Method and device for integrating enterprise subject identities

Abstract

The invention relates to the technical field of computers, and provides a method and a device for integrating enterprise subject identities, and the method comprises the steps: carrying out the standardization processing of the obtained certificate relation data of all financial institutions, and obtaining a certificate relation set; the certificate relation data submitted by each financial institution belongs to the same or different enterprise identity combination, and the certificate relation data is relation data between every two enterprise identities; and traversing the topological graph constructed according to the certificate relationship set by using a depth-first traversal algorithm, and integrating the enterprise identities belonging to the same enterprise to obtain an integration result. Traversal and integration of large-scale data can be completed within limited time. The problems that an existing enterprise subject identity label integration method is large in calculation amount and low in matching efficiency are solved. According to the invention, scattered enterprise identities can be integrated, the enterprise identities which are wrongly integrated are split from the original enterprise, and the newly generated enterprise identities are integrated into the original enterprise.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and device for integrating enterprise entity identity identification. Background Art

[0002] In the field of financial technology, the data quality of corporate legal person data reported by financial institutions is crucial, including basic information of legal persons, credit information of legal persons, financial statements of legal persons, etc. Compared with natural persons, corporate identity identification is more numerous. A company has multiple identity identifications such as unified social credit code, organization code, business registration number, tax code, taxpayer identification number (national tax), taxpayer identification number (local tax), etc. In order to objectively, comprehensively and effectively evaluate the credit, assets and liabilities, cash flow, etc. of a company, it is necessary to integrate the identity of the same company from the credit information reported by multiple financial institutions.

[0003] There are few technologies for integrating corporate identity in the market. Most of them determine whether they are the same company by matching the similarity of data items such as company name, industry address, etc., and integrate companies that meet the similarity requirements. This type of method has the following defects: if you want to match the exact company name, you need to perform segmented matching with the company entity, region, industry and other data in the full amount of companies in the database, which requires a large amount of calculation and low matching efficiency. Summary of the invention

[0004] The present invention provides a method and device for integrating corporate entity identity identification, which is used to solve the defects of large amount of calculation and low matching efficiency in existing corporate identity identification integration methods. It can complete the traversal and integration of large-scale data in a limited time and improve the matching efficiency. The technical solution proposed by the present invention is as follows: In a first aspect, the present invention provides a method for integrating an enterprise entity identity, comprising: Obtain the certificate relationship data submitted by each financial institution, perform standardization on the certificate relationship data of all financial institutions, and obtain a certificate relationship set; wherein the certificate relationship data submitted by each financial institution belongs to the same or different enterprise identity identifier combinations, and the certificate relationship data is the relationship data between two enterprise identity identifiers; A topological graph is constructed according to the document relationship set, and the topological graph is traversed using a depth-first traversal algorithm to integrate corporate identity identifiers belonging to the same enterprise to obtain an integration result.

[0005] Optionally, constructing a topological graph according to the document relationship set, traversing the topological graph using a depth-first traversal algorithm, integrating enterprise identities belonging to the same enterprise, and obtaining an integration result includes: Each enterprise identity in the document relationship set is used as a node of the topological graph, and edges between nodes are constructed according to the relationship data between the enterprise identity identifiers; if the two enterprise identity identifiers are judged to belong to the same enterprise, equal edges are constructed; if the two enterprise identity identifiers are judged not to belong to the same enterprise, unequal edges are constructed; Traversing the topological graph, for each unequal edge, retrieving all the corresponding associated paths; wherein the associated path is any path connecting two nodes of the unequal edge, and the path includes other nodes and edges; For each unequal edge, the associated path corresponding to the unequal edge is debonded according to the preset debonding rule to obtain a topological graph after debonding; According to the edges and nodes in the topological graph after the edge removal process, the enterprise identities belonging to the same enterprise are integrated to obtain an integration result.

[0006] Optionally, the associated path is debonded in the following manner: Identifying the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path; Generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path; Whether the two corporate identities connected by the edge are split or merged is determined according to the split mark; when the split mark is split, the corresponding corporate identity is split; when the split mark is not split, the corresponding corporate identity is merged.

[0007] Optionally, generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path includes: If the priorities of all equal edges in the associated path are the same, and the priorities of all edges are less than or equal to the priority of the unequal edge, then the split flags of all edges in the associated path are determined to be split; If the priorities of all equal edges in the associated path are the same, and the priorities of all edges are greater than the priority of the unequal edge, the splitting marks of all edges in the associated path are determined to be not split; When the priorities of all equal edges in the associated path are not exactly the same, compare the priority of the target edge with the priority of the unequal edges. If the priority of the target edge is less than or equal to the priority of the unequal edges, the split mark of the target edge is determined to be split, and the split marks of other edges are determined to be not split; if the priority of the target edge is greater than the priority of the unequal edges, the split marks of all edges in the associated path are determined to be not split; among them, the target edge is the edge with the lowest priority in the associated path, and the other edges are the edges in the associated path except the target edge.

[0008] Optionally, before performing edge removal processing on the associated path corresponding to each unequal edge according to a preset edge removal rule, the method further includes: Identify the priority of each unequal side and sort all unequal sides according to their priority; According to the sorting result of the priorities of the unequal edges, the execution order of performing edge removal processing on the associated paths corresponding to each unequal edge is determined.

