CN111861120A - Method, device and equipment for constructing enterprise association map and computer readable medium - Google Patents

Method, device and equipment for constructing enterprise association map and computer readable medium Download PDF

Info

Publication number
CN111861120A
CN111861120A CN202010556321.5A CN202010556321A CN111861120A CN 111861120 A CN111861120 A CN 111861120A CN 202010556321 A CN202010556321 A CN 202010556321A CN 111861120 A CN111861120 A CN 111861120A
Authority
CN
China
Prior art keywords
association
target
enterprise
enterprises
nodes
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010556321.5A
Other languages
Chinese (zh)
Other versions
CN111861120B (en
Inventor
贺敏
杜慧
董琳
郭富民
杨菁林
徐小磊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Institute of Computing Technology of CAS
National Computer Network and Information Security Management Center
Original Assignee
Institute of Computing Technology of CAS
National Computer Network and Information Security Management Center
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Institute of Computing Technology of CAS, National Computer Network and Information Security Management Center filed Critical Institute of Computing Technology of CAS
Priority to CN202010556321.5A priority Critical patent/CN111861120B/en
Publication of CN111861120A publication Critical patent/CN111861120A/en
Application granted granted Critical
Publication of CN111861120B publication Critical patent/CN111861120B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Economics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Strategic Management (AREA)
  • General Physics & Mathematics (AREA)
  • Educational Administration (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Operations Research (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Game Theory and Decision Science (AREA)
  • Development Economics (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The application relates to a method, a device, equipment and a computer readable medium for constructing an enterprise association map. The method comprises the following steps: acquiring a target data set, wherein the target data set comprises data of a plurality of target enterprises, and each piece of data comprises the associated characteristics of one target enterprise; dividing enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group; establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to the association types; and determining the association strength of the association edge by using the association coefficient and the association weight. The method and the device realize the construction of the enterprise association map, utilize the enterprise association map to express various association relations existing among enterprises and association strength among the enterprises, and provide a foundation for the evaluation of risk propagation among the enterprises.

