CN111445320B - Target community identification method and device, computer equipment and storage medium - Google Patents
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Abstract
The invention relates to a target community identification method, a device, computer equipment and a storage medium, wherein the method comprises the steps of obtaining an identification request; determining a corresponding individual set according to the identification request to obtain a set to be identified; determining individuals with association relations in a set to be identified to obtain a candidate individual set; traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with a direct or indirect connection relationship in a graph structure network so as to form a target community; and sending the related information of the target community to the terminal so that the terminal displays the related information of the target community. According to the invention, the graph structure network is constructed by determining the individuals with the association relation according to the identification request, the graph structure network is traversed by utilizing the graph traversal algorithm, all the associated individuals are found, so that the target community is determined, the virtual invoice community can be quickly and accurately found out in the business scene of the virtual invoice partner identification, the target community can be conveniently identified, the case handling time of the checking case handling personnel is shortened, and the accuracy is high.
Description
Technical Field
The present invention relates to a computer, and more particularly, to a target community identification method, apparatus, computer device, and storage medium.
Background
In the process of opening deficiency and cheating, the Shenzhen city inspection bureau of the national tax administration always needs to induce deficiency opening equipment to perform partner according to the existing deficiency opening condition. Traditional group partner induction of Shenzhen city inspection bureau often requires the inspection and transaction staff to have abundant transaction experience, and the group partner relationship between virtual issuing computers is comprehensively judged according to conditions such as the goods-taking condition and the goods-selling condition of the virtual issuing computers, the issuing amount scale, the issuing time period, whether the same issuing enterprises issue invoices or not, and the like. Such complex research and judgment results in that only a few professional case handling personnel can conduct research and judgment, and even professional inspection case handling personnel needs to consume a lot of time to induce a few virtual computer-opened group partners, the existing group partner induction method has high requirements on the personnel conducting research and judgment, high subjectivity, different experts possibly induce different group partners according to experience, and low output efficiency.
In the prior art, a machine learning model is generally adopted to analyze the relation data of the billing computers so as to determine the target to be searched, namely the virtual opening partner. However, the currently used community classification algorithm has low classification accuracy and accuracy, so that the effect of searching the target community data is not good.
Therefore, a new method is needed to be designed, the target community can be conveniently identified, the case handling time of the checking case handling personnel is shortened, and the accuracy is high.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a target community identification method, a target community identification device, computer equipment and a storage medium.
In order to achieve the above purpose, the present invention adopts the following technical scheme: the target community identification method comprises the following steps:
acquiring an identification request;
determining a corresponding individual set according to the identification request to obtain a set to be identified;
determining individuals with association relations in the set to be identified to obtain a candidate individual set;
traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with a direct or indirect connection relationship in a graph structure network so as to form a target community;
and sending the related information of the target community to the terminal so that the terminal displays the related information of the target community.
The further technical scheme is as follows: the identification request includes a specified business scenario and parameters defining an association relationship between individuals.
The further technical scheme is as follows: the determining the individuals with the association relationship in the set to be identified to obtain a candidate individual set comprises the following steps:
The relevant information of the set to be identified is arranged into data with the format of < individual, state and moment >, wherein the state is data corresponding to parameters defining the association relation among individuals;
screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified;
acquiring time corresponding to a plurality of individual groups to be identified, and calculating a time difference value corresponding to each individual group to be identified to obtain a to-be-judged difference value corresponding to each individual group to be identified;
screening out individual groups to be identified, corresponding to the individual groups to be identified, of which the difference value to be determined is smaller than a threshold value, so as to obtain intermediate individual groups;
screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers;
judging whether the number of candidates is not less than a frequency threshold;
if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set;
if the candidate number is smaller than the frequency threshold, no association relation exists among all individuals in the set to be identified, and a notice of no existence of the target community is sent to the terminal.
The further technical scheme is as follows: traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with a direct or indirect connection relationship in a graph structure network so as to form a target community, wherein the method comprises the following steps of:
Taking an individual in the candidate individual set as a vertex in the graph, and connecting the vertices corresponding to the two individuals with the association relationship to form a graph structure network;
randomly selecting a vertex from the graph structure network as a traversing starting point, and traversing the graph structure network by adopting a graph traversing algorithm to obtain a related vertex with a connecting line with the vertex so as to obtain a related vertex;
and obtaining individuals corresponding to the associated vertexes to form a target community.
The further technical scheme is as follows: the graph traversal algorithm includes at least one of a depth-first search method and a breadth-first search method.
The further technical scheme is as follows: the parameters defining the association between individuals include the IP addresses of the individuals.
The invention also provides a target community identification device, which comprises:
a request acquisition unit configured to acquire an identification request;
the to-be-identified set determining unit is used for determining a corresponding individual set according to the identification request so as to obtain a to-be-identified set;
the association relation determining unit is used for determining individuals with association relation in the set to be identified so as to obtain a candidate individual set;
the traversal unit is used for traversing the candidate individual set by adopting a graph traversal algorithm to acquire an individual set with a direct or indirect connection relationship in the graph structure network so as to form a target community;
And the information sending unit is used for sending the related information of the target community to the terminal so that the terminal can display the related information of the target community.
The further technical scheme is as follows: the association relation determining unit includes:
a format processing subunit, configured to sort the relevant information of the set to be identified into data with a format of < individual, state, and moment >, where the state is data corresponding to parameters defining an association relationship between individuals;
the first screening subunit is used for screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified;
the difference value calculation subunit is used for obtaining the moments corresponding to the individual groups to be identified, and calculating the moment difference value corresponding to each individual group to be identified so as to obtain the difference value to be judged corresponding to each individual group to be identified;
the second screening subunit is used for screening the to-be-identified individual groups, corresponding to the to-be-identified individual groups, of which the to-be-identified difference value is smaller than a threshold value, so as to obtain an intermediate individual group;
the number calculation subunit is used for screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers;
A judging subunit, configured to judge whether the number of candidates is not less than a frequency threshold; if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set;
and the notification sending subunit is used for sending a notification of the existence of the non-target community to the terminal if the candidate number is smaller than the frequency threshold value and no association relation exists among individuals in all the sets to be identified.
The invention also provides a computer device which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the method when executing the computer program.
The present invention also provides a storage medium storing a computer program which, when executed by a processor, performs the above-described method.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the individuals with association relations are determined according to the identification request, the graph structure network is constructed by the individuals, the graph structure network is traversed by utilizing the graph traversal algorithm, so that all the associated individuals are found, the target communities are determined, the target communities such as the virtual invoice communities can be quickly and accurately found out in the business scene identified by the virtual invoice communities, the target communities are conveniently identified, the case handling time of the checking and case handling personnel is shortened, and the accuracy is high.
The invention is further described below with reference to the drawings and specific embodiments.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic view of an application scenario of a target community identification method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a target community identification method according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a target community identification method according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of a target community identification method according to an embodiment of the present invention;
FIG. 5 is a schematic block diagram of a target community identification apparatus according to an embodiment of the present invention;
FIG. 6 is a schematic block diagram of an association determining unit of a target community identifying apparatus according to an embodiment of the present invention;
FIG. 7 is a schematic block diagram of a traversing unit of the target community identification apparatus according to the embodiment of the present invention;
Fig. 8 is a schematic block diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of a target community identification method according to an embodiment of the present invention. Fig. 2 is a schematic flowchart of a target community identification method according to an embodiment of the present invention. The target community identification method is applied to a server, the server performs data interaction with a terminal, after an identification request is acquired from the terminal, an individual set to be identified is determined according to the identification request, a set with a relation is determined by adopting a graph traversal algorithm, so that a target community is determined, and when the method is executed in a virtual invoice scene, the target community is a virtual opening group.
Fig. 2 is a flowchart illustrating a target community identification method according to an embodiment of the present invention. As shown in fig. 2, the method includes the following steps S110 to S150.
S110, acquiring an identification request.
In this embodiment, the identification request includes a specified business scenario and parameters defining the association relationship between individuals.
The service scenario refers to a scenario under which the method needs to be applied, and in this embodiment, the service scenario refers to a virtual invoice checking scenario, and parameters defining the association relationship between individuals are computer IP addresses of the virtual invoices.
Specifically, the parameter defining the association relationship between individuals includes the IP address of the individual.
S120, determining a corresponding individual set according to the identification request to obtain a set to be identified.
In this embodiment, the set to be identified refers to a natural person, an enterprise, an billing computer, etc. associated with the service scenario of the identification request.
For example: the service scene is Shenzhen virtual invoicing, the parameters defining the association relation between individuals are Shenzhen invoicing computers, and all Shenzhen invoicing computers are defined as the set to be identified. In the business scenario of the value added tax invoice flash response identification pair, individuals refer to billing computers in the Shenzhen, and the individuals can be generalized into a few groups in the subsequent stage.
S130, determining individuals with association relations in the set to be identified to obtain a candidate individual set.
In this embodiment, the candidate individual set refers to two individuals having an association relationship, and the association relationship refers to a relationship in which a certain parameter is the same or associated with.
Determining which individuals in the set to be identified have an association, wherein the two individuals have an association, i.e. an edge exists between the two individuals, and the edge can be directional or undirected, weighted or unweighted.
In this embodiment, the association relationship between the billing computers, that is, the association relationship between the individuals is determined by the behavior of billing based on the billing computer using the common IP address in a short time.
In one embodiment, referring to fig. 3, the step S130 may include steps S131 to S138.
S131, the relevant information of the set to be identified is arranged into data with the format of < individual, state and moment >, wherein the state is data corresponding to parameters defining the association relation among the individuals.
The individual refers to an identification code in a set to be identified, such as an ID number of a computer; the format of the relevant information of the set to be identified is organized into a plurality of N status records about individuals such as < individual, status, moment >, for example < mac1, 101.202.3.4, 13:22:15> represents one record, namely, the device individual mac1 is in 13:22:15 is being located at 101.202.3.4, the IP address is the state, and then the association relationship between individuals can be defined from the recorded data.
S132, screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified.
In this embodiment, the group of individuals to be identified refers to two individuals having the same state.
And when the parameter defining the association relation between the individuals is the IP address of the individual, filling the data in the one unit of the state into a specific value corresponding to the IP address.
S133, acquiring time corresponding to a plurality of individual groups to be identified, and calculating a time difference value corresponding to each individual group to be identified to obtain a difference value to be determined corresponding to each individual group to be identified.
In this embodiment, the difference to be determined corresponding to each individual group to be identified refers to a difference between two moments in the same state.
S134, screening out individual groups to be identified, corresponding to the individual groups to be identified, of which the difference to be determined is smaller than a threshold value, so as to obtain an intermediate individual group.
In this embodiment, the middle individual group refers to an individual group to be identified corresponding to a difference between two moments in the same state being smaller than a preset threshold.
For an individual A and an individual B in the set to be identified, if A is in a state S at a time t1 and B is also in a state S at a time t2, the individual A and the individual B are an individual group to be identified at the moment; the time difference Δt= |t1-t2| between individual a and individual B is small enough to be smaller than a given threshold ts, i.e. Δt= |t1-t2| < ts is satisfied, and a and B are in state S together at the respective instants t1 and t2, i.e. an effective association between a and B is considered to occur in state S, individual a and individual B can be generalized to an intermediate group of individuals.
S135, screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers.
In this embodiment, the candidate number refers to the number of intermediate individual groups corresponding to the same two individuals involved in the two intermediate individual groups, which are different in status between the two intermediate individual groups.
S136, judging whether the number of candidates is not less than a frequency threshold;
and S137, if the number of candidates is not smaller than the frequency threshold, taking the intermediate individual group as a candidate individual set.
If the A and the B have one effective association under n different states, the association relationship between the A and the B is considered to exist.
Such as: the billing computer a billing at the time 2019-12-31, 20:00:00 under IP 192.162.1.1, the billing computer B billing at the time 2019-12-31, 20:00:07 under IP 192.162.1.1, the state S refers to an IP address, the billing computers a and B billing at the same IP address, and the billing time interval is short enough, and the time interval is less than 7 seconds, and is less than a given threshold value of 1 minute, then one effective association is considered to exist between the billing computers a and B, if the billing computers a and B have another effective association at a different IP address 200.186.0.1, then the effective association reaches 2 times, then the association relationship between the billing computers a and B is considered to exist, and the different state number n=2 is designated, that is, the number of times threshold value is 2, although, in other embodiments, the threshold value of the effective association relationship may also be designated, that is, the number of times threshold value.
In this embodiment, the method is used to perform the partner identification of the virtual invoice, and find the partner of the virtual invoice from the original record data, that is, the corresponding computer related data, specifically, the original record data is organized into data in the format of < individual, state, time > and a plurality of such data, and what attribute is selected as the state is determined by the requirement of the service to be manually specified, that is, the identification request from the terminal. For example, the identification request adopts a parameter defining the association relationship of individuals as an IP address, and the IP address is designated as a state attribute, so that different states are different IP addresses, and if a geographic position attribute-city is required as a state on a service, different states are different cities, for example, some individuals are in guangzhou, some individuals are in Hangzhou, some individuals are in Beijing, and the like, and the different cities are different states of the individuals.
Judging that an association relation exists between an individual A and an individual B, and sorting the association relation from original recorded data into < A, shenzhen, 13:22:57>; < B, shenzhen, 13:22:50>; < C, guangzhou, 16:44:21>; < A, shanghai, 14:22:58>; < B, shanghai, 14:22:50>; in the three original records, it is found that the individual A and the individual B are in Shenzhen, the geographical position is taken as a state, and the time points of Shenzhen are very close to each other, the two time points 13:22:57 and 13:22:50 are only 7 seconds different, and less than the threshold ts=1 minute of the time difference which is considered by people, so that the effective association exists between the individual A and the individual B in the data records. Similarly, individuals a and B were once in the open sea and were very close in time, differing by less than 1 minute for only 8 seconds, and an additional effective association was made between individuals a and B in the open sea. Summarizing, the individual A and the individual B generate effective association under the two different 2 states, namely Shenzhen and Shanghai corresponding two states, the association relationship is satisfied, and the individual A and the individual B are considered to have the association relationship.
And S138, if the number of candidates is smaller than the frequency threshold, no association relation exists among individuals in all sets to be identified, and a notice of no existence of the target community is sent to the terminal.
In this embodiment, when no association relationship exists among the individuals in the set to be identified, it is determined that no association relationship exists among the individuals in all the sets to be identified, and a notification of no existence of the target community is sent to the terminal.
And S140, traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with direct or indirect connection relation in the graph structure network so as to form a target community.
In the present embodiment, the target community refers to a collection of individuals having a direct or indirect connection relationship in the graph structure network. In this embodiment, the target community refers to a partner of the virtual invoice.
And traversing individuals with association relations in the network by using a graph traversal algorithm, and summarizing a plurality of groups. By definition, individuals directly or indirectly connected in the graph structure network all belong to the same group.
Storing the candidate individual sets and the association relations between the candidate individual sets in a graph data structure to form a graph structure network, namely, enabling G= < V, E >, wherein G represents the graph data structure, V represents the vertex sets, namely, the individuals in the candidate individual sets, and E represents edges between the vertexes, namely, the association relations between the individuals in the candidate individual sets. Individuals defined to communicate directly or indirectly in the graph structure network all belong to the same group. Based on the definition, each connected subgraph is found out by utilizing the algorithm traversal graph G of graph traversal, and then virtual invoicing group partners, namely target communities, can be induced.
In one embodiment, referring to fig. 4, the step S140 may include steps S141 to S143.
S141, taking the individuals in the candidate individual set as vertexes in the graph, and connecting the vertexes corresponding to the two individuals with the association relationship to form a graph structure network.
In this embodiment, the graph structure network refers to a graph structure formed by a set of candidate individuals, and two individuals in the candidate individuals have an association relationship, that is, there is an edge between the two individuals, and the edge may be directional or undirected, weighted or not weighted, thereby forming a graph structure.
In graph theory, the connected graph is based on the concept of connected. In an undirected graph G, if there is a path from vertex i to vertex j, there is certainly a path from j to i, then i and j are said to be connected. If G is a directed graph, all edges in the path connecting i and j must be co-directional, the graph is called a connected graph if any two points in the graph are connected, and a strongly connected graph if the graph is a directed graph. Connectivity of the graph is a fundamental property of the graph fabric network.
S142, randomly selecting a vertex from the graph structure network as a traversing starting point, and traversing the graph structure network by adopting a graph traversing algorithm to obtain a related vertex with a connecting line with the vertex so as to obtain the related vertex.
In this embodiment, the associated vertex refers to a vertex that is directly or indirectly connected to a randomly selected vertex.
The graph traversal algorithm includes at least one of a depth-first search method and a breadth-first search method.
For a known graph structure network g= < E, V >, where E represents the set of edges in the graph, V represents the set of vertices in the graph, a vertex V is randomly selected from V as the starting point of traversal, a graph traversal algorithm such as BFS (breadth First traversal, breadth First Search) or DFS (Depth First Search) is selected, all vertices S in the connected graph found after traversal are eliminated from V, and the eliminated vertices are output as a partner. And repeatedly and randomly selecting vertexes from V to perform graph traversal and outputting the group partner until no vertexes in V are empty, and completing the group partner discovery process.
In this embodiment, the depth-first search method is a popularization of tree root traversal, and its basic idea is to start from a certain vertex v0 of the graph G, access v0, then select a vertex vi adjacent to v0 and not accessed to access, then select a vertex vj adjacent to vi and not accessed to access from vi, and continue in sequence. If all adjacent vertexes of the currently visited vertexes are visited, returning to the vertex w with the non-visited adjacent vertexes in the visited vertex sequence, and traversing forward from w in the same way until all vertexes in the graph are visited.
The breadth-first search method is a hierarchical traversal popularization of the tree, the basic idea of which is to first access an initial point vi and mark it as accessed, then access all non-accessed neighbor points vi1, vi2, …, vi t of vi and mark accessed, then access all non-accessed neighbor points of each vertex in the order of vi1, vi2, …, vit and mark it as accessed, and so on until all vertices in the graph that have path communication with the initial point vi are accessed.
S143, obtaining individuals corresponding to the associated vertexes to form a target community.
After traversing the graph structure network, individuals corresponding to all vertexes associated with a certain vertex can be obtained, so that the individuals corresponding to the vertexes are combined to form a group of virtual invoices, namely a target community.
And S150, sending the related information of the target community to the terminal so that the terminal displays the related information of the target community.
When the target community is determined, the information of the individual, the state and the time corresponding to the target community can be sent to the terminal to be displayed on the terminal, so that subsequent tracing and the like can be performed.
In the embodiment, the method is based on a qualitative virtual-issuing value-added tax invoice tool, and an indeterminate invoicing tool with an association relation with the qualitative virtual-issuing tool can be found out by utilizing a defined individual association relation; furthermore, the method is utilized to carry out the group induction on the equipment with the association relation, and the group numbers to which each billing tool belongs are obtained, so that the group induction is completed, the currently active virtual billing tool group is successfully found out, the case-handling time of the checking case-handling personnel is greatly shortened, and the assistance is provided for the accurate and rapid virtual-typing of the checking case-handling personnel.
According to the target community identification method, the individuals with the association relation are determined according to the identification request, the graph structure network is constructed by the individuals, the graph structure network is traversed by utilizing the graph traversal algorithm to find out all the associated individuals, so that the target communities are determined, the target communities such as the virtual invoice communities can be quickly and accurately found out in the business scene of the virtual invoice community identification, the target communities can be conveniently identified, the case handling time of the auditing and case handling personnel is shortened, and the accuracy is high.
Fig. 5 is a schematic block diagram of a target community identification apparatus 300 according to an embodiment of the present invention. As shown in fig. 5, the present invention further provides a target community recognition device 300 corresponding to the above target community recognition method. The target community recognition apparatus 300 includes a unit for performing the target community recognition method described above, and may be configured in a server. Specifically, referring to fig. 5, the target community identification apparatus 300 includes a request acquisition unit 301, a set to be identified determination unit 302, an association relationship determination unit 303, a traversal unit 304, and an information transmission unit 305.
A request acquisition unit 301 for acquiring an identification request; a to-be-identified set determining unit 302, configured to determine a corresponding individual set according to the identification request, so as to obtain a to-be-identified set; an association determining unit 303, configured to determine individuals having association in the set to be identified, so as to obtain a candidate individual set; a traversing unit 304, configured to traverse the candidate individual set by using a graph traversal algorithm, so as to obtain an individual set having a direct or indirect connection relationship in the graph structure network, so as to form a target community; an information sending unit 305, configured to send the related information of the target community to the terminal, so that the terminal displays the related information of the target community.
In one embodiment, as shown in fig. 6, the association determining unit 303 includes a format processing subunit 3031, a first filtering subunit 3032, a difference calculating subunit 3033, a second filtering subunit 3034, a number calculating subunit 3035, a judging subunit 3036 and a notification sending subunit 3037.