[0009] Optionally, the document relationship data is standardized in the following manner: For each certificate relationship data submitted by a financial institution, it is mapped to the corresponding fields of a pre-established standardized format according to its content; wherein, the standardized format includes a first enterprise identity type, a first enterprise identity number, a first enterprise identity name, a second enterprise identity type, a second enterprise identity number, a second enterprise identity name, a relationship flag, a priority and a data source, the relationship flag is used to indicate whether two enterprise identities point to the same enterprise, the priority is used to indicate the importance of the enterprise identity combination, and the data source indicates the financial institution to which the certificate relationship data belongs.

[0010] In a second aspect, the present invention further provides a device for integrating corporate entity identity identification, comprising the following modules: A processing module is used to obtain the certificate relationship data submitted by each financial institution, perform standardization processing on the certificate relationship data of all financial institutions, and obtain a certificate relationship set; wherein the certificate relationship data submitted by each financial institution belongs to the same or different enterprise identity identifier combinations, and the certificate relationship data is the relationship data between two enterprise identity identifiers; The traversal module is used to construct a topological map according to the document relationship set, traverse the topological map using a depth-first traversal algorithm, integrate the enterprise identity identifiers belonging to the same enterprise, and obtain an integration result.

[0011] In a third aspect, the present invention further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the method for integrating the corporate entity identity as described in the first aspect above is implemented.

[0012] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for integrating enterprise entity identity identification as described in the first aspect above.

[0013] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method for integrating enterprise entity identity identification as described in the first aspect above.

[0014] Based on the above technical solution, the beneficial effects of the present invention compared with the prior art are as follows: The method and device for integrating corporate subject identity provided by the present invention first obtains the document relationship data submitted by multiple financial institutions and performs standardized processing. This step reduces the complexity of the subsequent matching process by unifying the data format and standard, thereby improving the matching efficiency. By traversing the topological graph constructed according to the document relationship set using the depth-first traversal algorithm, the corporate identity identifiers belonging to the same enterprise are integrated to obtain an integration result, and the traversal and integration of large-scale data can be completed within a limited time. The problem of large amount of calculation and low matching efficiency in the existing corporate subject identity integration method is solved.

[0015] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0016] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is one of the flow charts of the method for integrating the corporate entity identity provided by the present invention.

[0019] Figure 2 This is the second flow chart of the method for integrating the corporate entity identity provided by the present invention.

[0020] Figure 3 This is the third flow chart of the method for integrating the corporate entity identity provided by the present invention.

[0021] Figure 4 It is a schematic diagram of the topology diagram provided by the present invention.

[0022] Figure 5It is a schematic diagram of all the paths that can be connected from point A to point H provided by the present invention.

[0023] Figure 6 Yes Figure 5 Schematic diagram of the edge splitting operation on the path in .

[0024] Figure 7 It is a schematic diagram of all the paths that can be connected from point C to point I provided by the present invention.

[0025] Figure 8 Yes Figure 7 Schematic diagram of the edge splitting operation on the path in .

[0026] Fig. 9 This is a schematic diagram of the final edge removal situation.

[0027] Fig.10 It is a structural schematic diagram of a device for integrating corporate entity identity provided by the present invention.

[0028] Fig.11 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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.

[0030] Combine the following Figure 1-Figure 10 The method and device for integrating the identity of an enterprise subject of the present invention are described. The method for integrating the identity of an enterprise subject of the present invention is described in detail in detail. Figure 1 As shown, For data from various data sources (i.e. Figure 1 The document relationship data of the standardized document relationship source 1, the standardized document relationship source 2, ... the standardized document relationship source n) are standardized to obtain a document relationship set, the document relationship set is input (input) for algorithm operation, and the integration result 1, the integration result 2, ... the integration result n are output (output), each integration result is filtered and intercepted, and the final integration result is output. The overall process of the present invention is divided into the following steps: ① Users / technical developers can obtain the relationships between various data sources from various storage media such as files and databases, and encapsulate them into Java objects in a specified format.

[0031] ② Input the encapsulated Java object into the algorithm for calculation.

[0032] ③ Filter and intercept the results of the calculation according to certain business rules.

[0033] Reference Figure 2 As shown, the method for integrating the corporate entity identity includes the following: Step S110: Obtain the certificate relationship data submitted by each financial institution, standardize the certificate relationship data of all financial institutions, and obtain a certificate relationship set.

[0034] The certificate relationship data provided by each financial institution is collected. The certificate relationship data submitted by each financial institution may belong to the same enterprise identity combination or to different enterprise identity combinations. As shown in Table 1, the certificate relationship data submitted by financial institutions A and B are the same enterprise identity combination. The enterprise identity combination of the certificate relationship data submitted by financial institution C is different from that of financial institutions A and B. The certificate relationship data is the relationship data between two enterprise identity identifiers, and the relationship data between two enterprise identity identifiers refers to a data set used to describe and record the relationship between two different but possibly related enterprise identity identifiers. These enterprise identity identifiers may include officially recognized identity information such as the unified social credit code, organization code, business registration number, tax registration number, etc. of the enterprise, as well as unofficial but widely used identity identifiers such as the enterprise name. The relationship data specifically describes whether the two identity identifiers belong to the same enterprise, as well as the attribute information such as priority, validity, and timeliness between these identity identifiers. By integrating and analyzing these relationship data, enterprise identity information can be managed and utilized more effectively, and data accuracy and business collaboration efficiency can be improved. The above-mentioned enterprise identity identifier combination can be a combination of any two of the above-mentioned enterprise identity identifiers. For example, it can be a combination of the unified social credit code and the organization code, or it can be a combination of the unified social credit code and the industrial and commercial registration number.