Description

Method, device and equipment for constructing enterprise association map and computer readable medium
Technical Field
The present application relates to the technical field of enterprise risk assessment, and in particular, to a method, an apparatus, a device, and a computer-readable medium for constructing an enterprise association graph.
Background
With the rapid development of modern society, the threshold of registering and investing enterprises is greatly reduced, and a large number of enterprises are pulled out, wherein a plurality of enterprises have a plurality of associated responsibility relations, and the enterprises are not independent individuals and have a certain relation with personnel and other enterprises. The enterprises are related through the association relationship of the enterprises such as investment control, personnel employment and the like, the association can be direct association or indirect association through other enterprises or personnel, a plurality of enterprises are interwoven through the explicit or implicit association, and the complex interwoven association also brings the spread of risks among the enterprises. For example, some enterprises have high risk such as fund breakage, bond breach and the like because some enterprises are subjected to some illegal activities and are investigated by police, industrial and commercial administration departments, and other enterprises related to the enterprises may participate in related operation activities or have benefits transmitted, which may result in risks such as fund loss caused by fund breakage of risky enterprises and suspected crimes of personnel.
At present, in the related technology, emotion tendency analysis is performed according to internet texts, so that risks existing in an enterprise are evaluated, but at present, a representation scheme of incidence relations among the enterprises is lacked, so that the influence of risk propagation on the enterprise cannot be evaluated more accurately from the perspective of the incidence relations among the enterprises.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The application provides a method, a device, equipment and a computer readable medium for constructing an enterprise association map, so as to solve the technical problem of 'lack of representation of association relationship among enterprises'.
In a first aspect, the present application provides a method for constructing an enterprise association graph, including: acquiring a target data set, wherein the target data set comprises data of a plurality of target enterprises, and each piece of data in the target data set comprises an associated characteristic of one target enterprise; dividing enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group, wherein the target enterprises in one enterprise group at least have one same association characteristic; establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to association types, wherein the association types represent association relations among the target enterprises due to the fact that the target enterprises have the same association characteristics; and determining the association strength of the association edge by utilizing an association coefficient and an association weight, wherein the association coefficient is used for representing the contribution degree of the association type matched with the association coefficient to risk conduction, and the association weight is used for representing the closeness of the association relation between enterprises with the association type.
Optionally, before obtaining the target data set, determining the association type, the association coefficient, and the association weight according to the following manner: determining the type of the incidence relation between the target enterprises with the incidence characteristics as an incidence type; and determining the correlation coefficient and the correlation weight corresponding to each correlation type according to the set parameters.
Optionally, constructing an association edge between nodes for a graph node in an enterprise group according to an association type includes: selecting a target enterprise group from the plurality of enterprise groups, wherein the type of the incidence relation between the target enterprises in the target enterprise group is a target incidence type; and establishing a target association type association edge between every two nodes in the target enterprise group in the map nodes, wherein the association edge comprises two reverse association edges which are in reverse relation with each other.
Optionally, after establishing an association edge of the target association type between every two nodes in the target enterprise group in the graph node, the method further includes establishing association edges between the nodes and nodes for nodes in other enterprise groups except the target enterprise group according to the following manner: in the case where no associated edge exists between any two graph nodes in other enterprise groups, an associated edge is constructed for the two graph nodes.
Optionally, in a case that there is no associated edge between any two graph nodes in other enterprise groups, after constructing associated edges for the two graph nodes, the method further includes constructing associated edges between nodes and graph nodes in multiple enterprise groups simultaneously as follows: determining each enterprise group to which different association characteristics belong under the condition that the association objects referred by the different association characteristics are the same association object; and under the condition that no association edge exists between any two map nodes in each enterprise group to which different association characteristics belong, constructing association edges for the two map nodes.
Optionally, the determining the association strength of the association edge by using the association coefficient and the association weight comprises: and determining the product of the correlation coefficient matched with the correlation type of the correlation edge and the correlation weight as the correlation strength of the correlation edge.
Optionally, the determining the association strength of the association edge by using the association coefficient and the association weight further includes: in the case where a plurality of association types exist for one association edge, the maximum value among the plurality of association strengths is determined as the association strength of the association edge.
In a second aspect, the present application provides an apparatus for constructing an enterprise association graph, including: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring a target data set, the target data set comprises data of a plurality of target enterprises, and each piece of data in the target data set is associated with one target enterprise; the grouping module is used for dividing the enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group, wherein the target enterprises in one enterprise group at least have one same association characteristic; the system comprises a construction module, a correlation module and a processing module, wherein the construction module is used for establishing map nodes for a plurality of target enterprises, and constructing correlation edges between the nodes for the map nodes in an enterprise group according to correlation types, and the correlation types represent the correlation relations among the target enterprises due to the same correlation characteristics; and the association strength determining module is used for determining the association strength of the association edge by utilizing an association coefficient and an association weight, wherein the association coefficient is used for representing the contribution degree of the association type matched with the association coefficient to risk conduction, and the association weight is used for representing the closeness of the association relation between the enterprises with the association type.
In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and the processor implements the steps of any one of the above methods when executing the computer program.
In a fourth aspect, the present application also provides a computer readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform any of the methods of the first aspect.
Compared with the related art, the technical scheme provided by the embodiment of the application has the following advantages:
