data and models according to claim 3, characterized in that: The step S43 comprises the steps of: S431, constructing a target adjacency matrix and a quasi-isomorphic adjacency matrix respectively according to the target directed graph and the quasi-isomorphic business directed graph; S432, exchanging rows or columns of the target adjacency matrix and the quasi-isomorphic adjacency matrix for a limited number of times to obtain a target transformed adjacency matrix and a quasi-isomorphic transformed adjacency matrix; Determine whether the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix; If the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix, the target directed graph is isomorphic to the quasi-isomorphic business directed graph, and an isomorphic business directed graph is obtained; If the target transformation adjacency matrix is ​​not the same as the quasi-isomorphic transformation adjacency matrix, then the target directed graph and the quasi-isomorphic business directed graph are not isomorphic.

5. The method for mapping supply chain data and models according to claim 4, characterized in that: Step S431 constructs a target adjacency matrix and a quasi-isomorphic adjacency matrix according to the target directed graph and the quasi-isomorphic business directed graph, respectively, including: if there is an edge from node vi to node vj in the preset directed graph, then the adjacency matrix M[i][j]=1; if there is no edge from node vi to node vj in the directed graph, then the adjacency matrix M[i][j]=0, in,<vi,vj> represents an ordered pair, and E represents a directed graph edge set.

6. The method for mapping supply chain data and models according to claim 4, characterized in that: The method for determining whether the target transformation adjacency matrix is ​​the same as the quasi-isomorphic transformation adjacency matrix in step S432 is: When the target transformation adjacency matrix and the quasi-isomorphic transformation adjacency matrix satisfy Then the target transformation adjacency matrix is ​​judged to be the same as the quasi-isomorphic transformation adjacency matrix, otherwise the target transformation adjacency matrix is ​​judged to be different from the quasi-isomorphic transformation adjacency matrix. Among them, M1 is the target transformation adjacency matrix, M2 is the quasi-isomorphic transformation adjacency matrix, and E i is an elementary transformation matrix, i∈(1, 2,…, n).

7. The method for mapping supply chain data to a model according to claim 4, characterized in that: According to the definition of graph isomorphism and the corresponding business activity node positions after exchanging rows or columns, the nodes of the isomorphic business directed graph and the target directed graph are matched one by one to obtain the data mapping rules between the isomorphic business directed graph and the target directed graph.

8. A supply chain data integration method, characterized in that: The supply chain data is integrated by mapping the supply chain data and the model established by the supply chain data and the model mapping method described in any one of claims 1 to 7.

9. A mapping system for supply chain data and models, characterized in that: The mapping method of supply chain data and model according to any one of claims 1 to 7 is used to establish the mapping of supply chain data and model, comprising: The acquisition module is used to obtain the target directed graph of each business data information and model of each node in the supply chain; A business data flow graph construction module is used to construct a business data flow graph based on business data information; A business directed graph set construction module is used to construct a business directed graph according to the business data flow graph to form a business directed graph set; An isomorphic judgment module is used to traverse the business directed graphs in the business directed graph set, perform isomorphic judgment on the business directed graph and the target directed graph, and obtain an isomorphic business directed graph that is isomorphic to the target directed graph; The mapping module is used to establish the mapping between the supply chain data and the model according to the data mapping rules generated by the target directed graph and the isomorphic business directed graph.

10. Supply chain data integration system, characterized in that, include: The supply chain data and model mapping system of claim 9; The integration module is used to integrate the supply chain data according to the mapping between the supply chain data and the model.

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