[0035] The source data used in the present invention is the certificate relationship data submitted by various financial institutions. Since the data formats submitted by various financial institutions may be different, and the formats of the two corporate identity tags may be different, the data format used for the certificate relationship data needs to be standardized. In order to clearly describe the standardized format of the certificate relationship, an example is given below, see Table 1.

[0036] Table 1

[0037] In Table 1, the first enterprise identification type (enterprise identification type 1) and the second enterprise identification type (enterprise identification type 2) columns represent the value range of the enterprise identification type, which can be a unified social credit code, organization code, business registration number, tax code, taxpayer identification number (national tax), taxpayer identification number (local tax) and other types; the first enterprise identification number (enterprise identification number 1) and the second enterprise identification number (enterprise identification number 2) represent the specific identification number of the enterprise; the first enterprise identification name (enterprise identification name 1) and the second enterprise identification name (enterprise identification name 2) represent the actual name of the enterprise; the relationship flag field can only take two values ​​0 and 1, a value of 1 represents the same enterprise, and a value of 0 represents not the same enterprise; the priority field can take values ​​1, 2, 3, 4, 5, 6, etc., and the smaller the value, the higher the relationship level; the source field represents the submission of different financial institutions, and can also be a fill-in value. The above priorities are set according to the source of the document relationship data in the specific financial business. For example, the regulatory agencies include the following types of relationships: 1. Certificate relationships approved by the regulatory agencies; 2. Certificate relationships strongly and proactively reported by financial institutions (which have been carefully verified); 3. Certificate relationships reported by financial institutions when reporting basic information services; 4. Certificate relationships generated by the regulatory agency's internal system by matching basic information (matching data items such as company name, registered address, and telephone number). 5. Certificate relationships generated by other means; The above certificate relationships are sorted from large to small, that is, from high to low feasibility.

[0038] The first row of data in the table means: the unified social credit code: XXXXXX and the organization code: YYYYYY reported by financial institution A to the financial regulatory authority are the same company, with a priority of 3. The second row of data means: the unified social credit code: XXXXXX and the organization code: YYYYYY reported by financial institution B to the financial regulatory authority are not the same company, with a priority of 3. The third row of data means: the unified social credit code: XXXXXX and the business registration number: MMMMMMM reported by financial institution C to the financial regulatory authority are the same company, with a priority of 3.

[0039] Before collecting data, clarify the types of corporate identity that need to be collected, such as unified social credit code, organization code, business registration number, etc. Establish contact with multiple financial institutions and request them to provide the certificate relationship data they have. Receive the certificate relationship data provided by each financial institution to form a data set. Before mapping the data to Table 1, clean the data set, specifically check whether there are duplicate records in the data set and delete these duplicate records. For missing fields in the data set, decide whether to fill in default values, delete related records, or perform other processing based on business needs. Unify the data format to ensure that the format of all data matches the requirements of Table 1. Standardize the company names, such as unifying them to full names, removing special characters, and performing spelling corrections.

[0040] The pre-processed data is then standardized. For the document relationship data submitted by each financial institution, it is mapped to the corresponding fields of the pre-established standardized format (such as Table 1) according to its content. The specific steps are as follows: Fill in the corporate identity type: Based on the collected data, determine the types of two corporate identities and fill them in the "Corporate Identity Type 1" and "Corporate Identity Type 2" columns of Table 1 respectively.

[0041] Fill in the enterprise identity number: fill in the specific numbers of the two enterprise identity numbers in the "Enterprise Identity Number 1" and "Enterprise Identity Number 2" columns of Table 1 respectively.

[0042] Fill in the corporate identity name: If the collected data contains corporate names associated with two corporate identities, these names can be filled in the "Corporate Identity Name 1" and "Corporate Identity Name 2" columns of Table 1 respectively.

[0043] Determine the relationship flag: The relationship flag is used to indicate whether two enterprise identity identifiers point to the same enterprise. First, compare the two enterprise identity identifiers (such as the unified social credit code and the organization code) to check whether they correspond to the records of the same enterprise. If the two identity identifiers can match other information of the same enterprise in the database (such as the company name, legal representative, registered address, etc.), it can be considered that the two identity identifiers point to the same enterprise, and the relationship flag should be set to "yes" or 1. If the two identity identifiers cannot match other information of the same enterprise, or there are obvious differences in the matched information, it can be considered that the two identity identifiers do not point to the same enterprise, and the relationship flag should be set to "no" or 0.

[0044] In some cases, there may be multiple identities corresponding to the same company, but not all identities can be directly matched. For example, a company may use different registration numbers for historical reasons, but these numbers actually point to the same company. In this case, it is necessary to make a comprehensive judgment based on other information of the company (such as establishment time, business scope, equity structure, etc.) to determine whether there is an actual connection. Determine the value of the relationship flag based on the connection between the two company identities. If the two identities point to the same company, the relationship flag is set to 1; otherwise, it is set to 0.

