CN116595183A

CN116595183A - Wind control method, device, medium and equipment

Info

Publication number: CN116595183A
Application number: CN202310168785.2A
Authority: CN
Inventors: 赵朗琦; 孙清清; 陈阳; 刘芳如; 赵晓倩
Original assignee: Alipay Hangzhou Information Technology Co Ltd
Current assignee: Alipay Hangzhou Information Technology Co Ltd
Priority date: 2023-02-24
Filing date: 2023-02-24
Publication date: 2023-08-15

Abstract

The specification discloses a method, a device, a medium and equipment for wind control, which are used for acquiring a local name list, determining entities in the local list and relationships among the entities, wherein the entities comprise enterprises and/or natural persons, and further constructing a first knowledge graph. And determining all entities in the external list, which are the same as the entities in the first knowledge graph, as all the entities to be combined according to the external list acquired in advance. And merging the information of each entity to be merged in the external list into the first knowledge graph to obtain a second knowledge graph. And determining attention labels of all the nodes according to the information of the entities corresponding to all the nodes in the second knowledge graph. When a wind control request of a to-be-wind-controlled entity is received, the wind control of the to-be-wind-controlled entity can be performed by using a corresponding wind control rule according to the attention degree label of the node corresponding to the to-be-wind-controlled entity in the second knowledge graph, so that the wind control efficiency is improved, the error wind control caused by the lack of local name information is avoided, and the wind control accuracy is improved.

Description

Wind control method, device, medium and equipment

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a medium, and a device for wind control.

Background

With the rapid development of the internet, privacy data and wind control are increasingly concerned. Wind control refers to risk control, and the service provider may take various measures to reduce the probability of occurrence of a risk event, or to control possible losses within a certain range, so as to avoid the losses that are hard to bear when the risk event occurs.

While the risk faced by a service provider in providing service to different customers is different. In providing services to customers, the social impact of the customers is often positively correlated with the risks they carry. Because the status and impact of such customers increases the social impact and thus the risk of the service compared to normal customers. Thus, how to wind control is an important issue when a service provider provides services to different customers.

Based on this, the present description provides a method of wind control.

Disclosure of Invention

The present disclosure provides a method and apparatus for air control, a storage medium and a device to at least partially solve the above-mentioned problems of the prior art.

The technical scheme adopted in the specification is as follows:

the present specification provides a method of wind control, the method comprising:

Acquiring a local name list, and determining entities in the local list and the relation among the entities according to the local list; wherein the entity comprises an enterprise and/or a natural person;

constructing a first knowledge graph by taking the determined entities as nodes and the determined relationship among the entities as edges;

for each entity in the first knowledge graph, taking the entity as a first entity, and determining the entity which is the same as the first entity in the external list as an entity to be combined according to the external list acquired in advance;

combining the information of each entity to be combined in the external list into the first knowledge graph to obtain a second knowledge graph;

aiming at each node in the second knowledge graph, determining a attention label of the node according to the information of the entity corresponding to the node;

when a wind control request of an entity to be wind controlled is received, determining a wind control rule corresponding to the attention degree label according to the attention degree label of the node corresponding to the entity to be wind controlled in the second knowledge graph, and performing wind control on the entity to be wind controlled by using the wind control rule.

Optionally, the information of the entity includes at least: attribute information of the entity and a relation between the entity and other entities;

According to a pre-acquired external list, determining an entity which is the same as the first entity in the external list specifically comprises the following steps:

for each entity in the external list, the entity is taken as a second entity, and the similarity of the information of the first entity and the information of the second entity is determined according to the attribute information of the first entity, the relationship between the first entity and other first entities in the first knowledge graph, the attribute information of the second entity and the relationship between the second entity and other second entities in the external list;

and determining the entity which is the same as the first entity in the external list according to the similarity between the information of the first entity and the information of each second entity in the external list.

Optionally, the information of the entity includes: attribute information of the entity itself;

merging the information of each entity to be merged in the external list into the first knowledge graph, wherein the method specifically comprises the following steps:

for each first entity, determining increment information of attribute information of the entity to be combined corresponding to the first entity relative to the attribute information of the first entity;

and merging the increment information into the attribute information of the first entity.