A format processing subunit 3031, configured to sort the relevant information of the set to be identified into data with a format of < individual, state, and moment >, where the state is data corresponding to parameters defining an association relationship between individuals; a first screening subunit 3032, configured to screen all two individuals in the same state according to the identification request, so as to obtain a plurality of to-be-identified individual groups; the difference value calculating subunit 3033 is configured to obtain moments corresponding to a plurality of to-be-identified individual groups, and calculate a moment difference value corresponding to each to-be-identified individual group, so as to obtain a to-be-determined difference value corresponding to each to-be-identified individual group; a second screening subunit 3034, configured to screen an individual group to be identified, where the difference value to be determined corresponding to the individual group to be identified is smaller than a threshold value, so as to obtain an intermediate individual group; a number calculation subunit 3035, configured to screen the number of intermediate individual groups with different states and identical individuals from the intermediate individual groups, so as to obtain a candidate number; a judging subunit 3036, configured to judge whether the number of candidates is not less than the frequency threshold; if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set; and the notification sending subunit 3037 is configured to send, to the terminal, a notification that no target community exists if the candidate number is smaller than the frequency threshold and no association relationship exists between the individuals in all the sets to be identified.
In one embodiment, as shown in fig. 7, the traversal unit 304 includes a network formation sub-unit 3041, a vertex traversal sub-unit 3042, and an individual acquisition sub-unit 3043.
A network forming subunit 3041, configured to connect vertices corresponding to two individuals with an association relationship with an individual in the candidate individual set as vertices in the graph, so as to form a graph structure network; a vertex traversing subunit 3042, configured to randomly select a vertex from the graph structure network as a traversing starting point, and perform the traversing of the graph structure network by using a graph traversing algorithm to obtain a related vertex having a connection with the vertex, so as to obtain a related vertex; an individual obtaining subunit 3043, configured to obtain an individual corresponding to the associated vertex, so as to form a target community.
It should be noted that, as will be clearly understood by those skilled in the art, the specific implementation process of the target community identifying apparatus 300 and each unit may refer to the corresponding description in the foregoing method embodiment, and for convenience and brevity of description, the description is omitted here.
The target community identifying apparatus 300 described above may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 8.
Referring to fig. 8, fig. 8 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a server, where the server may be a stand-alone server or may be a server cluster formed by a plurality of servers.
With reference to FIG. 8, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a target community identification method.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the execution of a computer program 5032 in the non-volatile storage medium 503, which computer program 5032, when executed by the processor 502, causes the processor 502 to perform a target community identification method.
The network interface 505 is used for network communication with other devices. It will be appreciated by those skilled in the art that the architecture shown in fig. 8 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting of the computer device 500 to which the present inventive arrangements may be implemented, as a particular computer device 500 may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
Wherein the processor 502 is configured to execute a computer program 5032 stored in a memory to implement the steps of:
acquiring an identification request; determining a corresponding individual set according to the identification request to obtain a set to be identified; determining individuals with association relations in the set to be identified to obtain a candidate individual set; traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with a direct or indirect connection relationship in a graph structure network so as to form a target community; and sending the related information of the target community to the terminal so that the terminal displays the related information of the target community.
Wherein the identification request includes a specified business scenario and parameters defining an association relationship between individuals.
The parameters defining the association between individuals include the IP addresses of the individuals.
In an embodiment, when the step of determining the individuals having the association relationship in the set to be identified to obtain the candidate individual set is implemented by the processor 502, the following steps are specifically implemented:
the relevant information of the set to be identified is arranged into data with the format of < individual, state and moment >, wherein the state is data corresponding to parameters defining the association relation among individuals; screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified; acquiring time corresponding to a plurality of individual groups to be identified, and calculating a time difference value corresponding to each individual group to be identified to obtain a to-be-judged difference value corresponding to each individual group to be identified; screening out individual groups to be identified, corresponding to the individual groups to be identified, of which the difference value to be determined is smaller than a threshold value, so as to obtain intermediate individual groups; screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers; judging whether the number of candidates is not less than a frequency threshold; if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set; if the candidate number is smaller than the frequency threshold, no association relation exists among all individuals in the set to be identified, and a notice of no existence of the target community is sent to the terminal.
In one embodiment, when the step of traversing the candidate individual set by using the graph traversal algorithm to obtain the individual set having a direct or indirect connection relationship in the graph structure network to form the target community, the processor 502 specifically implements the following steps:
taking an individual in the candidate individual set as a vertex in the graph, and connecting the vertices corresponding to the two individuals with the association relationship to form a graph structure network; randomly selecting a vertex from the graph structure network as a traversing starting point, and traversing the graph structure network by adopting a graph traversing algorithm to obtain a related vertex with a connecting line with the vertex so as to obtain a related vertex; and obtaining individuals corresponding to the associated vertexes to form a target community.
The graph traversal algorithm comprises at least one of a depth-first search method and a breadth-first search method.
It should be appreciated that in an embodiment of the application, the processor 502 may be a central processing unit (Central Processing Unit, CPU), the processor 502 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Those skilled in the art will appreciate that all or part of the flow in a method embodying the above described embodiments may be accomplished by computer programs instructing the relevant hardware. The computer program comprises program instructions, and the computer program can be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer readable storage medium. The storage medium stores a computer program which, when executed by a processor, causes the processor to perform the steps of:
acquiring an identification request; determining a corresponding individual set according to the identification request to obtain a set to be identified; determining individuals with association relations in the set to be identified to obtain a candidate individual set; traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with a direct or indirect connection relationship in a graph structure network so as to form a target community; and sending the related information of the target community to the terminal so that the terminal displays the related information of the target community.
Wherein the identification request includes a specified business scenario and parameters defining an association relationship between individuals.
The parameters defining the association between individuals include the IP addresses of the individuals.
In one embodiment, when the processor executes the computer program to implement the step of determining the individuals having association relationships in the set to be identified to obtain a candidate individual set, the method specifically includes the following steps:
the relevant information of the set to be identified is arranged into data with the format of < individual, state and moment >, wherein the state is data corresponding to parameters defining the association relation among individuals; screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified; acquiring time corresponding to a plurality of individual groups to be identified, and calculating a time difference value corresponding to each individual group to be identified to obtain a to-be-judged difference value corresponding to each individual group to be identified; screening out individual groups to be identified, corresponding to the individual groups to be identified, of which the difference value to be determined is smaller than a threshold value, so as to obtain intermediate individual groups; screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers; judging whether the number of candidates is not less than a frequency threshold; if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set; if the candidate number is smaller than the frequency threshold, no association relation exists among all individuals in the set to be identified, and a notice of no existence of the target community is sent to the terminal.
In one embodiment, when the processor executes the computer program to implement the step of traversing the candidate individual set by using a graph traversal algorithm to obtain an individual set having a direct or indirect connection relationship in the graph structure network, to form a target community, the method specifically includes the following steps:
taking an individual in the candidate individual set as a vertex in the graph, and connecting the vertices corresponding to the two individuals with the association relationship to form a graph structure network; randomly selecting a vertex from the graph structure network as a traversing starting point, and traversing the graph structure network by adopting a graph traversing algorithm to obtain a related vertex with a connecting line with the vertex so as to obtain a related vertex; and obtaining individuals corresponding to the associated vertexes to form a target community.
The graph traversal algorithm comprises at least one of a depth-first search method and a breadth-first search method.
The storage medium may be a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, or other various computer-readable storage media that can store program codes.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. 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 invention.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be combined, divided and deleted according to actual needs. In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The integrated unit may be stored in a storage medium if implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a terminal, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (7)
1. The target community identification method is characterized by comprising the following steps:
acquiring an identification request;
determining a corresponding individual set according to the identification request to obtain a set to be identified;
determining individuals with association relations in the set to be identified to obtain a candidate individual set;
traversing the candidate individual set by adopting a graph traversing algorithm to obtain an individual set with a direct or indirect connection relationship in a graph structure network so as to form a target community;
the related information of the target community is sent to the terminal, so that the terminal displays the related information of the target community;
the identification request comprises a designated service scene and parameters defining the association relationship between individuals;
the determining the individuals with the association relationship in the set to be identified to obtain a candidate individual set comprises the following steps:
The relevant information of the set to be identified is arranged into data with the format of < individual, state and moment >, wherein the state is data corresponding to parameters defining the association relation among individuals;
screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified;
acquiring time corresponding to a plurality of individual groups to be identified, and calculating a time difference value corresponding to each individual group to be identified to obtain a to-be-judged difference value corresponding to each individual group to be identified;
screening out individual groups to be identified, corresponding to the individual groups to be identified, of which the difference value to be determined is smaller than a threshold value, so as to obtain intermediate individual groups;
screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers;
judging whether the number of candidates is not less than a frequency threshold;
if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set;
if the candidate number is smaller than the frequency threshold, no association relation exists among individuals in all sets to be identified, and a notice of no existence of the target community is sent to the terminal;
performing the partner identification of the virtual invoices, finding out the partner of the virtual invoices from the original recorded data, and arranging the original recorded data into data in the format of individual, state and moment, wherein the identification request of the terminal determines what attribute is selected as the state; the identification request adopts a parameter defining the association relation of the individual as an IP address, the IP address is designated as a state attribute, then different states are different IP addresses, and if the geographic position attribute-city is required to be used as the state on the service, the different states are different cities, and the different cities are the different states of the individual.
2. The method of claim 1, wherein traversing the set of candidate individuals using a graph traversal algorithm to obtain the set of individuals having direct or indirect connection relationships in the graph structure network to form the target community comprises:
taking an individual in the candidate individual set as a vertex in the graph, and connecting the vertices corresponding to the two individuals with the association relationship to form a graph structure network;
randomly selecting a vertex from the graph structure network as a traversing starting point, and traversing the graph structure network by adopting a graph traversing algorithm to obtain a related vertex with a connecting line with the vertex so as to obtain a related vertex;
and obtaining individuals corresponding to the associated vertexes to form a target community.
3. The target community identification method of claim 2, wherein the graph traversal algorithm comprises at least one of a depth-first search method and a breadth-first search method.
4. The target community identification method of claim 1, wherein the parameter defining the association relationship between individuals includes an IP address of the individual.
5. The target community identification device is characterized by comprising:
a request acquisition unit configured to acquire an identification request;
The to-be-identified set determining unit is used for determining a corresponding individual set according to the identification request so as to obtain a to-be-identified set;
the association relation determining unit is used for determining individuals with association relation in the set to be identified so as to obtain a candidate individual set;
the traversal unit is used for traversing the candidate individual set by adopting a graph traversal algorithm to acquire an individual set with a direct or indirect connection relationship in the graph structure network so as to form a target community;
an information sending unit, configured to send related information of the target community to a terminal, so that the terminal displays the related information of the target community;
the association relation determining unit includes:
a format processing subunit, configured to sort the relevant information of the set to be identified into data with a format of < individual, state, and moment >, where the state is data corresponding to parameters defining an association relationship between individuals;
the first screening subunit is used for screening all two individuals in the same state according to the identification request to obtain a plurality of individual groups to be identified;
the difference value calculation subunit is used for obtaining the moments corresponding to the individual groups to be identified, and calculating the moment difference value corresponding to each individual group to be identified so as to obtain the difference value to be judged corresponding to each individual group to be identified;
The second screening subunit is used for screening the to-be-identified individual groups, corresponding to the to-be-identified individual groups, of which the to-be-identified difference value is smaller than a threshold value, so as to obtain an intermediate individual group;
the number calculation subunit is used for screening the number of the intermediate individual groups which are different in state and identical in individual from the intermediate individual groups to obtain candidate numbers;
a judging subunit, configured to judge whether the number of candidates is not less than a frequency threshold; if the number of candidates is not less than the frequency threshold, taking the intermediate individual group as a candidate individual set;
a notification sending subunit, configured to send a notification that no target community exists to the terminal if the number of candidates is less than the frequency threshold, and if no association relationship exists between individuals in all the sets to be identified;
performing the partner identification of the virtual invoices, finding out the partner of the virtual invoices from the original recorded data, and arranging the original recorded data into data in the format of individual, state and moment, wherein the identification request of the terminal determines what attribute is selected as the state; the identification request adopts a parameter defining the association relation of the individual as an IP address, the IP address is designated as a state attribute, then different states are different IP addresses, and if the geographic position attribute-city is required to be used as the state on the service, the different states are different cities, and the different cities are the different states of the individual.
6. A computer device, characterized in that it comprises a memory on which a computer program is stored and a processor which, when executing the computer program, implements the method according to any of claims 1-4.
7. A storage medium storing a computer program which, when executed by a processor, performs the method of any one of claims 1 to 4.
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| CN113806600B (en) * | 2021-09-29 | 2023-09-15 | 中国平安人寿保险股份有限公司 | Method, device, equipment and medium for constructing family relation network of service data |
| CN113837874B (en) * | 2021-11-22 | 2022-04-12 | 北京芯盾时代科技有限公司 | Data identification method and device, storage medium and electronic equipment |
| CN114610921B (en) * | 2021-11-30 | 2023-02-28 | 腾讯科技（深圳）有限公司 | Object cluster portrait determination method, device, computer equipment and storage medium |
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