[0045] Prioritize: This is used to indicate the importance of a combination of enterprise identities. Based on business needs and data characteristics, determine which combination of enterprise identity types should be considered more reliable or more important when processing enterprise identity relationships, and set the corresponding priority.

[0046] The data source is used to indicate the financial institution to which the certificate relationship data belongs, such as financial institutions A, B, and C in Table 1 above.

[0047] After the mapping is completed, the data in Table 1 is organized into a document relationship set, which contains all enterprise identity identifiers and the relationships between them.

[0048] Step S120: construct a topological graph according to the document relationship set, traverse the topological graph using a depth-first traversal algorithm, integrate the corporate identity identifiers belonging to the same enterprise, and obtain an integration result.

[0049] After standardizing the certificate relationship data, the certificate relationship set is obtained. The certificate relationship set needs to be input into the decision algorithm for calculation in order to realize the integration of corporate identity. The decision algorithm of the present invention is implemented on the basis of the depth first search algorithm (DFS). The depth first search algorithm is an important mathematical algorithm in graph theory, and is widely used in topological sorting, path finding, search engines, crawlers, etc. in production. Starting from the initial access node, the initial access node may have multiple adjacent nodes. The strategy of depth first traversal is to first visit the first adjacent node, and then use this visited adjacent node as the initial node to visit its first adjacent node. It can be understood as follows: each time after visiting the current node, the first adjacent node of the current node is visited first. In order to facilitate understanding, it is necessary to introduce the concepts of edges of equal relationships (hereinafter referred to as equal edges), edges of unequal relationships (hereinafter referred to as unequal edges), nodes, etc.

[0050] The above equal sides are used to indicate that the two enterprise identity identifiers constitute a certificate relationship of the same enterprise. The unequal sides are used to indicate that the two enterprise identity identifiers constitute a certificate relationship of not the same enterprise.

[0051] The above nodes are corporate identity tags, and the two corporate identities in equal or unequal sides become nodes.

[0052] The present invention uses a depth-first traversal algorithm to traverse the topology graph. During the traversal process, the algorithm will record the nodes that have been visited (i.e., enterprise identities) and avoid repeated visits. Through DFS traversal, according to the results of the DFS traversal, the enterprise identities belonging to the same enterprise are integrated and the integration result is output. The integration result can be a database, a data table, or a visualized graph or tree structure containing enterprise identities and their relationships.

[0053] The method for integrating corporate subject identity provided by the present invention first obtains the certificate relationship data submitted by multiple financial institutions and performs standardized processing. This step reduces the complexity of the subsequent matching process by unifying the data format and standard, thereby improving the matching efficiency. A topological map is constructed according to the certificate relationship set, and the constructed topological map is traversed using the depth-first traversal algorithm to integrate the corporate identity identifiers belonging to the same enterprise, so as to obtain the integration result of all corporate identity identifiers. The depth-first traversal algorithm is highly efficient and can complete the traversal and integration of large-scale data within a limited time. The problem of large amount of calculation and low matching efficiency of the existing corporate subject identity integration method is solved. At the same time, the method of the present invention reduces the link of human intervention by obtaining data submitted by multiple financial institutions and using an algorithm for automatic processing. This helps to reduce the problem of inaccurate preset similarity indicators and relevance thresholds caused by human factors.

[0054] The present invention is based on multiple data sources such as the relationship data between two corporate identity identifiers reported by various financial institutions, agrees on the priority of document relationships, and develops intelligent algorithms for automated decision-making, thereby achieving the goal of integrating corporate identity identifiers. The ultimate goal of integrating corporate identity identifiers is to determine which corporate identity identifiers are classified as one company through the relationship data between two corporate identity identifiers. By integrating different corporate identity identifiers, data redundancy can be eliminated, and the same company can be prevented from having multiple different identity identifiers, resulting in data confusion. The integrated corporate identity identifier data can remain consistent in all related systems to ensure the accuracy and reliability of the data. By integrating corporate identity identifiers, security vulnerabilities and risks caused by multiple identity identifiers can be reduced, and data security can be improved.

[0055] In an optional embodiment, the topological graph is constructed according to the document relationship set in the above step S120, and the topological graph is traversed using a depth-first traversal algorithm to integrate the corporate identity identifiers belonging to the same enterprise to obtain an integration result, including: S1201. Construct a topological graph according to the document relationship set. Specifically, each enterprise identity in the document relationship set is used as a node of the topological graph, and edges between nodes are constructed according to the relationship data between two enterprise identity identifiers. If two enterprise identity identifiers are judged to belong to the same enterprise, equal edges are constructed; if two enterprise identity identifiers are judged not to belong to the same enterprise, unequal edges are constructed.

[0056] In Table 1, each unique corporate identity will be considered as a node in the topology graph. If two corporate identities are marked as documents of the same company in Table 1, an edge is drawn between them. This means that the two identities actually point to the same company. The process of building the topology graph is as follows: Based on the corporate identities in Table 1, create a set of nodes. Each node represents a unique corporate identity. For each pair of corporate identities marked as the same company in Table 1, add an equal edge connecting the two nodes in the topology graph. For each pair of identities marked as not the same company in Table 1, add an unequal edge connecting the two nodes in the topology graph.