Optionally, the information of the entity includes: the relationship between the entity and other entities;

for each first entity, determining the relationship between the entity to be combined corresponding to the first entity and other entities in the external list as the relationship to be combined; and determining the relation between the first entity and other entities in the first knowledge graph as a first relation of the first entity;

determining an incremental relationship of the relationship to be combined relative to the first relationship;

and determining other entities except the entity to be combined corresponding to the first entity in the increment relation as undetermined entities, and establishing the relation between the first entity and the undetermined entities in the first knowledge graph according to the increment relation when the undetermined entities exist in the first knowledge graph.

Optionally, the method further comprises:

when the undetermined entity does not exist in the first knowledge graph, adding the undetermined entity into the first knowledge graph, and establishing a relation between the first entity and the undetermined entity in the first knowledge graph according to the increment relation.

Optionally, merging the information of each entity to be merged in the external list into the first knowledge graph, which specifically includes:

determining an incremental entity of the external list relative to the first knowledge-graph;

and merging the information of each entity to be merged in the external list and the information of the increment entity into the first knowledge graph.

Optionally, determining the attention label of the node according to the information of the entity corresponding to the node specifically includes:

when the entity corresponding to the node is a designated natural person or a designated enterprise, the first attention label is used as the attention label of the node; wherein the designated natural persons at least comprise high social influence people, and the designated enterprises at least comprise high-operation risk enterprises.

Optionally, the method further comprises:

when the entity corresponding to the node is not a designated enterprise or a designated natural person, determining a attention label of the adjacent node of the node;

and if the attention label of at least one adjacent node of the node is the first attention label, taking the second attention label as the attention label of the node.

Optionally, determining, according to the attention label of the node corresponding to the entity to be wind controlled in the second knowledge graph, a wind control rule corresponding to the attention label specifically includes:

For each node in the second knowledge graph, determining the similarity between the information of the entity corresponding to the node and the information of the entity to be winded; the information of the entity at least comprises attribute information of the entity and the relationship between the entity and other entities;

and determining a attention degree label of a node corresponding to the entity to be wind-controlled in the second knowledge graph according to the similarity and a preset similarity threshold value, and determining a wind control rule corresponding to the attention degree label.

The present specification provides a device for wind control, comprising:

the acquisition module is used for acquiring a local name list and determining entities in the local list and the relation among the entities according to the local list; wherein the entity comprises an enterprise and/or a natural person;

the construction module is used for constructing a first knowledge graph by taking the determined entities as nodes and the determined relationship among the entities as edges;

the first determining module is used for determining, as a to-be-combined entity, an entity identical to the first entity in the external list according to the external list acquired in advance by taking the entity as the first entity for each entity in the first knowledge graph;

The merging module is used for merging the information of each entity to be merged in the external list into the first knowledge graph to obtain a second knowledge graph;

the second determining module is used for determining a attention degree label of each node in the second knowledge graph according to the information of the entity corresponding to the node;

and the wind control module is used for determining a wind control rule corresponding to the attention degree label according to the attention degree label of the node corresponding to the entity to be wind controlled in the second knowledge graph when a wind control request of the entity to be wind controlled is received, and performing wind control on the entity to be wind controlled by using the wind control rule.

The present description provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of wind control described above.

The present specification provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of wind control described above when executing the program.

The above-mentioned at least one technical scheme that this specification adopted can reach following beneficial effect:

In the method for wind control provided in the present specification, a local list is first obtained, and entities in the local list and relationships between the entities are determined, where the entities include enterprises and/or natural persons. And secondly, constructing a first knowledge graph by taking the determined entities as nodes and the determined relationship among the entities as edges. And taking the entity in the first knowledge graph as a first entity, and determining all the entities which are the same as the first entity in the external list as all the entities to be combined according to the external list acquired in advance. And then combining the information of each entity to be combined in the external list into the first knowledge graph to obtain a second knowledge graph. And determining attention labels of all the nodes according to the information of the entities corresponding to all the nodes in the second knowledge graph. And finally, when a wind control request of the entity to be wind controlled is received, determining a wind control rule corresponding to the attention degree label according to the attention degree label of the node corresponding to the entity to be wind controlled in the second knowledge graph, and using the wind control rule to wind control the entity to be wind controlled.