the method comprises the steps of obtaining a target data set, wherein the target data set comprises data of a plurality of target enterprises, and each piece of data comprises an associated characteristic of one target enterprise; dividing enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group; establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to the association types; and determining the association strength of the association edge by using the association coefficient and the association weight. The method realizes the construction of the enterprise association map, expresses various association relations among enterprises and the association strength among the enterprises by using the enterprise association map, and provides a foundation for the evaluation of risk propagation among the enterprises.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the technical solutions in the embodiments or related technologies of the present application, the drawings needed to be used in the description of the embodiments or related technologies will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without any creative effort.
Fig. 1 is a hardware environment diagram of an alternative method for constructing an enterprise association graph according to an embodiment of the present application;
FIG. 2 is a flowchart of an alternative method for constructing an enterprise association graph according to an embodiment of the present application;
fig. 3 is a block diagram of an alternative apparatus for constructing an enterprise association graph according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for the convenience of description of the present application, and have no specific meaning in themselves. Thus, "module" and "component" may be used in a mixture.
In the related art, emotion tendency analysis is performed according to internet texts, so that risks existing in an enterprise are evaluated, but the enterprise is not a completely independent individual and has a certain association with people and other enterprises. The enterprise and the enterprise have various associations, such as investment relationships, corporate relationships and the like, which may be direct associations or indirect associations through other enterprises or persons, and a plurality of enterprises are interwoven through the explicit or implicit associations, and it is the complex interwoven association that brings spread of risks among the enterprises. When an individual enterprise is investigated by a public security organization, a business administration department or the like because of some illegal activities, or high-risk situations such as fund breakage, bond default and the like occur, the enterprise is called an inauguration enterprise. The enterprises associated with these inauguration enterprises may participate in the operations of the inauguration enterprises, the beneficial delivery to the inauguration enterprises, etc., and may be at risk of capital loss due to capital breakdown of the inauguration enterprises, criminal suspicion of personnel, etc., and thus the enterprises associated with the inauguration enterprises may also have certain risks. From a risk propagation perspective, the closer the association to the risky enterprise, the higher the risk of the enterprise. Under the recognition, the technical scheme of the application constructs the enterprise association map based on the business association relationship, provides the knowledge map for describing direct connection and indirect connection between enterprises through various association relationships, distinguishes and comprehensively considers various association relationships between the enterprises from the risk propagation angle, and finally determines the association strength, so that a knowledge base is provided for the evaluation of enterprise risk propagation.
According to an aspect of the embodiments of the present application, an embodiment of a method for constructing an enterprise association graph is provided.
Alternatively, in the embodiment of the present application, the method described above may be applied to a hardware environment formed by the terminal 101 and the server 103 as shown in fig. 1. As shown in fig. 1, a server 103 is connected to a terminal 101 through a network, which may be used to provide services for the terminal or a client installed on the terminal, and a database 105 may be provided on the server or separately from the server, and is used to provide data storage services for the server 103, and the network includes but is not limited to: wide area network, metropolitan area network, or local area network, and the terminal 101 includes but is not limited to a PC, a cell phone, a tablet computer, and the like.
The method for constructing an enterprise association graph in the embodiment of the present application may be executed by the server 103, or may be executed by both the server 103 and the terminal 101, as shown in fig. 2, the method may include the following steps:
step S202, a target data set is obtained, the target data set comprises data of a plurality of target enterprises, and each piece of data in the target data set comprises an associated characteristic of one target enterprise.
In the embodiment of the present application, the target data set may be a data set including a large amount of enterprise information, and preferably, the embodiment of the present application is described as an industrial and commercial data set, and denoted by D. Each piece of data D in the industrial and commercial data set D may include the name of the enterprise, the legal person, the natural person stockholder, the high management, the contact telephone, the contact mailbox, the enterprise and investment proportion of the enterprise investment, the enterprise and stock control proportion of the enterprise control, and the like. The corporate, the natural person stockholders, the high-level management, the contact telephone, the contact mailbox and the like can be used as the association features, and under the condition of possessing the same association features, the association relationship exists between the enterprises with the same association features, if the enterprise A and the enterprise B possess the common natural person stockholder, the association relationship exists between the enterprise A and the enterprise B, and the association features are the common natural person stockholder. For another example, if a person is a legal person of enterprise a and a high management of enterprise B, there is an association relationship between enterprise a and enterprise B, and the association feature is legal person and high management.
Step S204, dividing the enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group, wherein the target enterprises in one enterprise group at least have one same association characteristic.
In the embodiment of the application, the association features can be grouped according to each association feature, one association feature serves as an enterprise group, that is, enterprises with the same association feature are combined into the same enterprise group, and because one enterprise has association features such as a legal person, a high-head stock, a natural person shareholder, a contact telephone, a contact mailbox and the like, one enterprise can be simultaneously divided into a plurality of enterprise groups, and all enterprises in the same enterprise group have at least one same association feature.
Optionally, note that N is an enterprise, p is a legal person, sp is a high management, vp is a natural stakeholder, h is a contact phone, and m is a contact mailbox, for example:
dividing enterprises according to the legal person, firstly counting the legal person in a data set D to obtain (p)1、p2…pn) Then, the enterprises of the same legal person are divided into a group, and then the legal person piA business represented by a human professional may be recorded as
Figure BDA0002544426260000071
All enterprises in the enterprise group have the same legal pi；
Dividing enterprises according to high management, and counting the high management in a data set D to obtain (sp) 1、sp2…spn) Dividing the same high-pipe enterprise into a group, then high-pipe spiAn enterprise in full-time management may be recorded as
Figure BDA0002544426260000072
All enterprises in the Enterprise group have the same high-pipe spi；
Dividing enterprises according to natural shareholders, and counting the natural shareholders in the data set D to obtain (vp)1、vp2…vpn) Dividing enterprises of the same natural shareholders into a group, so that vp of the natural shareholdersiAn enterprise represented by a natural stakeholder may be recorded as
Figure BDA0002544426260000073
All enterprises in the enterprise group have the same natural stakeholder vpi；
Dividing enterprises according to the contact calls, and counting the contact calls in the data set D to obtain (h)1、h2…hn) If the enterprises with the same contact number are divided into a group, the contact number is hiCan be recorded as
Figure BDA0002544426260000074
All enterprises in the enterprise group have the same contact number hi；