[0057] In the topology graph, an association path is any path that connects two nodes that are connected by unequal edges. These paths are indirectly connected through other nodes (i.e., other corporate identities). When building a topology graph, you do not need to explicitly draw all possible association paths, but you should ensure that the structure of the graph allows for these paths to exist. Ensure that each node and edge in the topology graph is consistent with the information in Table 1. Verify that the topology graph correctly represents all document relationships in Table 1, ensuring that there are no missing nodes or edges, and that the connectivity of the graph reflects the actual corporate identity relationships. The layout of nodes and edges in the topology graph can be adjusted to improve readability. Use appropriate drawing tools to optimize the display of the graph to make it clearer and easier to understand. The topology graph constructed based on the set of document relationships in Table 1 can clearly represent the equal and unequal relationships between corporate identities.

[0058] S1202, traversing the topological graph, and for each unequal edge, retrieving all the corresponding associated paths; wherein the associated path is any path connecting two nodes of the unequal edge, and the path includes other nodes and edges.

[0059] Retrieve all the associated paths corresponding to each unequal edge in the topology graph. These associated paths are paths connecting two nodes of the unequal edge, which are indirectly connected through other nodes (i.e. other corporate identities). The purpose of this step is to find all possible paths that connect two nodes of the unequal edge, so as to facilitate subsequent edge removal and integration.

[0060] S1203: For each unequal edge, perform edge removal processing on the associated path corresponding to the unequal edge according to a preset edge removal rule to obtain a topological graph after edge removal processing.

[0061] Traverse each unequal edge in the topology graph and determine whether the edges in each associated path of the unequal edge need to be split according to the preset edge splitting rules. If splitting is required, these edges can be marked in the graph (for example, using different colors or line types) or deleted from the graph. Based on the marking or deletion operation in the previous step, the structure of the topology graph is updated. The topology graph after edge splitting is shown in the figure below. Figure 6 shown.

[0062] S1204: Integrate enterprise identities belonging to the same enterprise according to the edges and nodes in the topological graph after the edge removal process to obtain an integration result.

[0063] Map the split edge result of each unequal edge in the above topological graph, that is, mark the split edges of each unequal edge in the topological graph to obtain an updated topological graph. Traverse the updated topological graph, and in the traversal process, identify the node sets of all unsplit edges, which are called connected components. The corporate identities represented by the nodes in each connected component belong to the same company. For each connected component, integrate all corporate identities in it into a list, or store them in a record in the database. Generate a list or database containing all corporate identities and their relationships. Output the integration results in an appropriate format (such as a CSV file, Excel file, or database table), and store them in a specified location for subsequent use.

[0064] The present invention can ensure that each enterprise identity is correctly identified and integrated by traversing the topology map through the depth-first traversal algorithm. This helps to avoid missing or misidentifying enterprise identities, thereby improving the accuracy of the integration results. The depth-first traversal algorithm is an efficient traversal algorithm that can complete the traversal and integration of the entire topology map in a relatively short period of time. This helps to save time and resources and improve the efficiency of the integration process. By constructing a topology map and retrieving associated paths, the process can support the analysis of complex enterprise identity relationships. This helps to discover potential associations and connections, providing strong support for subsequent decisions and actions.

[0065] In an optional embodiment, before performing edge removal processing on each associated path corresponding to each unequal side in step S1202, the method further includes: Identify the priority of each unequal edge, sort all the unequal edges according to their priority, and determine the execution order of edge removal processing for the associated path corresponding to each unequal edge according to the sorting result of the priority of the unequal edges.

[0066] Before starting the edge splitting process, you first need to identify all the unequal edges. Sort the priorities of all the unequal edges. The purpose of sorting is to determine the execution order of the edge splitting process, that is, which associated paths corresponding to the unequal edges should be processed first and which ones should be processed later. The specific methods of sorting can include ascending sorting, descending sorting, or sorting according to a certain custom rule. According to the priority sorting results of the unequal edges, the execution order of the edge splitting process can be determined.

[0067] The present invention is explained by giving priority to the associated paths corresponding to unequal sides with higher priorities. By first processing the associated paths corresponding to unequal sides with higher priorities, the expected edge removal effect can be achieved more quickly, reducing unnecessary calculations and resource consumption. By determining the execution order of edge removal processing according to the priority of the unequal sides, a more flexible edge removal strategy can be supported. For example, the priority and sorting rules of unequal sides can be dynamically adjusted according to business needs or data analysis results. When processing a large amount of complex enterprise identity association data, by first processing the associated paths corresponding to unequal sides with higher priorities, it is possible to more effectively deal with anomalies or noise in the data and improve the robustness and stability of data processing.

[0068] In an optional embodiment, the associated path is debonded in the following manner: S210: Identify the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path.

[0069] In the process of constructing the topology graph, the edges in the topology graph are assigned corresponding attributes according to the priority information in Table 1. For example, a priority attribute can be set for each edge, and its value is set to the corresponding priority in Table 1. Based on the topology graph that has been integrated with the priority, all associated paths are identified. These paths are composed of nodes and the edges connecting them. For each edge in the unequal edges and associated paths, its corresponding priority is obtained.

[0070] S220 , generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path.

[0071] According to business logic or predefined rules, set the splitting rules for edges of different priorities. These rules may include splitting low-priority edges first, retaining high-priority edges, or splitting to different degrees according to the priority differences of edges. Based on the set splitting rules and the priority of each edge, a split marker is generated for each edge in the associated path. This marker can be a binary value (such as 0 for no split and 1 for split), or a more complex value indicating the degree of splitting or priority.