According to the method, the first knowledge graph is constructed by determining the entities in the local list and the relation among the entities, and the information of the entities in the external list is combined into the first knowledge graph to obtain the second knowledge graph. And further, according to the information of the entity corresponding to each node in the second knowledge graph, determining the attention label of each node. When the entity is subjected to wind control, the wind control can be performed based on the second knowledge graph, so that the wind control efficiency is improved, the error wind control caused by the lack of local name information is avoided, and the wind control accuracy is improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the specification, illustrate and explain the exemplary embodiments of the present specification and their description, are not intended to limit the specification unduly. Attached at

In the figure:

FIG. 1 is a schematic flow chart of a method of wind control in the present specification;

FIG. 2 is a schematic diagram of a first knowledge graph constructed according to the present disclosure;

FIG. 3 is a schematic diagram of entity information merging provided in the present specification;

FIG. 4 is a schematic diagram of entity information merging provided in the present specification;

FIG. 5 is a schematic view of a wind-controlled apparatus provided herein;

fig. 6 is a schematic view of the electronic device corresponding to fig. 1 provided in the present specification.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the present specification more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art without the exercise of inventive faculty, are intended to be within the scope of the application, based on the embodiments in the specification.

The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

Fig. 1 is a schematic flow chart of a method for wind control provided in the present specification, which may specifically include the following steps:

s100: acquiring a local name list, and determining entities in the local list and the relation among the entities according to the local list; wherein the entity comprises an enterprise and/or a natural person.

S102: and constructing a first knowledge graph by taking the determined entities as nodes and the determined relationship among the entities as edges.

Service providers are at high risk when providing business services to highly socially influential individuals and high-risk business enterprises. Therefore, a general service provider has a local name list for recording the information of people with high social influence and enterprises with high management risk, and the like, so that when the service is provided for the client, the identity information in the local list corresponding to the client can be judged according to the information in the local list, thereby facilitating the follow-up implementation of wind control by using different rules. In addition to using local names, the service provider may determine the identity of the customer using a list purchased at an organization that is dedicated to providing a list of people with high social impact and/or high-risk enterprises, using information collected from encyclopedias, news, and the like. In one or more embodiments of the present specification, other lists except for local names and external information are collectively referred to as external lists for convenience of description.

The Knowledge Graph (knowledgegraph) is composed of nodes (entities) and edges (relationships between entities). Each node has several attributes and attribute values, the direction of the edge indicates the direction of the relationship, and the label on the edge indicates the type of the relationship. The knowledge graph can clearly represent the association relation between the entities, can be easily identified and processed by a computer, and can greatly improve the information retrieval efficiency. Based on this, the present description provides a method of wind control. The method can be executed by a server of a service provider, and the scheme is described with the server as an execution subject.

Specifically, in one or more embodiments of the present description, a server may first obtain a local manifest and extract entities in the local list, including businesses and/or natural persons, and relationships between the entities. And then taking the entities as nodes and the relation among the entities as edges to construct a first knowledge graph. For example: fig. 2 is a schematic diagram for constructing a first knowledge graph provided in the present specification, where circles represent entities as natural people, and boxes represent entities as enterprises. For the ' a sex male ' in the local list, which is manager of enterprise x, partner b … … ', the relationship between the entities and the extraction of the entities are carried out, and the entities are obtained: natural people a, b and enterprise x, get the relationship between entities: the natural person a is a manager of the enterprise x, the spouse of the natural person a is the natural person b, and then a first knowledge graph is constructed by taking a, b and x as nodes and taking the relation between a and b and the relation between a and x as sides.

S104: and aiming at each entity in the first knowledge graph, taking the entity as a first entity, and determining the entity which is the same as the first entity in the external list as an entity to be combined according to the external list acquired in advance.

In one or more embodiments of the present disclosure, after the first knowledge-graph is constructed according to the local ticket, the server may further determine the same entity in the external list as the entity in the first knowledge-graph, so as to perform the merging of the information of the entities through the subsequent steps.

Because the standards of the natural people or enterprises with risks recorded by the local list and the external list are different and the information sources of the entities are different, the relationship between the entities contained in the local list and the external list is not identical. Therefore, when the information of the entities is combined, the same entities in the local names and the external lists are found first, and then the information of the entities is combined based on the same entities. Specifically, for each entity in the first knowledge graph, the server may take the entity as a first entity, and then determine, according to a pre-acquired external list, an entity in the external list that is the same as the entity, as an entity to be combined. The information of the entities in the external list is combined into the first knowledge graph in the subsequent step, so that when the entities are subjected to wind control, the wind control can be performed based on more comprehensive information, and the accuracy of the wind control is improved.