Dividing the enterprises according to the contact mailboxes, and counting the contact mailboxes in the data set D to obtain (m)1、m2…mn) If the enterprises in the same contact mailbox are divided into a group, the enterprises are contactedMail box is miCan be recorded as
Figure BDA0002544426260000075
All enterprises in the enterprise group have the same contact mailbox mi。
The grouping method aims at the condition of indirect association between enterprises, for example, the enterprises take personnel, telephone, mailbox and the like as the basis for establishing the association relationship, and the enterprises with the indirect association relationship are at least grouped into one enterprise group.
Optionally, in this embodiment of the application, direct association between enterprises may not be grouped, that is, an association between a target enterprise and an inauguration enterprise or between multiple target enterprises is a direct association such as investment and stock, such association characteristics of the direct association may not be grouped, or two directly associated enterprises may be individually used as a group to indicate that a direct association exists between the two enterprises. For example, if enterprise a holds stock for enterprise B, enterprise a invests in enterprise B, and the two are directly related to each other, the basis for establishing the association relationship does not depend on personnel, telephone, mailbox, and the like, and there is no direct association relationship between enterprise a and enterprise B owned by other enterprises at the same time, so that grouping is not required.
Step S206, establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to the association types, wherein the association types represent association relations among the target enterprises due to the fact that the target enterprises have the same association characteristics.
In the embodiment of the application, each enterprise is abstracted into nodes, directed edges, namely associated edges, between the nodes can be constructed by the nodes in the same enterprise group, the fact that association relationships exist between the enterprises with the same association characteristics is shown, the type of the association relationships, namely the type of the association characteristics is shown, the associated edges can be shown by E, and the association types can be shown by T kTo indicate. For example:
the enterprises are grouped according to the legal person, and then the enterprise N is established in one enterprise group of the same legal personiAnd NjAssociated edge E betweeni，jAnd Ej，iAssociated with type T (E)i，j) And T (E)j，i) Are all common legal people.
Grouping enterprises according to high management, and establishing an enterprise N in an enterprise group with the same high managementiAnd NjAssociated edge E betweeni，jAnd Ej，iAssociated with type T (E)i，j) And T (E)j，i) Are all "common high pipes".
Grouping enterprises according to natural shareholders, and establishing an enterprise N in an enterprise group with the same natural shareholdersiAnd NjAssociated edge E betweeni，jAnd Ej，iAssociated with type T (E)i，j) And T (E)j，i) All are "common natural stakeholders".
Grouping the enterprises according to the contact telephone, and establishing an enterprise N in an enterprise group with the same contact telephoneiAnd NjAssociated edge E betweeni，jAnd Ej，iAssociated with type T (E)i，j) And T (E)j，i) Are all "co-phones".
Grouping the enterprises according to the contact mailboxes, and establishing an enterprise N in an enterprise group with the same contact mailboxiAnd NjAssociated edge E betweeni，jAnd Ej，iAssociated with type T (E)i，j) And T (E)j，i) Are all "common mailboxes".
In the embodiment of the application, association edges between nodes can be established for nodes in different enterprise groups, for example, if there is a case that the corporate of some enterprises and the high administration of other enterprises are the same person, the enterprises with corporate and high administration as the same person can be associated, that is, two-way association edges are established between two nodes in which the corporate and the high administration are the same object in the sub-corporate and high administration groups.
In the embodiment of the application, in addition to establishing a relationship edge between every two indirectly related enterprises (namely, enterprises in an enterprise group, because of the existence of indirect association relationship established by personnel, telephone, mailbox and the like), the method establishes a relationship edge between every two indirectly related enterprises and controls investment and stockTwo enterprises in direct association of classes can directly build an association edge between the two enterprises. For example, Enterprise NiInvests in enterprise NjThen enterprise N may be establishediAnd NjAssociated edge E betweeni，jAnd Ej，i，Ei，jRepresents NiTo NjControlling strands, the direction of the associated edge being from NiPoint to NjAssociated with type T (E)i，j) To "stock control", Ej，iRepresents NjIs of NiThe direction of the associated edge is from NjPoint to NiAssociated with type T (E)j，i) Is "subsidiary".
In the embodiment of the present application, the association edge between nodes may be a bidirectional association edge, that is, N may be a bidirectional association edgeiPoint to NjIs shown as Ei，jMay also consist of NjPoint to NiIs shown as Ej，i。NiPoint to NjWhen is, represents NjIn association with type T (E)i，j) Lower acceptor NiOn the contrary, NjPoint to NiWhen is, represents NiIn association with type T (E)j，i) Lower acceptor NjThe influence of (c). It should be noted that, in the embodiment of the present application, the graph nodes and the enterprises are not distinguished, that is, the association relationship between the nodes and the influence between the nodes may be actually understood as the association relationship between the enterprises and the influence between the enterprises.
And step S208, determining the association strength of the association edge by using an association coefficient and an association weight, wherein the association coefficient is used for representing the contribution degree of the association type matched with the association coefficient to risk conduction, and the association weight is used for representing the closeness of the association relation between enterprises with the association type.
In the embodiment of the present application, the correlation coefficient may be used to represent the contribution degree of the correlation type of the correlation edge between two nodes to risk conduction, and is represented by Cor (T)k) Is shown as Cor (T)k)∈(0，1]. E.g. NiEnterprise to NjThe enterprise controls stocks by NiPoint to NjAssociated edge of Ei，j，NiAnd NjHas an association type T (E)i，j) For "straggling", the correlation coefficient Cor (T (E)i，j) Can be 1, corresponding, since NiEnterprise to NjEnterprise stock control, then NjEnterprises belong to NiSubsidiary of the enterprise, by NjPoint to NiAssociated edge of Ej，i，NjAnd NiHas an association type T (E)j，i) Is "subsidiary", the correlation coefficient Cor (T (E)j，i) ) may be 0.9. The association weight is used to represent the closeness of the association relationship between enterprises having an association type, and may be used
Figure BDA0002544426260000101
To indicate. E.g. NiEnterprise to NjThe enterprise controlling stock, then, associating the weight
Figure BDA0002544426260000102
May be NiTo NjIn the ratio of stock control, otherwise, NjEnterprises belong to NiSubsidiaries of an enterprise, associated weights
Figure BDA0002544426260000103
May be 1. The strength of association may be used to represent the probability that the current enterprise is affected by the risk of being passed (the risk of being passed), which may be denoted as S, and is denoted by NiTo NjPassing risk, i.e. associated edge, by NiPoint to NjThe strength of association can be expressed as
Figure BDA0002544426260000104
Indicates the association type as TkAssociated edge E ofi，jThe strength of the association.
In the embodiment of the present application, let NiAnd NjType of inter-relationship TkHas a strength of association of
Figure BDA0002544426260000105
The correlation strength may be determined by the product of the correlation coefficient and the correlation strength, i.e.:
Figure BDA0002544426260000106