[0072] S230: Determine whether two enterprise identities connected by the edge are split or merged according to the split mark.

[0073] According to the splitting marks of all edges in the association path, it can be determined which enterprise identities should be split and which should be merged. The splitting marks of each edge are parsed to determine which edges should be split and which edges should be retained. When the splitting mark is split, the corresponding enterprise identity is split; when the splitting mark is not split, the corresponding enterprise identity is merged. According to the parsing results, the splitting operation is performed on the edges in the association path. This involves disconnecting low-priority edges, retaining high-priority edges, or performing more complex splitting and merging operations according to the specific values ​​of the splitting marks. After the splitting operation, a topological graph after splitting is generated, which describes the splitting and merging of enterprise identities in the association path and reflects the application effect of priority information in edge splitting. Through this process, the topological graph data that incorporates priority information can be more effectively managed and utilized, and accurate edge splitting processing can be performed to meet the needs of business logic and data analysis.

[0074] The present invention can more effectively manage a large amount of complex enterprise identity-related data and reduce data redundancy and computational burden through edge splitting processing. Edge splitting processing can perform precise operations based on the priority of the edge to ensure that important and critical associations are retained, while secondary or redundant associations are effectively removed. By generating a split mark for each edge, the reasons and basis for the edge splitting results can be more easily explained, thereby improving the transparency and credibility of the data. Edge splitting processing provides a more flexible foundation for subsequent data analysis, mining, and visualization, enabling customized data processing and display according to user needs. The present invention can realize the integration of scattered enterprise identities, split the enterprise identities that have been incorrectly integrated from the original enterprise, and integrate the newly generated enterprise identities into the original enterprise.

[0075] In an optional embodiment, a split mark is generated for each edge in the association path. This mark will be based on two key factors: first, the relative relationship of the priorities of all edges in the association path, and second, the comparison result of each edge's priority with the unequal edge priorities. This process is intended to help identify which edges become split points in the subsequent edge splitting process.

[0076] The step S220 described above, generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path, can be implemented in the following manner: A splitting mark of each edge in the association path is generated according to the relative relationship of the priorities of all the edges in the association path and the relative relationship between the priority of each edge in the association path and the priority of the unequal edges.

[0077] First, it is necessary to collect the priority information of all edges in the association path, including the priority of each edge and the priority of unequal edges. This information comes from the previous analysis step or the data normalization stage. Next, analyze the relative relationship of the priorities of all edges in the association path. This includes comparing the priority differences between equal edges and the priority relationship between these edges and unequal edges. Based on the above analysis, a split mark is generated for each edge. This mark can be a binary value (such as 0 or 1, indicating split or not split), or a more complex encoding (such as a color code or classification label), depending on the needs of subsequent processing. The logic for generating split marks can be based on a series of rules and thresholds. For example, if the priority of an edge is lower than that of unequal edges, then this edge may be marked as an edge that needs to be split. If all edges in the association path have the same priority, then there is no need to split because these edges represent the same corporate identity.

[0078] The present invention can more accurately identify which edges are more likely to become split points by comprehensively considering the relative relationship of the priorities of the edges in the associated path and the comparison results with the priorities of the unequal edges. This helps to reduce the situation of mistaken splitting or missed splitting and improve the accuracy of splitting. The split mark not only provides a basis for edge splitting, but also can be used as input information for subsequent analysis. For example, when integrating corporate identity identifiers and their relationships, split marks can be used to identify and handle potential conflicts or inconsistencies, thereby providing more accurate and reliable data support for subsequent tasks such as corporate association analysis and risk identification.

[0079] In an optional embodiment, the step S220 described above, generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path, includes: (1) If the priorities of all equal edges in the associated path are the same, and the priorities of all edges are less than or equal to the priority of the unequal edge, then the split marks of all edges in the associated path are determined to be split; (2) If the priorities of all equal edges in the associated path are the same, and the priorities of all edges are greater than the priority of the unequal edge, the split marks of all edges in the associated path are determined to be not split.

[0080] (3) When the priorities of all equal edges in the associated path are not exactly the same, compare the priority of the target edge with the priority of the unequal edges. If the priority of the target edge is less than or equal to the priority of the unequal edges, the split mark of the target edge is determined to be split, and the split marks of the other edges are determined to be not split; if the priority of the target edge is greater than the priority of the unequal edges, the split marks of all edges in the associated path are determined to be not split; among them, the target edge is the edge with the lowest priority in the associated path, and the other edges are the edges in the associated path except the target edge.

[0081] First, compare the priorities of all equal edges in the associated path to see if they are the same. If all equal edges have the same priority, proceed to the next step of comparison. Compare the priorities of all edges with those of unequal edges.

[0082] In the case where all equal edge priorities are the same, compare the priorities of these edges with the priorities of unequal edges. If the priorities of all edges are less than or equal to the priorities of unequal edges, then it is considered that these edges are relatively weak in logic and may be more likely to be affected or conflicted by unequal edges. Therefore, all edges in the associated path are marked as split. On the contrary, if the priorities of all edges are greater than the priorities of unequal edges, then these edges are relatively strong in logic and are less likely to be affected by unequal edges. Therefore, all edges in the associated path are marked as not split.