In addition, when the server determines the entity in the external list that is the same as the entity in the first knowledge-graph, the server may determine the same entity according to the similarity of the information in the external list with the entity in the first knowledge-graph by determining the similarity of the information in the external list with the entity in the first knowledge-graph. Wherein the information of the entity at least comprises: attribute information of the entity itself, and relationships between the entity and other entities.

Specifically, after the server regards the entity as a first entity for each entity in the first knowledge graph, the server may further determine, for each entity in the external list, a similarity between information of the first entity and information of the second entity according to attribute information of the first entity itself, a relationship between the first entity and other first entities in the first knowledge graph, attribute information of the second entity itself, and a relationship between the second entity and other second entities in the external list. And then determining the entity which is the same as the first entity in the external list according to the similarity between the information of the first entity and the information of each second entity in the external list. If the entity is a natural person, the birth date, the job date, the age, the native place, the learning information and the like of the natural person are attribute information of the entity. If the entity is a business, the business establishment date, the business information, the high management information, the business scale and the like are attribute information of the entity.

In addition, when determining the same entity as the first entity in the external list, the server may first determine a similarity between attribute information of the first entity and attribute information of the second entity, as the first similarity. And then taking other entities which are related to the first entity in the first knowledge graph as first entities to be determined, taking other entities which are related to the second entity in the external list as second entities to be determined, and determining the similarity of the attribute information of the first entity to be determined and the attribute information of the second entity to be determined as second similarity. And determining the entity which is the same as the first entity in the external list according to the weight proportion occupied by the first similarity and the second similarity. For example: the similarity between the attribute information of A and the attribute information of A1 is determined to be 80 percent. And the similarity of the attribute information of the natural person B related to a and the natural person B1 related to A1 is 60%, and the weight ratio of the similarity of the attribute information of the preset entity to the attribute information of other similar entities related to the entity is 8:2, so that the final similarity of a and A1 is 80% ×0.8+60% ×0.2=76%.

And the information of the two corresponding entities in different lists can be taken as a sample, and whether the two entities are the same entity or not can be taken as a label to train the identification model. And deploying the trained recognition model in the server, and when determining the entity identical to the first entity in the external list, inputting the second entity and the first entity into the recognition model for each second entity in the external list, and determining whether the second entity and the first entity are identical entities according to the recognition result. In particular, what method may be used to determine the same entity as the first entity in the external list is not limited in this specification, as long as a determination may be made.

S106: and merging the information of each entity to be merged in the external list into the first knowledge graph to obtain a second knowledge graph.

In one or more embodiments of the present disclosure, after determining each entity to be combined of the entities in the external list and the first knowledge-graph in the above step, the server may further combine information of each entity to be combined to the first knowledge-graph based on the determined entity to be combined to obtain the second knowledge-graph.

Specifically, when the information of the entity to be combined includes attribute information of the entity, the server may determine, for each first entity in the first knowledge graph, incremental information of attribute information of the entity to be combined corresponding to the first entity relative to attribute information of the first entity, and combine the incremental information into the attribute information of the first entity. That is, after determining the entity A1 to be combined corresponding to the entity a in the first knowledge graph, the information different from the attribute information of the entity a in the attribute information of the entity A1 is used as the incremental information and is combined into the attribute information of the entity a. For example: the attribute information of the entity A1 in the external list is: sex A1 is female, graduate university in 2018. The attribute information of the entity A in the local list is as follows: a is female, and ancestor Z province. The incremental information for entity A1 relative to entity a is graduate university in 2018. The information is combined with the attribute information of the entity A.

When the information of the entity to be combined includes the relationship between the entity and other entities, the server may determine, for each first entity, the relationship between the entity to be combined corresponding to the first entity and other entities in the external list, as the relationship to be combined. And determining the relation between the first entity and other entities in the first knowledge graph as a first relation of the first entity. And then determining an increment relation of the relation to be combined relative to the first relation, determining other entities except the entity to be combined corresponding to the first entity in the increment relation as undetermined entities, and establishing the relation between the first entity and the undetermined entity in the first knowledge graph according to the increment relation when the undetermined entity exists in the first knowledge graph.

Fig. 3 is a schematic diagram of entity information merging provided in the present disclosure, and it can be seen that an entity to be merged in the external list is a natural person B1, which corresponds to the natural person B in the first knowledge graph. The relationship between the natural person B1 and other entities in the external list is: the palliative of B1 is C, the father is E, and D is a friend. The relationship between B1 and C, D, E is the relationship to be merged. The relationship between the natural person B and other entities in the first knowledge graph is as follows: the father of B is E and the son of B is F. The relationship between B and E, F is the first relationship. From this, the incremental relationship of the relationship to be merged with respect to the first relationship is: the palpation of B1 is C, the palpation is D is a friend, and the pending entity is C, D. And the entity in the first knowledge graph is provided with the entity C, and the entity D is not provided, so that the relationship between B and C is established in the first knowledge graph only according to the incremental relationship that the gird of B1 is C.

Further, when the server determines that the undetermined entity does not exist in the first knowledge graph, adding the undetermined entity into the first knowledge graph, and establishing a relation between the first entity and the undetermined entity in the first knowledge graph according to the increment relation. Along the above example, there is no entity D in the first knowledge graph, so the entity D is added to the first knowledge graph, and the relationship between B and D in the first knowledge graph is constructed according to the incremental relationship that B1 and D are friends, and the obtained second knowledge graph is shown in fig. 4.

S108: and aiming at each node in the second knowledge graph, determining the attention label of the node according to the information of the entity corresponding to the node.

In one or more embodiments of the present disclosure, the server may combine the information of each entity to be combined to the first knowledge-graph in the above step, and after obtaining the second knowledge-graph, determine, for each node in the second knowledge-graph, a attention label of the node according to the information of the entity corresponding to the node.

When the entity corresponding to the node is a designated natural person or a designated enterprise, the first attention label is used as the attention label of the node. The specific natural person and the specific enterprise are not limited in the specification, and can be set according to specific business requirements.

Note that, the attention label indicates that: the degree of attention of the entity corresponding to the node, namely the magnitude of wind control force. The first attention label indicates that the attention to the specified nature person or the specified enterprise is high, that is, the precautionary measure should be enhanced with particular attention to the precautionary risk when providing services to the specified nature person or the specified enterprise.

S110: when a wind control request of an entity to be wind controlled is received, determining a wind control rule corresponding to the attention degree label according to the attention degree label of the node corresponding to the entity to be wind controlled in the second knowledge graph, and performing wind control on the entity to be wind controlled by using the wind control rule.

In one or more embodiments of the present disclosure, after determining the second knowledge graph and the attention label of each node in the second knowledge graph, when the server receives the wind control request of the entity to be wind controlled, the server may determine, according to the attention label of the node corresponding to the entity to be wind controlled in the second knowledge graph, a wind control rule corresponding to the attention label, and wind control the entity to be wind controlled using the wind control rule.

Specifically, for each node in the second knowledge graph, the server may determine similarity between information of an entity corresponding to the node and information of an entity to be controlled, where the information of the entity includes at least attribute information of the entity itself and a relationship between the entity and other entities. And then determining a attention degree label of a node corresponding to the entity to be controlled in the second knowledge graph according to the similarity and a preset similarity threshold value, and determining a wind control rule corresponding to the attention degree label.

Further, when determining the attention label of the node corresponding to the entity to be winded in the second knowledge graph according to the similarity and the preset similarity threshold, the server may determine the similarity greater than the preset similarity threshold as the similarity to be selected. And then determining the maximum similarity in the similarity to be selected, determining a node in a second knowledge graph corresponding to the maximum similarity, and further determining a attention label of the node. And finally, performing wind control on the entity to be wind controlled by using a wind control rule corresponding to the attention label. If each similarity is not greater than the preset similarity threshold, the fact that the entity to be controlled by wind is not in the second knowledge graph, namely the corresponding attention label is not found. Then no or a low level of wind control may be implemented.

Based on the wind control method shown in fig. 1, the server may obtain a local name list and determine the entities in the local list and the relationships between the entities, and construct a first knowledge graph by taking the determined entities as nodes and the determined relationships between the entities as edges. And then determining all the entities in the external list, which are the same as the entities in the first knowledge graph, as all the entities to be combined. And then combining the information of each entity to be combined in the external list into the first knowledge graph to obtain a second knowledge graph. And determining attention labels of all the nodes according to the information of the entities corresponding to all the nodes in the second knowledge graph. And finally, when the server receives the wind control request of the entity to be wind controlled, determining a wind control rule corresponding to the attention degree label according to the attention degree label of the node corresponding to the entity to be wind controlled in the second knowledge graph, and using the wind control rule to wind control the entity to be wind controlled. The method can perform wind control on the entity based on the second knowledge graph, improves the wind control efficiency, avoids the error wind control caused by the lack of local name information, and improves the wind control accuracy.

In addition, there is a great risk that a person who has a relationship with a person who is assigned to nature, an enterprise who has a relationship with a parent-child company, or the like, is assigned to an enterprise, and the like. Therefore, in the step S108, when determining, for each node in the second knowledge graph, the attention label of the node according to the information of the entity corresponding to the node, the server may further determine, when the entity corresponding to the node is not a designated enterprise or a designated natural person, the attention label of the adjacent node of the node, and if the attention label of at least one adjacent node of the node is the first attention label, the second attention label is used as the attention label of the node. That is, attention labels are set on the association natural people of the appointed natural people and the appointed enterprises and the association enterprises to distinguish the association natural people from the ordinary people and the ordinary enterprises, so that wind control is more strict, and potential risks are prevented.

When determining the adjacent node of the node, the node may be a node that determines a first-order adjacent or a node that determines a first-order adjacent and a second-order adjacent, specifically, a node that determines a few-order adjacent, which may be set according to the need, and the present description is not limited.

And as described in S108 above, the attention label indicates that: the degree of attention of the entity corresponding to the node, namely the magnitude of wind control force. The second attention degree label is different from the corresponding wind control rule of the first attention degree label, and the wind control force of the first attention degree label is larger than that of the second attention degree label. The wind control rules corresponding to the attention label can be enhanced supervision, limited provision of service, termination of provision of service and the like, and the specific wind control rules corresponding to the attention label are not limited in the specification and can be set according to specific needs. For example, the natural person a uses the APP of the service provider to transfer accounts, and after information matching, it is determined that the label of the node in the second knowledge graph corresponding to the natural person a is the first attention label. And assuming that the wind control rule corresponding to the first attention label provides service for termination, and the wind control rule corresponding to the second attention label provides service for limitation. Then when nature a uses the APP to make a transfer, the transfer transaction cannot proceed. And the labels of the nodes in the second knowledge graph corresponding to the children of the natural person A are second attention labels, when the children B of the natural person A are confirmed to transfer accounts, the upper limit of the transfer amount is limited to X elements, and the upper limit of the transfer times is limited to Y times.

Based on the above-mentioned method for wind control, the embodiment of the present disclosure further provides a schematic diagram of a wind control device, as shown in fig. 5.

Fig. 5 is a schematic diagram of a wind control device provided in the present specification, specifically including:

the obtaining module 500 is configured to obtain a local name list, and determine an entity in the local list and a relationship between entities according to the local list; wherein the entity comprises an enterprise and/or a natural person;

the construction module 502 is configured to construct a first knowledge graph with the determined entities as nodes and the determined relationships between the entities as edges;

a first determining module 504, configured to determine, for each entity in the first knowledge graph, the entity as a first entity, according to a pre-acquired external list, an entity in the external list that is the same as the first entity, as an entity to be combined;

a merging module 506, configured to merge information of each entity to be merged in the external list into the first knowledge-graph to obtain a second knowledge-graph;

a second determining module 508, configured to determine, for each node in the second knowledge graph, a attention label of the node according to information of an entity corresponding to the node;

And the wind control module 510 is configured to determine a wind control rule corresponding to a attention degree label of a node corresponding to the entity to be wind controlled in the second knowledge graph when a wind control request of the entity to be wind controlled is received, and wind control the entity to be wind controlled by using the wind control rule.

the first determining module 504 is specifically configured to determine, for each entity in the external list, a similarity between information of the first entity and information of the second entity according to attribute information of the first entity, a relationship between the first entity and other first entities in the first knowledge graph, attribute information of the second entity, and a relationship between the second entity and other second entities in the external list, where the entity is taken as the second entity; and determining the entity which is the same as the first entity in the external list according to the similarity between the information of the first entity and the information of each second entity in the external list.

The merging module 506 is specifically configured to determine, for each first entity, incremental information of attribute information of an entity to be merged corresponding to the first entity relative to attribute information of the first entity; and merging the increment information into the attribute information of the first entity.

the merging module 506 is specifically configured to determine, for each first entity, a relationship between an entity to be merged corresponding to the first entity and other entities in the external list, as a relationship to be merged; and determining the relation between the first entity and other entities in the first knowledge graph as a first relation of the first entity; determining an incremental relationship of the relationship to be combined relative to the first relationship; and determining other entities except the entity to be combined corresponding to the first entity in the increment relation as undetermined entities, and establishing the relation between the first entity and the undetermined entities in the first knowledge graph according to the increment relation when the undetermined entities exist in the first knowledge graph.

Optionally, the merging module 506 is further configured to add the undetermined entity to the first knowledge-graph when the undetermined entity does not exist in the first knowledge-graph, and establish a relationship between the first entity and the undetermined entity in the first knowledge-graph according to the incremental relationship.

Optionally, the merging module 506 is specifically configured to determine an incremental entity of the external list relative to the first knowledge-graph; and merging the information of each entity to be merged in the external list and the information of the increment entity into the first knowledge graph.

Optionally, the second determining module 508 is specifically configured to, when the entity corresponding to the node is a designated natural person or a designated enterprise, use the first attention label as the attention label of the node; wherein the designated natural persons at least comprise high social influence people, and the designated enterprises at least comprise high-operation risk enterprises.

Optionally, the second determining module 508 is further configured to determine, when the entity corresponding to the node is not a designated enterprise or a designated natural person, a attention label of a neighboring node of the node; and if the attention label of at least one adjacent node of the node is the first attention label, taking the second attention label as the attention label of the node.

Optionally, the wind control module 510 is specifically configured to determine, for each node in the second knowledge graph, a similarity between information of an entity corresponding to the node and information of the entity to be wind controlled; the information of the entity at least comprises attribute information of the entity and the relationship between the entity and other entities; and determining a attention degree label of a node corresponding to the entity to be wind-controlled in the second knowledge graph according to the similarity and a preset similarity threshold value, and determining a wind control rule corresponding to the attention degree label.

The embodiments of the present specification also provide a computer readable storage medium storing a computer program, where the computer program is configured to perform the method of wind control described above.

Based on the wind control method described above, the embodiment of the present disclosure further provides a schematic structural diagram of the electronic device shown in fig. 6. At the hardware level, as in fig. 6, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile storage, although it may include hardware required for other services. The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to realize the wind control method.

Of course, other implementations, such as logic devices or combinations of hardware and software, are not excluded from the present description, that is, the execution subject of the following processing flows is not limited to each logic unit, but may be hardware or logic devices.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable Gate Array, FPGA)) is an integrated circuit whose logic function is determined by the programming of the device by a user. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented by using "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before the compiling is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but not just one of the hdds, but a plurality of kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), lava, lola, myHDL, PALASM, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.

It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present description can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present description is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

It should also be noted that 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 one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.

The foregoing is merely exemplary of the present disclosure and is not intended to limit the disclosure. Various modifications and alterations to this specification will become apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of the present description, are intended to be included within the scope of the claims of the present description.

Claims

1. A method of wind control, the method comprising:

2. The method of claim 1, the information of the entity comprising at least: attribute information of the entity and a relation between the entity and other entities;

3. The method of claim 1, the information of the entity comprising: attribute information of the entity itself;

4. The method of claim 1, the information of the entity comprising: the relationship between the entity and other entities;

5. The method of claim 4, the method further comprising:

6. The method of claim 1, wherein merging the information of each entity to be merged in the external list into the first knowledge graph specifically includes:

7. The method of claim 1, wherein determining the attention label of the node according to the information of the entity corresponding to the node specifically includes:

When the entity corresponding to the node is a designated natural person or a designated enterprise, the first attention label is used as the attention label of the node.

8. The method of claim 7, the method further comprising:

9. The method of claim 1, wherein determining, according to the attention label of the node corresponding to the entity to be winded in the second knowledge graph, the wind control rule corresponding to the attention label specifically includes:

10. A device for wind control, the device comprising in particular:

and when a wind control request of an entity to be wind controlled is received, the wind control module determines a wind control rule corresponding to the attention degree label according to the attention degree label of the node corresponding to the entity to be wind controlled in the second knowledge graph, and uses the wind control rule to wind control the entity to be wind controlled.

11. A computer readable storage medium storing a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-9.

12. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any of the preceding claims 1-9 when the program is executed.