in the embodiment of the application, a target data set is obtained, wherein the target data set comprises data of a plurality of target enterprises, and each piece of data comprises an associated characteristic of one target enterprise; dividing enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group; establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to the association types; the method for determining the association strength of the association edge by using the association coefficient and the association weight realizes that the enterprise association map is constructed by the nodes, the association edges between the nodes and the association weight of the association edge, so that the explicit or implicit association relationship between enterprises is represented by using the knowledge map, and the degree of closeness of the association relationship between the enterprises, namely the association strength, can be represented in detail, thereby constructing a foundation for the evaluation of enterprise risk propagation.
Optionally, before obtaining the target data set, the embodiment of the present application further includes determining the association type, the association coefficient, and the association weight according to the following manner: determining the type of the incidence relation between the target enterprises with the incidence characteristics as an incidence type; and determining the correlation coefficient and the correlation weight corresponding to each correlation type according to the set parameters.
In the embodiment of the application, the type of the association relationship between two enterprises can be determined according to the association characteristics between the two enterprises, and the type is used as the association type TkFrom the correlation type, the correlation coefficient Cor (T) corresponding to the correlation type can be confirmed according to the setting parameterk) And associated weights
Figure BDA0002544426260000111
In the embodiment of the present application, the setting parameters may be defined manually and obtained by the server or the terminal device, and preferably, the obtained setting parameters may be as shown in table 1.
TABLE 1
Figure BDA0002544426260000112
As can be seen from table 1, the association types of the association relationship between the enterprises may include 13 types, for example:
the directly related association types include two types, namely stock control and subsidiary company, T (E)i，j) Representing Enterprise N for "holdingsiInvests in enterprise Nj. "stock control" and "subsidiary" are in a reciprocal relationship, T (E)i，j) To "stock control", then T (E)j，i) Is a "subsidiaries" relationship.
The association type based on the personnel is a relation pair consisting of a legal person, a natural person stockholder, a high pipe and three types of personnel: (Fairman, Highcast), (Gangcast, Fairman), (Fairman, Natural man stockholder), (Natural man stockholder, Fairman), (Natural man stockholder, Gangcast), (Gangcast, Natural man stockholder), T (E)i，j) Is "common legal", it means enterprise NiAnd enterprise NjThere are common jurisdictions. T (E)i，j) "Fairman, high management", this means that the enterprise N isiThe legal person is simultaneously enterprise NjA high pipe. The relationship pairs of French, natural man, stockholder and high-tube are in inverse relationship, such as T (E)i，j) Is "(French, high pipe)", then T (E)j，i) Is a relationship of "(high pipe, legal)". The person-based association type in the embodiment of the present application belongs to an indirect association type.
Other types of associations indirectly associated are contact calls and contact mailboxes, T (E)i，j) Representing enterprise N for "common telephoneiAnd enterprise NjThere is a common contact phone.
Optionally, constructing an association edge between nodes for a graph node in an enterprise group according to an association type includes: selecting a target enterprise group from the plurality of enterprise groups, wherein the type of the incidence relation between the target enterprises in the target enterprise group is a target incidence type; and establishing a target association type association edge between every two nodes in the target enterprise group in the map node, wherein the association edge comprises two reverse association edges which are in reverse relation with each other.
In the embodiment of the application, an enterprise group can be selected first by constructing the association edges between the nodes, and the association edges are constructed between every two nodes in the enterprise group. The selected enterprise group is a target enterprise group, and the type of the association relationship among the enterprises in the group is a target association type.
In the embodiment of the application, as a preferred mode, an association type of one of a corporate identity, a corporate telephone and a common mailbox may be selected as a target association type, and an enterprise group corresponding to the target association type is performed as a target enterprise group.
Optionally, after establishing an association edge of the target association type between every two nodes in the target enterprise group in the graph node, the method further includes establishing association edges between the nodes and nodes for nodes in other enterprise groups except the target enterprise group according to the following manner: in the case where no associated edge exists between any two graph nodes in other enterprise groups, an associated edge is constructed for the two graph nodes.
In the embodiment of the application, after the establishment of the association edges between all the nodes in the target enterprise group, the association edges between the nodes in other enterprise groups may be established. Because an enterprise can be divided into a plurality of enterprise groups, nodes in a plurality of target enterprise groups are contained in other enterprise groups except the target enterprise group, and at the moment, a correlation edge is constructed for any two nodes without correlation edges between every two nodes in other enterprise groups. E.g. N 1、N2、N3Belonging to the same enterprise group and the association type T of the enterprise groupkIs "common legal", N1、N2、N3An associated edge is established between every two enterprises and another enterprise group comprises N2、N3、N4The association type T of the business groupkFor "common high pipe", the construction of the associated edge is to judge N2、N3There is an associated edge between them, so that it is no longer repeatedly constructed, N2、N4And N3、N4There is no associated edge between them, then it is N2、N4And N3、N4And constructing an associated edge between the two.
Optionally, in a case that there is no associated edge between any two graph nodes in the enterprise group, after constructing the associated edge for the two graph nodes, the method further includes constructing associated edges between the nodes and graph nodes in the multiple enterprise groups simultaneously according to the following manner: determining each enterprise group to which different association characteristics belong under the condition that the association objects referred by the different association characteristics are the same association object; and under the condition that no association edge exists between any two map nodes in each enterprise group to which different association characteristics belong, constructing association edges for the two map nodes.
In the embodiment of the application, the corporate, the high management and the natural person stockholder represent all real natural persons, and thus, there is a case where the corporate of the enterprise a serves as the high management of the enterprise B at the same time, and so on, and there is a case where the corporate, the natural person stockholder, the high management and the natural person stockholder coincide with each other. For example, an association type T for a business group kIs a "common person", the person is p1Another enterprise group is associated with type TkIs a "common high pipe", the high pipe is sp1If p is1And sp1If all the nodes are the same object, establishing associated edges for the nodes in the two enterprise groups pairwise. According to the method, if no association edge exists between every two adjacent pairs, the association edge is constructed.
Optionally, in this embodiment of the application, for two directly related enterprises, for example, two enterprises having a relationship of stock control and stock control may directly construct a related edge.
Optionally, the determining the association strength of the association edge by using the association coefficient and the association weight comprises: and determining the product of the correlation coefficient matched with the correlation type of the correlation edge and the correlation weight as the correlation strength of the correlation edge.
In the embodiment of the present application, after the association edges are constructed for all nodes in the target enterprise group, the corresponding association coefficient and the association weight are determined according to the association type between every two nodes, specifically referring to table 1 above, and the product of the association coefficient and the association weight is used as the association strength of the association edge.