[0083] If the priorities of all equal edges in the association path are not exactly the same, further analysis is required. In this case, find the minimum value among the priorities of all edges in the association path, which is called the target priority, and the corresponding edge is called the target edge. Then, compare the priority of the target edge with the priority of the unequal edge. If the priority of the target edge is less than or equal to the priority of the unequal edge, then the target edge may be more likely to be affected or conflicted by the unequal edge, so the target edge is marked as split, and the other edges are marked as not split. If the priority of the target edge is greater than the priority of the unequal edge, then the entire association path is relatively strong in logic and is unlikely to be affected by the unequal edge. Therefore, all edges in the association path are marked as not split.

[0084] The present invention can more accurately identify which edges are more logically susceptible to the influence or conflict of unequal edges by comprehensively considering the priority of equal edges and the priority relationship between each edge and unequal edges, thereby making more reasonable splitting decisions. The process provides a set of clear rules and logic, making the edge splitting process more intuitive and easy to understand. This helps to reduce the impact of human errors and subjective judgments and improve processing efficiency. Through reasonable splitting processing, conflicts and inconsistencies in association paths can be reduced, thereby enhancing the consistency and reliability of data. This is crucial for subsequent enterprise association analysis, risk identification and other tasks. The process allows the splitting strategy to be customized according to different business needs and data characteristics. For example, the rules or thresholds for priority comparison can be adjusted according to actual conditions to adapt to different application scenarios.

[0085] In order to better explain the logic of the algorithm, the method of integrating the corporate entity identity of the present invention is described through a specific example. The flowchart is shown in FIG. Figure 3 As shown in the figure, A, B, C, D, E, F, G, H, I, and J represent 10 nodes, among which there are equal edges between the 10 nodes. At the same time, there are unequal edges AH with a priority of 1 and CI with a priority of 3, forming a relationship topology diagram as shown in the figure below. Figure 4 shown.

[0086] Step 1: Sort the unequal edges in the document relationship set from high to low priority. Loop through each unequal edge and find all associated paths that can connect the two nodes based on the two nodes of each unequal edge. Since there are two unequal edges "AH" and "CI" in the document relationship set, and the priority of the "AH" edge is higher than that of the "CI" edge, first retrieve all associated paths that can connect point "A" to point "H" (that is, unequal edges AH) from the topology graph, such as Figure 5 shown.

[0087] The search results show a total of 10 associated paths, the specific paths are as follows: The first path: A->B->D->E->F->H; The second path: A->B->D->E->F->G->H; The third path: A->B->D->E->F->G->J->H; The fourth path: A->B->D->E->F->J->H; The fifth path: A->B->D->E->F->J->G->H; The sixth path: A->B->C->E->F->H; The seventh path: A->B->C->E->F->G->H; The eighth path: A->B->C->E->F->G->J->H; Path 9: A->B->C->E->F->J->H; The tenth path: A->B->C->E->F->J->G->H.

[0088] Step 2: Perform edge splitting operation on the associated path retrieved in the first step, specifically identifying the priority of each edge in the associated path, and marking whether all edges in the associated path are split according to the priority, such as Figure 6 shown.

[0089] Find the edge with the lowest priority from the 10 paths one by one and compare it with the priority of the "AH" edge. The following results are obtained.

[0090] The result of edge removal on the first path: the DE edge and the FH edge are removed; The result of edge removal on the second path: the DE edge and the GH edge are removed; The result of edge removal on the third path: edge DE is removed; The result of edge removal on the fourth path: the DE edge and the FJ edge are removed; The result of edge removal on the fifth path: DE edge, FJ edge, and GH edge are removed; The result of edge removal on the sixth path: the FH edge is removed; Result of edge removal on the seventh path: GH edge is removed; The result of edge removal on the eighth path: BC edge, CE edge, EF edge, FG edge, and JH edge are removed; The result of edge removal on the ninth path: the FJ edge is removed; The result of edge removal on the tenth path: FJ edge and GH edge are removed; Step 3: Based on the unequal CI, retrieve all associated paths that can connect point "C" to point "I", such as Figure 7 shown.

[0091] The search results have 2 associated paths, the specific paths are as follows: The first path: C->B->D->E->I; The second path: C->E->I.

[0092] Step 4: Perform edge removal operation on the associated path retrieved in step 3, such as Figure 8 As shown: From the two associated paths, find the edge with the lowest priority and compare it with the priority of the CI split edge. The following results are obtained.

[0093] The result of edge removal on the first path: the DE edge is removed; The result of edge removal on the second path: no edge removal.

[0094] Step 5: Calculate the decision result based on the splitting results of the second and fourth steps, and determine the splitting and merging of the corporate identity based on the splitting mark. Fig. 9 shown.

[0095] The final integration result is as follows: {A, B, D}, {C}, {E, I}, {F}, {G, J}, {H}. That is, the corporate identity A, B, D are the same company, C is a separate company, E and I are the same company; F is a separate company, G and J are the same company, and H is a separate company.

[0096] The device for integrating the enterprise subject identity provided by the present invention is described below. The device for integrating the enterprise subject identity described below and the method for integrating the enterprise subject identity described above can be referenced to each other.

[0097] The device for integrating the corporate entity identity provided by the present invention refers to Fig.10 As shown, including: The processing module 310 is used to obtain the certificate relationship data submitted by each financial institution, and perform standardization processing on the certificate relationship data of all financial institutions to obtain a certificate relationship set; wherein the certificate relationship data submitted by each financial institution belongs to the same or different enterprise identity combination, and the certificate relationship data is the relationship data between two enterprise identity identifiers; The traversal module 320 is used to construct a topological graph according to the document relationship set, traverse the topological graph using a depth-first traversal algorithm, integrate the enterprise identities belonging to the same enterprise, and obtain an integration result.

[0098] Fig.11 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.11 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the method for integrating the corporate subject identity.

[0099] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0100] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method of integrating the enterprise entity identity provided by the above methods.

[0101] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the method for integrating the corporate entity identity provided by the above methods.

[0102] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0103] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for integrating corporate entity identity identification, characterized in that: include: Obtain the certificate relationship data submitted by each financial institution, perform standardization on the certificate relationship data of all financial institutions, and obtain a certificate relationship set; wherein the certificate relationship data submitted by each financial institution belongs to the same or different enterprise identity identifier combinations, and the certificate relationship data is the relationship data between two enterprise identity identifiers; A topological graph is constructed according to the document relationship set, and the topological graph is traversed using a depth-first traversal algorithm to integrate corporate identity identifiers belonging to the same enterprise to obtain an integration result.

2. The method for integrating corporate entity identity according to claim 1, characterized in that: The step of constructing a topological graph according to the document relationship set, traversing the topological graph using a depth-first traversal algorithm, and integrating the enterprise identities belonging to the same enterprise to obtain an integration result includes: Each enterprise identity in the document relationship set is used as a node of the topological graph, and edges between nodes are constructed according to the relationship data between the enterprise identity identifiers; if the two enterprise identity identifiers are judged to belong to the same enterprise, equal edges are constructed; if the two enterprise identity identifiers are judged not to belong to the same enterprise, unequal edges are constructed; Traversing the topological graph, for each unequal edge, retrieving all the corresponding associated paths; wherein the associated path is any path connecting two nodes of the unequal edge, and the path includes other nodes and edges; For each unequal edge, the associated path corresponding to the unequal edge is debonded according to the preset debonding rule to obtain a topological graph after debonding; According to the edges and nodes in the topological graph after the edge removal process, the enterprise identities belonging to the same enterprise are integrated to obtain an integration result.

3. The method for integrating corporate entity identity according to claim 2, characterized in that: The associated path is debonded in the following way: Identifying the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path; Generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path; Whether the two corporate identities connected by the edge are split or merged is determined according to the split mark; when the split mark is split, the corresponding corporate identity is split; when the split mark is not split, the corresponding corporate identity is merged.

4. The method for integrating corporate entity identity according to claim 3, characterized in that: Generating a split mark for each edge in the association path according to the priority of the unequal edges corresponding to the association path and the priority of each edge in the association path includes: If the priorities of all equal edges in the associated path are the same, and the priorities of all edges are less than or equal to the priority of the unequal edge, then the split flags of all edges in the associated path are determined to be split; If the priorities of all equal edges in the associated path are the same, and the priorities of all edges are greater than the priority of the unequal edge, the splitting marks of all edges in the associated path are determined to be not split; When the priorities of all equal edges in the associated path are not exactly the same, compare the priority of the target edge with the priority of the unequal edges. If the priority of the target edge is less than or equal to the priority of the unequal edges, the split mark of the target edge is determined to be split, and the split marks of other edges are determined to be not split; if the priority of the target edge is greater than the priority of the unequal edges, the split marks of all edges in the associated path are determined to be not split; among them, the target edge is the edge with the smallest priority in the associated path, and the other edges are the edges in the associated path except the target edge.

5. The method for integrating corporate entity identity according to claim 2, characterized in that: Before performing edge removal processing on the associated paths corresponding to each unequal edge according to a preset edge removal rule, the method further includes: Identify the priority of each unequal side and sort all unequal sides according to their priority; According to the sorting result of the priorities of the unequal edges, the execution order of performing edge removal processing on the associated paths corresponding to each unequal edge is determined.

6. The method for integrating corporate entity identity according to claim 1, characterized in that: The document relationship data is standardized in the following ways: For each certificate relationship data submitted by a financial institution, it is mapped to the corresponding fields of a pre-established standardized format according to its content; wherein, the standardized format includes a first enterprise identity type, a first enterprise identity number, a first enterprise identity name, a second enterprise identity type, a second enterprise identity number, a second enterprise identity name, a relationship flag, a priority and a data source, the relationship flag is used to indicate whether two enterprise identities point to the same enterprise, the priority is used to indicate the importance of the enterprise identity combination, and the data source indicates the financial institution to which the certificate relationship data belongs.

7. A device for integrating corporate entity identity identification, characterized in that: include: A processing module is used to obtain the certificate relationship data submitted by each financial institution, perform standardization processing on the certificate relationship data of all financial institutions, and obtain a certificate relationship set; wherein the certificate relationship data submitted by each financial institution belongs to the same or different enterprise identity identifier combinations, and the certificate relationship data is the relationship data between two enterprise identity identifiers; The traversal module is used to construct a topological map according to the document relationship set, traverse the topological map using a depth-first traversal algorithm, integrate the enterprise identity identifiers belonging to the same enterprise, and obtain an integration result.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for integrating enterprise entity identity identification as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for integrating enterprise entity identity identification as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for integrating enterprise entity identity identification as claimed in any one of claims 1 to 6 is implemented.

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