And determining the association strength of other association edges in the same way, namely determining corresponding association coefficients and association weights according to the association types between every two nodes, and taking the product of the association coefficients and the association weights as the association strength of the association edges.
Optionally, the determining the association strength of the association edge by using the association coefficient and the association weight further includes: in the case where a plurality of association types exist for one association edge, the maximum value among the plurality of association strengths is determined as the association strength of the association edge.
In the embodiment of the application, since the association coefficients and the association weights corresponding to different association types are different from each other, if multiple association types exist between two nodes, the association strengths corresponding to the association types are respectively obtained, and one with the largest numerical value is selected as the final association strength of the association edge between the two nodes, for example, when the association strength of the association edge between the two nodes with a common high-ranking pipe is determined, if the association relationship of a common legal person exists between the two nodes, the corresponding association coefficient is 1 according to the association type of the common legal person, the association weight is 1, the association strength corresponding to the common legal person is 1 which is the product of the association coefficient and the association weight, meanwhile, the association coefficient corresponding to the common high-ranking pipe is obtained according to the association type of the common high-ranking pipe and is 0.4 which is the product of the association coefficient and the association weight, the association weight is 1 which is 0.4 which is the association strength corresponding to the common high-ranking pipe, and comparing the sizes of the two points, and finally determining that the association strength of the association edge between the two points is 1.
The method comprises the steps of obtaining a target data set, wherein the target data set comprises data of a plurality of target enterprises, and each piece of data comprises an associated characteristic of one target enterprise; dividing enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group; establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to the association types; and determining the association strength of the association edge by using the association coefficient and the association weight. The method realizes the construction of the enterprise association map, expresses various association relations among enterprises and the association strength among the enterprises by using the enterprise association map, and provides a foundation for the evaluation of risk propagation among the enterprises.
According to another aspect of the embodiments of the present application, as shown in fig. 3, there is provided an apparatus for constructing an enterprise association graph, including: a data obtaining module 301, configured to obtain a target data set, where the target data set includes data of multiple target enterprises, and each piece of data in the target data set includes an association characteristic of a target enterprise; the grouping module 303 is configured to divide the enterprises with the same association characteristics among the multiple target enterprises into the same enterprise group, where a target enterprise in an enterprise group has at least one same association characteristic; a building module 305, configured to build graph nodes for multiple target enterprises, and build association edges between the nodes for the graph nodes in the enterprise group according to association types, where the association types represent association relationships among the multiple target enterprises due to the same association characteristics; and an association strength determining module 307, configured to determine an association strength of the association edge by using an association coefficient and an association weight, where the association coefficient is used to indicate a degree of contribution of an association type matched with the association coefficient to risk conduction, and the association weight is used to indicate a closeness of an association relationship between enterprises having the association type.
It should be noted that the data obtaining module 301 in this embodiment may be configured to execute step S202 in this embodiment, the grouping module 303 in this embodiment may be configured to execute step S204 in this embodiment, the constructing module 305 in this embodiment may be configured to execute step S206 in this embodiment, and the association strength determining module 307 in this embodiment may be configured to execute step S208 in this embodiment.
It should be noted here that the modules described above are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of the above embodiments. It should be noted that the modules described above as a part of the apparatus may operate in a hardware environment as shown in fig. 1, and may be implemented by software or hardware.
Optionally, the apparatus for constructing an enterprise association map further includes: the association type determination module is used for determining the type of the association relation between the target enterprises with the association characteristics as an association type; and the parameter determining module is used for determining the correlation coefficient and the correlation weight corresponding to each correlation type according to the set parameters.
Optionally, the apparatus for constructing an enterprise association map further includes: the system comprises a selection module, a processing module and a processing module, wherein the selection module is used for selecting a target enterprise group from a plurality of enterprise groups, and the type of the incidence relation between target enterprises in the target enterprise group is a target incidence type; the first building module is used for building association edges of a target association type between every two nodes in the target enterprise group in the map nodes, and the association edges comprise two reverse association edges which are in reverse relation with each other.
Optionally, the apparatus for constructing an enterprise association map further includes: and the second construction module is used for constructing the associated edges for any two map nodes in the enterprise group under the condition that the associated edges do not exist between the two map nodes.
Optionally, the apparatus for constructing an enterprise association map further includes: the enterprise group determining module is used for determining each enterprise group to which different associated characteristics belong under the condition that the associated objects referred by the different associated characteristics are the same associated object; and the third construction module is used for constructing the association edges for the two map nodes under the condition that the association edges do not exist between any two map nodes in each enterprise group to which the different association characteristics belong.
Optionally, the apparatus for constructing an enterprise association map further includes: and the calculation module is used for determining the product of the association coefficient matched with the association type of the association edge and the association weight as the association strength of the association edge.
Optionally, the apparatus for constructing an enterprise association map further includes: and the comparison determining module is used for determining the maximum value of the plurality of association strengths as the association strength of the association side under the condition that one association side has a plurality of association types.
There is also provided, in accordance with yet another aspect of the embodiments of the present application, a computer device, including a memory and a processor, the memory having stored therein a computer program executable on the processor, the processor implementing the steps when executing the computer program.
The memory and the processor in the computer device communicate with each other through a communication bus and a communication interface. The communication bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc.
The Memory may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
There is also provided, in accordance with yet another aspect of an embodiment of the present application, a computer-readable medium having non-volatile program code executable by a processor.
Optionally, in an embodiment of the present application, a computer readable medium is configured to store program code for the processor to perform the following steps:
step S202, a target data set is obtained, the target data set comprises data of a plurality of target enterprises, and each piece of data in the target data set comprises the associated characteristics of one target enterprise;
step S204, dividing the enterprises with the same association characteristics in a plurality of target enterprises into the same enterprise group, wherein the target enterprises in one enterprise group at least have one same association characteristic;
step S206, establishing map nodes for a plurality of target enterprises, and establishing association edges between the nodes for the map nodes in the enterprise group according to association types, wherein the association types represent association relations among the target enterprises due to the fact that the target enterprises have the same association characteristics;
and step S208, determining the association strength of the association edge by using an association coefficient and an association weight, wherein the association coefficient is used for representing the contribution degree of the association type matched with the association coefficient to risk conduction, and the association weight is used for representing the closeness of the association relation between enterprises with the association type.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment is not described herein again.
When the embodiments of the present application are specifically implemented, reference may be made to the above embodiments, and corresponding technical effects are achieved.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented by means of units performing the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and in actual implementation, there may be other divisions, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially implemented or make a contribution to the prior art, or may be implemented in the form of a software product stored in a storage medium and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk. It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A method for constructing an enterprise association map is characterized by comprising the following steps:
acquiring a target data set, wherein the target data set comprises data of a plurality of target enterprises, and each piece of data in the target data set comprises an associated characteristic of one target enterprise;
dividing the enterprises with the same association characteristics in the target enterprises into the same enterprise group, wherein the target enterprises in one enterprise group at least have one same association characteristic;
establishing graph nodes for the target enterprises, and establishing association edges between the nodes for the graph nodes in the enterprise group according to association types, wherein the association types represent association relations among the target enterprises due to the fact that the target enterprises have the same association characteristics;
Determining the association strength of the association edge by utilizing an association coefficient and an association weight, wherein the association coefficient is used for representing the contribution degree of the association type matched with the association coefficient to risk conduction, and the association weight is used for representing the compactness of the association relationship between enterprises with the association type.
2. The method of claim 1, wherein prior to obtaining the target data set, further comprising determining the association type, the association coefficient, and the association weight as follows:
determining a type of incidence relation between the target enterprises with the incidence characteristics as the incidence type;
and determining the association coefficient and the association weight corresponding to each association type according to set parameters.
3. The method of claim 2, wherein constructing association edges between nodes for the graph nodes in the enterprise group according to association types comprises:
selecting a target enterprise group from a plurality of enterprise groups, wherein the type of the incidence relation between the target enterprises in the target enterprise group is a target incidence type;
and establishing an association edge of the target association type between every two nodes in the target enterprise group in the graph nodes, wherein the association edge comprises two reverse association edges which are in reverse relation with each other.
4. The method of claim 3, wherein after establishing the associated edges of the target association type between the nodes in the target enterprise group for the graph nodes, further comprising establishing the associated edges between nodes for nodes in other enterprise groups than the target enterprise group as follows:
and under the condition that the association edge does not exist between any two graph nodes in the other enterprise groups, constructing the association edge for the two graph nodes.
5. The method of claim 4, wherein in the absence of the associated edge between any two of the graph nodes in the other enterprise groups, after constructing an associated edge for both of the graph nodes, further comprising simultaneously constructing the associated edges between nodes and graph nodes in the plurality of enterprise groups as follows:
determining each enterprise group to which different associated characteristics belong under the condition that the associated objects referred by the different associated characteristics are the same associated object;
and under the condition that the association edge does not exist between any two map nodes in each enterprise group to which the different association features belong, constructing the association edge for the two map nodes.
6. The method of any of claims 1 to 5, wherein determining the strength of the association of the associated edge using the association coefficient and the association weight comprises:
determining the correlation strength of the correlation edge as a product of the correlation coefficient matching the correlation type of the correlation edge and the correlation weight.
7. The method of claim 6, wherein determining the strength of association of the associated edge using the association coefficient and the association weight further comprises:
in the case that a plurality of association types exist in one association edge, determining the maximum value of a plurality of association strengths as the association strength of the association edge.
8. An apparatus for constructing an enterprise association map, comprising:
the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module is used for acquiring a target data set, the target data set comprises data of a plurality of target enterprises, and each piece of data in the target data set comprises an association characteristic of one target enterprise;
the grouping module is used for dividing the enterprises with the same association characteristics in the target enterprises into the same enterprise group, wherein the target enterprises in one enterprise group at least have one same association characteristic;
The construction module is used for establishing graph nodes for the target enterprises and constructing association edges between the nodes for the graph nodes in the enterprise group according to association types, wherein the association types represent association relations among the target enterprises due to the fact that the target enterprises have the same association characteristics;
and the association strength determining module is used for determining the association strength of the association edge by utilizing an association coefficient and an association weight, wherein the association coefficient is used for representing the contribution degree of the association type matched with the association coefficient to risk conduction, and the association weight is used for representing the closeness of the association relation between enterprises with the association type.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable medium having non-volatile program code executable by a processor, wherein the program code causes the processor to perform the method of any of claims 1 to 7.
CN202010556321.5A 2020-06-17 2020-06-17 Method, device, equipment and computer readable medium for constructing enterprise association graph Active CN111861120B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010556321.5A CN111861120B (en) 2020-06-17 2020-06-17 Method, device, equipment and computer readable medium for constructing enterprise association graph

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010556321.5A CN111861120B (en) 2020-06-17 2020-06-17 Method, device, equipment and computer readable medium for constructing enterprise association graph

Publications (2)

Publication Number Publication Date
CN111861120A true CN111861120A (en) 2020-10-30
CN111861120B CN111861120B (en) 2023-10-13

Family

ID=72986216

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010556321.5A Active CN111861120B (en) 2020-06-17 2020-06-17 Method, device, equipment and computer readable medium for constructing enterprise association graph

Country Status (1)

Country Link
CN (1) CN111861120B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112819353A (en) * 2021-02-07 2021-05-18 撼地数智(重庆)科技有限公司 Risk analysis method based on enterprise graph and computer equipment
CN113688287A (en) * 2021-08-24 2021-11-23 撼地数智(重庆)科技有限公司 Enterprise risk infection path analysis method, device, equipment and storage medium
CN115170271A (en) * 2022-09-09 2022-10-11 中证数智科技(深圳)有限公司 Clustering method, device, equipment and storage medium for risk associated enterprises
CN117522139A (en) * 2023-11-22 2024-02-06 深圳市赫德创新科技有限公司 Enterprise association risk analysis method, device and medium based on topological graph

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100169134A1 (en) * 2008-12-31 2010-07-01 Microsoft Corporation Fostering enterprise relationships
CN107665252A (en) * 2017-09-27 2018-02-06 深圳证券信息有限公司 A kind of method and device of creation of knowledge collection of illustrative plates
CN108647981A (en) * 2018-05-17 2018-10-12 阿里巴巴集团控股有限公司 A kind of target object incidence relation determines method and apparatus
CN109271426A (en) * 2018-10-10 2019-01-25 中科鼎富（北京）科技发展有限公司 Enterprise's association relationship analysis method, device and computer readable storage medium
CN109670944A (en) * 2018-12-19 2019-04-23 信雅达系统工程股份有限公司 A kind of rating business credit method and system based on map relational network
CN110738388A (en) * 2019-09-02 2020-01-31 深圳壹账通智能科技有限公司 Method, device, equipment and storage medium for risk conduction of associated map evaluation

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100169134A1 (en) * 2008-12-31 2010-07-01 Microsoft Corporation Fostering enterprise relationships
CN107665252A (en) * 2017-09-27 2018-02-06 深圳证券信息有限公司 A kind of method and device of creation of knowledge collection of illustrative plates
CN108647981A (en) * 2018-05-17 2018-10-12 阿里巴巴集团控股有限公司 A kind of target object incidence relation determines method and apparatus
CN109271426A (en) * 2018-10-10 2019-01-25 中科鼎富（北京）科技发展有限公司 Enterprise's association relationship analysis method, device and computer readable storage medium
CN109670944A (en) * 2018-12-19 2019-04-23 信雅达系统工程股份有限公司 A kind of rating business credit method and system based on map relational network
CN110738388A (en) * 2019-09-02 2020-01-31 深圳壹账通智能科技有限公司 Method, device, equipment and storage medium for risk conduction of associated map evaluation

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112819353A (en) * 2021-02-07 2021-05-18 撼地数智(重庆)科技有限公司 Risk analysis method based on enterprise graph and computer equipment
CN113688287A (en) * 2021-08-24 2021-11-23 撼地数智(重庆)科技有限公司 Enterprise risk infection path analysis method, device, equipment and storage medium
CN115170271A (en) * 2022-09-09 2022-10-11 中证数智科技(深圳)有限公司 Clustering method, device, equipment and storage medium for risk associated enterprises
CN115170271B (en) * 2022-09-09 2023-05-12 中证数智科技(深圳)有限公司 Clustering method, device, equipment and storage medium for risk associated enterprises
CN117522139A (en) * 2023-11-22 2024-02-06 深圳市赫德创新科技有限公司 Enterprise association risk analysis method, device and medium based on topological graph

Also Published As

Publication number Publication date
CN111861120B (en) 2023-10-13

Similar Documents

Publication Publication Date Title
CN111861120A (en) Method, device and equipment for constructing enterprise association map and computer readable medium
CN110020956B (en) Cross-block-chain interaction method and system, computer equipment and storage medium
WO2020119272A1 (en) Risk identification model training method and apparatus, and server
US10325177B1 (en) System, device, and method for image anomaly detection
US8296356B2 (en) Rating based on relationship
US8751375B2 (en) Event processing for detection of suspicious financial activity
WO2019020095A1 (en) Merchant evaluation method and system
JP2019522275A (en) Electronic mortgage brokerage and monitoring
CN104184763B (en) A kind of feedback information processing method and system, service equipment
US9582719B2 (en) Geographical area condition determination
TW201802732A (en) Method and device for controlling data risk
CN111861119B (en) Enterprise risk data processing method and device based on enterprise risk association graph
US20140358805A1 (en) Illegal Activity Detection through Interpersonal Relationship Resolution
CN109446276A (en) Order hold-up interception method, device, equipment and medium based on relational data model
CN106101098B (en) A kind of information assets recognition methods and device
US20140100891A1 (en) First Responder Dispatch System
CN108650289A (en) A kind of method and apparatus of the management data based on block chain
CN110135684A (en) A kind of capability comparison method, capability comparison device and terminal device
Joshi et al. Political issue extraction model: A novel hierarchical topic model that uses tweets by political and non-political authors
Askitas et al. Detecting mortgage delinquencies
CN109376287B (en) House property map construction method, device, computer equipment and storage medium
CN104572393A (en) Buyer and seller login monitoring method and buyer and seller login monitoring system
DeSombre et al. Surveillance technology at the fair: Proliferation of cyber capabilities in international arms markets
CN112308352A (en) Order identification method and device and electronic equipment
CN109800276A (en) Strength of association appraisal procedure, device, equipment and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant