CN109753527A - Abnormal enterprise's method for digging, device, computer equipment and storage medium - Google Patents
Abnormal enterprise's method for digging, device, computer equipment and storage medium Download PDFInfo
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- CN109753527A CN109753527A CN201910004378.1A CN201910004378A CN109753527A CN 109753527 A CN109753527 A CN 109753527A CN 201910004378 A CN201910004378 A CN 201910004378A CN 109753527 A CN109753527 A CN 109753527A
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Abstract
This application involves a kind of abnormal enterprise's method for digging, device, computer equipment and storage mediums based on association map, this method comprises: obtaining the abnormal enterprise mark of known exception enterprise；From the association map pre-established, searches and abnormal enterprise's mark is identified there are the level-one affiliated enterprise of incidence relation and level-one associate people identifies；It is identified as association starting point with the level-one associate people, there are the second level affiliated enterprise of incidence relation marks with level-one associate people mark for lookup from the association map；Level-one affiliated enterprise mark and second level affiliated enterprise mark are compared with the enterprise's mark for including in preset enterprise's blacklist respectively；The enterprise to be detected that the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise identify unique identification respectively is determined as abnormal enterprise.Abnormal enterprise's digging efficiency can be improved using this method.
Description
Technical field
This application involves field of computer technology, set more particularly to a kind of abnormal enterprise method for digging, device, computer
Standby and storage medium.
Background technique
With the rapid development of science and technology, the quantity of enterprise gradually increases, and the type of enterprise is also increasing.However,
Influence of the quality of one enterprise to entire society be it is great, it is most important to the abnormality detection of enterprise.
In conventional method, abnormal enterprise is detected, the information for obtaining enterprise operation etc. is usually required, by superintendent
Member manually checks enterprise operation information, to judge whether the enterprise is abnormal enterprise.It will be apparent that this pass through superintendent
The member mode manually checked identifies abnormal enterprise, and efficiency is very low.
Summary of the invention
Based on this, it is necessary in view of the above technical problems, provide a kind of exception that can be improved abnormal Corporate Identity efficiency
Enterprise's method for digging, device, computer equipment and storage medium.
A kind of exception enterprise method for digging, which comprises
Obtain the abnormal enterprise mark of known exception enterprise；
From the association map pre-established, there are the level-ones of incidence relation to be associated with enterprise with abnormal enterprise's mark for lookup
Industry mark and level-one associate people mark；
It is identified as association starting point with the level-one associate people, is searched and the level-one affiliated person from the association map
There are the second level affiliated enterprise of incidence relation marks for member's mark；
Level-one affiliated enterprise mark and second level affiliated enterprise mark are marked with the enterprise in preset enterprise's blacklist respectively
Knowledge is compared；
By the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise mark difference unique identification
Enterprise to be detected be determined as abnormal enterprise.
In one of the embodiments, the method also includes:
It is identified as association starting point with the level-one associate people, from the association map, lookup is associated with the level-one
There are the second level associate people of incidence relation marks by giver identification；
The second level associate people is identified as association starting point, from the association map, searches and is closed with the second level
Joining giver identification, there are the three-level affiliated enterprise of incidence relation marks；
When determining that enterprise's blacklist is identified there are the three-level affiliated enterprise, then the three-level affiliated enterprise is determined
The enterprise to be detected for identifying institute's unique identification is abnormal enterprise.
In one of the embodiments, the method also includes:
When level-one affiliated enterprise mark is not present in enterprise's blacklist, then obtain corresponding to level-one affiliated enterprise mark
First anomaly analysis basic data；In the anomaly analysis model that first anomaly analysis basic data input is trained in advance,
Anomaly analysis result of the output for the enterprise to be detected of level-one affiliated enterprise mark institute's unique identification；
When second level affiliated enterprise mark is not present in enterprise's blacklist, then obtain corresponding to second level affiliated enterprise mark
Second anomaly analysis basic data；The second anomaly analysis basic data is inputted in the anomaly analysis model, needle is exported
To the anomaly analysis result of the enterprise to be detected of second level affiliated enterprise mark institute's unique identification.
It is described in one of the embodiments, to obtain the first corresponding anomaly analysis basis number of level-one affiliated enterprise mark
According to including:
From association map in, search with the level-one affiliated enterprise mark have incidence relation first event information and/
Or first information, obtain include the first event information and/or the first information the first anomaly analysis basis number
According to.
It is described in one of the embodiments, to obtain the second corresponding anomaly analysis basis number of second level affiliated enterprise mark
According to including:
From association map, the second event information and/or that there is incidence relation with second level affiliated enterprise mark is searched
Two informations, obtain include the second event information and/or the second information the second anomaly analysis basic data.
In one of the embodiments, the method also includes:
Negative operation event associated with abnormal enterprise's mark is obtained according to the association map, and is established described negative
First degree of risk conduct the relation between operation event and abnormal enterprise's mark；
It regard level-one associate people mark as conducting spots, establishes abnormal enterprise's mark with second level affiliated enterprise and identify it
Between second degree of risk conduct the relation；
Three-level associate people mark associated with the second level affiliated enterprise mark is searched from association map；
It obtains and identifies the associated level Four affiliated enterprise mark in association map with the three-level associate people；
It regard three-level associate people mark as conducting spots, establishes the second level affiliated enterprise mark and be associated with enterprise with level Four
Third degree risk conduct the relation between industry mark；
According to first degree, second degree and third degree risk conduct the relation, risk conduct the relation figure is constructed.
In one of the embodiments, from the association map pre-established, lookup is deposited with abnormal enterprise's mark
Before the level-one affiliated enterprise mark and level-one associate people mark of incidence relation, the method also includes:
Obtain the association analysis basic data including company information and enterprise key personal information；
Analysis processing is associated to the association analysis basic data；
According to association analysis as a result, extracting enterprise's mark from company information, and extracted from enterprise key personal information
Giver identification, and establish the incidence relation between enterprise's mark and enterprise's mark, enterprise's mark and giver identification；
According to the incidence relation of foundation, building association map.
A kind of exception enterprise excavating gear, described device include:
Module is obtained, the abnormal enterprise for obtaining known exception enterprise identifies；
Associative search module is closed for from the association map pre-established, searching to exist with abnormal enterprise's mark
The level-one affiliated enterprise mark and level-one associate people mark of connection relationship；It is identified as association starting point with the level-one associate people,
There are the second level affiliated enterprise of incidence relation marks with level-one associate people mark for lookup from the association map；
Abnormal enterprise's determination module, for respectively by level-one affiliated enterprise mark and second level affiliated enterprise identify with it is preset
The enterprise's mark for including in enterprise's blacklist is compared；By the level-one affiliated enterprise being included in enterprise's blacklist mark and two
The enterprise to be detected that grade affiliated enterprise identifies unique identification respectively is determined as abnormal enterprise.
A kind of computer equipment, including memory and processor, the memory are stored with computer program, the processing
Device performs the steps of when executing the computer program
Obtain the abnormal enterprise mark of known exception enterprise；
From the association map pre-established, there are the level-ones of incidence relation to be associated with enterprise with abnormal enterprise's mark for lookup
Industry mark and level-one associate people mark；
It is identified as association starting point with the level-one associate people, is searched and the level-one affiliated person from the association map
There are the second level affiliated enterprise of incidence relation marks for member's mark；
The enterprise that will include in level-one affiliated enterprise mark and second level affiliated enterprise mark and preset enterprise's blacklist respectively
Industry mark is compared；
By the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise mark difference unique identification
Enterprise to be detected be determined as abnormal enterprise.
A kind of computer readable storage medium, is stored thereon with computer program, and the computer program is held by processor
It is performed the steps of when row
Obtain the abnormal enterprise mark of known exception enterprise；
From the association map pre-established, there are the level-ones of incidence relation to be associated with enterprise with abnormal enterprise's mark for lookup
Industry mark and level-one associate people mark；
It is identified as association starting point with the level-one associate people, is searched and the level-one affiliated person from the association map
There are the second level affiliated enterprise of incidence relation marks for member's mark；
The enterprise that will include in level-one affiliated enterprise mark and second level affiliated enterprise mark and preset enterprise's blacklist respectively
Industry mark is compared；
By the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise mark difference unique identification
Enterprise to be detected be determined as abnormal enterprise.
Above-mentioned exception enterprise method for digging, device, computer equipment and storage medium, by including enterprise and enterprise, enterprise
Industry is associated with map with personnel this three degree of incidence relations, in conjunction with clearly knowing in the presence of abnormal abnormal enterprise mark, to look into
It finds out that there are the level-one affiliated enterprise of incidence relation marks and level-one associate people mark with abnormal enterprise's mark, and is based on
Level-one associate people identifier lookup goes out associated second level affiliated enterprise mark.It can more in depth excavate and known exception
Enterprise has an affiliated enterprise of incidence relation, and with abnormal enterprise there are the abnormal risks of the affiliated enterprise of incidence relation often very
It is high.In turn, in conjunction with the enterprise to be detected that enterprise's blacklist identifies firsts and seconds affiliated enterprise carries out exception and sentences
It is fixed, when firsts and seconds affiliated enterprise mark is present in enterprise's blacklist, then determine the enterprise that it is identified for abnormal enterprise
Industry.That is, association map and enterprise's blacklist based on various dimensions incidence relation can be quick, quasi- from known exception enterprise
Abnormal enterprise really is excavated, digging efficiency is improved.
Detailed description of the invention
Fig. 1 is the application scenario diagram of abnormal enterprise method for digging in one embodiment；
Fig. 2 is the flow diagram of abnormal enterprise method for digging in one embodiment；
Fig. 3 is the flow diagram of one embodiment risk conduct the relation figure generation step；
Fig. 4 is the schematic diagram of one embodiment risk conduct the relation figure；
Fig. 5 is the structural block diagram of abnormal enterprise excavating gear in one embodiment；
Fig. 6 is the structural block diagram of abnormal enterprise excavating gear in another embodiment；
Fig. 7 is the internal structure chart of computer equipment in one embodiment.
Specific embodiment
It is with reference to the accompanying drawings and embodiments, right in order to which the objects, technical solutions and advantages of the application are more clearly understood
The application is further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the application, not
For limiting the application.
Exception enterprise provided by the present application method for digging, can be applied in application environment as shown in Figure 1.Wherein, it takes
Business device 110 is attached with terminal 120 by network.Wherein, server 110, can be either multiple with independent server
The server cluster of server composition is realized.Terminal 120 can be, but not limited to be various personal computers, laptop,
Smart phone, tablet computer and portable wearable device.
User can be inputted or be selected known exception enterprise by terminal 120.Terminal 120 obtains the different of known exception enterprise
Chang Qiye mark, and abnormal enterprise mark is sent to server 110.Server 110 can be from the association map pre-established
In, it searches and abnormal enterprise's mark is identified there are the level-one affiliated enterprise of incidence relation and level-one associate people identifies；With level-one
Associate people is identified as association starting point, and there are the second level of incidence relation passes with level-one associate people mark for lookup from association map
Join enterprise's mark；To include in level-one affiliated enterprise mark and second level affiliated enterprise mark and preset enterprise's blacklist respectively
Enterprise's mark is compared；By the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise mark difference
The enterprise to be detected of unique identification is determined as abnormal enterprise.
It should be noted that " first " and " second " in each embodiment of the application is only used for distinguishing, be not used as sequence,
The restriction of subordinate etc..
In one embodiment, as shown in Fig. 2, providing a kind of abnormal enterprise method for digging, it is applied to Fig. 1 in this way
In server 110 for be illustrated, comprising the following steps:
S202 obtains the abnormal enterprise mark of known exception enterprise.
It is known that abnormal enterprise, is it is known that there is abnormal enterprise.Abnormal enterprise's mark is known exception enterprise
The enterprise of industry identifies.
Specifically, user can pass through terminal input or selected known exception enterprise.Terminal obtains known exception enterprise
Abnormal enterprise's mark, and abnormal enterprise mark is sent to server.
S204, from the association map pre-established, there are the level-ones of incidence relation to be associated with abnormal enterprise's mark for lookup
Enterprise's mark and level-one associate people mark.
Wherein, it is associated with map, is the graph-based to incidence relation, that is, is the network of personal connections established based on incidence relation
Network figure.
It should be noted that being associated in map includes that enterprise's mark is identified with enterprise, enterprise's mark and people in the present embodiment
Three degree of incidence relations between member's mark.
In one embodiment, the incidence relation between enterprise's mark and enterprise's mark may include cooperative relationship, transaction
At least one of relationship, holding types such as relationship and competitive relation.In one embodiment, enterprise mark with giver identification it
Between incidence relation, may include at least one of types such as investment relation, ownership and membership relations and guarantee's relationship.
In one embodiment, association map can also further include other other than including above-mentioned three degree of incidence relations
The incidence relation of dimension, for example, can also be including the incidence relation between giver identification and giver identification (for example, relatives are associated with
Relationship or transaction association relationship), enterprise mark event information between incidence relation and enterprise mark and information it
Between at least one of incidence relation etc..
Level-one affiliated enterprise mark, be with abnormal enterprise mark there are the enterprise of level-one incidence relation marks.Level-one association
Giver identification, be with abnormal enterprise mark there are the giver identifications of level-one incidence relation.Level-one incidence relation refers to direct correlation
Relationship.It should be noted that the incidence relation of each rank such as level-one, second level, three-level and level Four in each embodiment of the application,
For indicating the distance of the incidence relation between abnormal enterprise's mark, and enterprise's mark is not limited and giver identification uses together
A type of incidence relation is searched.
Specifically, server can position abnormal enterprise's mark, then search and fixed from the association map pre-established
There are the enterprise of level-one incidence relation mark and giver identifications for the abnormal enterprise mark of position, obtain level-one affiliated enterprise mark and one
Grade associate people mark.
It is appreciated that server can identify corresponding various incidence relations in association map according to abnormal enterprise
Type searches the enterprise's mark for having level-one incidence relation with abnormal enterprise's mark and giver identification respectively.For example, server can
With according to cooperative relationship, transaction relationship, holding relationship and competitive relation etc., searching with abnormal enterprise's mark there is level-one to close respectively
The enterprise of connection relationship identifies, and according to investment relation, ownership and membership relations and guarantee's relationship etc., searches and has with abnormal enterprise's mark
There is the giver identification of level-one incidence relation.It should be noted that here, only wants to search to have with abnormal enterprise's mark and be associated with
The level-one affiliated enterprise of relationship identifies and level-one associate people mark, specific used association when being not limited to search
The type of relationship.
In one embodiment, before step S204, this method further includes the steps that establishing association map, specifically includes
Following steps: the association analysis basic data including company information and enterprise key personal information is obtained；To association analysis basis
Data are associated analysis processing；According to association analysis as a result, extracting enterprise's mark from company information, and from enterprise key people
Member information in extract giver identification, and establish enterprise mark with enterprise mark, enterprise mark and being associated between giver identification
System；According to the incidence relation of foundation, building association map.
Wherein, association analysis basic data is the data for being associated analysis.Company information is related to enterprise
Information.Company information, including enterprise's mark.Enterprise key personal information refers to information relevant to enterprise key personnel.Enterprise
Industry core person information, including giver identification.Enterprise key personnel refer to decisive, nuclear for enterprise expansion projects
The personnel of effect.
In one embodiment, enterprise key personnel, including legal determine representative, company director, shareholder and public affairs
Take charge of at least one of senior executive etc..
Specifically, the available association analysis basis number including company information and enterprise key personal information of server
According to.Further, server can be associated analysis processing to association analysis basic data, to obtain association analysis result.
It is appreciated that association analysis is as a result, be the result for analyzing the incidence relation between enterprise and enterprise, enterprise and personnel.Service
Device can be identified according to association analysis as a result, extracting enterprise from company information, and extract people from enterprise key personal information
Member's mark, and establish the incidence relation between enterprise's mark and enterprise's mark, enterprise's mark and giver identification.Server can incite somebody to action
The incidence relation of foundation is patterned expression, to construct association map.
S206 is identified as association starting point with level-one associate people, searches from association map and identifies with level-one associate people
There are the second level affiliated enterprise of incidence relation marks.
Wherein, it is associated with starting point, that is, searches the starting point of incidence relation.Second level affiliated enterprise mark is identified with abnormal enterprise
There are the enterprise of second level incidence relation marks.
Specifically, server can be identified as association starting point with level-one associate people, lookup and level-one from association map
There are the enterprise of direct correlation relationship marks for associate people mark.It is directly closed it is appreciated that existing with level-one associate people mark
The enterprise of connection relationship identifies, i.e., is identified by level-one associate people and establish indirect association relationship between abnormal enterprise's mark, from
And with abnormal enterprise mark there are second level incidence relations, therefore, be properly termed as second level affiliated enterprise mark.
Level-one affiliated enterprise mark and second level affiliated enterprise are identified respectively and include in preset enterprise's blacklist by S208
Enterprise mark be compared.
Wherein, enterprise's blacklist is the inventory for having recorded abnormal enterprise's mark.
Specifically, be stored in advance enterprise's blacklist in server, server level-one affiliated enterprise can be identified with it is pre-
If enterprise's blacklist in include enterprise mark be compared, and by second level affiliated enterprise mark with preset enterprise's blacklist
In include enterprise mark be compared, with judge level-one affiliated enterprise mark and second level affiliated enterprise identify whether be located at enterprise
In blacklist.
S210, the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise mark is unique respectively
The enterprise to be detected of mark is determined as abnormal enterprise.
It should be noted that enterprise to be detected, that is, refer to whether not yet know is abnormal enterprise, and need through the application reality
The method in example is applied to detect the enterprise for determining whether abnormal enterprise.
It is appreciated that when level-one affiliated enterprise mark or second level affiliated enterprise mark are present in enterprise's blacklist, i.e.,
Level-one affiliated enterprise mark or second level affiliated enterprise mark are included in enterprise's blacklist, then can will be included in enterprise's blacklist
In level-one affiliated enterprise mark and the enterprise to be detected of second level affiliated enterprise mark unique identification respectively be determined as abnormal enterprise.
It is appreciated that when there is no level-one affiliated enterprise mark or second level affiliated enterprise marks in enterprise's blacklist
When, server can directly identify level-one affiliated enterprise or the enterprise to be detected of second level affiliated enterprise mark institute's unique identification is sentenced
It is set to normal enterprise.Server is also available to be associated with enterprise with the level-one affiliated enterprise being not present in blacklist mark or second level
Industry identifies corresponding data, with further to level-one affiliated enterprise mark or second level affiliated enterprise mark institute's unique identification to
It detects enterprise and carries out anomaly analysis.
Above-mentioned exception enterprise method for digging, passes through the pass including this three degree of incidence relations of enterprise Yu enterprise, enterprise and personnel
Join map, in conjunction with clearly knowing to identify in the presence of abnormal abnormal enterprise, exists to find out with abnormal enterprise's mark
The level-one affiliated enterprise mark and level-one associate people mark of incidence relation, and correlation is gone out based on level-one associate people identifier lookup
The second level affiliated enterprise of connection identifies.It can more in depth excavate and be associated with enterprise with incidence relation with known exception enterprise
Industry, and that there are the abnormal risks of the affiliated enterprise of incidence relation is often very high with abnormal enterprise.In turn, in conjunction with the black name of enterprise
Single pair firsts and seconds affiliated enterprise identifies identified enterprise and carries out abnormal determination, when firsts and seconds affiliated enterprise mark is deposited
When being in enterprise's blacklist, then determine the enterprise that it is identified for abnormal enterprise.That is, being based on from known exception enterprise
The association map and enterprise's blacklist of various dimensions incidence relation, can quickly and accurately excavate abnormal enterprise, improve excavation
Efficiency.
In one embodiment, this method further include: association starting point is identified as with level-one associate people, from association map
In, there are the second level associate people of incidence relation marks with level-one associate people mark for lookup；Second level associate people is identified and is made
To be associated with starting point, from association map, there are the three-level affiliated enterprise of incidence relation marks with second level associate people mark for lookup；
When determining that enterprise's blacklist is identified there are three-level affiliated enterprise, then the to be checked of three-level affiliated enterprise mark institute's unique identification is determined
Surveying enterprise is abnormal enterprise.
It is appreciated that further including the incidence relation between giver identification and giver identification in the present embodiment, in association map.
In one embodiment, the incidence relation between giver identification and giver identification may include that relatives' incidence relation and transaction are closed
At least one of connection relationship.
Specifically, server can be identified as association starting point with level-one associate people, from association map, lookup and level-one
There are the giver identifications of direct correlation relationship for associate people mark, obtain second level associate people mark.
It is appreciated that with level-one associate people mark, there are the giver identifications of direct correlation relationship, i.e., are associated with by level-one
Indirect association relationship is established between giver identification and abnormal enterprise's mark, there are second levels to be associated with to identify with abnormal enterprise
Therefore system is properly termed as second level associate people mark.
Further, server can by second level associate people identify as association starting point, from association map in, search with
There are the enterprise of direct correlation relationship marks for second level associate people mark, obtain three-level affiliated enterprise mark.It is appreciated that with two
Grade associate people mark is identified and second level affiliated person there are the enterprise of direct correlation relationship mark by level-one associate people
Indirect association relationship is established between the transition of member's mark, with abnormal enterprise mark, there are three-level passes to identify with abnormal enterprise
Therefore connection relationship is properly termed as three-level affiliated enterprise mark.
Whether it includes that the three-level affiliated enterprise identifies that server can be searched in enterprise's blacklist, when determining enterprise's blacklist
There are when three-level affiliated enterprise mark, then determine that the enterprise to be detected of three-level affiliated enterprise mark institute's unique identification is abnormal enterprise
Industry.
It should be noted that each level-one affiliated enterprise as described in the examples of the application identifies, second level affiliated enterprise identifies,
Three-level affiliated enterprise mark, level-one associate people mark and second level associate people mark etc. can be at least one respectively, and
It is not limited to one.
In above-described embodiment, based on the incidence relation between personnel and personnel and personnel and enterprise, from association map
It further excavates with abnormal enterprise's mark there are the three-level affiliated enterprise of three-level incidence relation mark, and the combination black name of enterprise
It is single, three-level affiliated enterprise is identified and carries out abnormal judgement, can more quickly and accurately excavate potential abnormal enterprise.
In one embodiment, this method further include: when level-one affiliated enterprise mark is not present in enterprise's blacklist, then
Obtain the first corresponding anomaly analysis basic data of level-one affiliated enterprise mark；The input of first anomaly analysis basic data is pre-
First in trained anomaly analysis model, exception point of the output for the enterprise to be detected of level-one affiliated enterprise mark institute's unique identification
Analyse result；When second level affiliated enterprise mark is not present in enterprise's blacklist, then obtain corresponding to second level affiliated enterprise mark
Second anomaly analysis basic data；Second anomaly analysis basic data is inputted in anomaly analysis model, output is closed for second level
Join the anomaly analysis result of the enterprise to be detected of enterprise's mark institute's unique identification.
Wherein, anomaly analysis basic data is the basic data for carrying out anomaly analysis processing.Anomaly analysis model,
It is the machine learning model for carrying out anomaly analysis processing.
In one embodiment, the first anomaly analysis basic data may include that level-one affiliated enterprise mark is corresponding
In basic information (for example, registration information) and operation information (business scope, manage annual report report the information such as situation) of enterprise etc.
At least one.Second anomaly analysis basic data may include the basis letter of the corresponding enterprise of second level affiliated enterprise mark
At least one of breath (for example, registration information) and operation information (business scope, manage annual report report the information such as situation) etc..
In one embodiment, the first anomaly analysis basic information can also include identifying to have with level-one affiliated enterprise to close
The event information and/or information of connection relationship.Second anomaly analysis basic information can also include marking with second level affiliated enterprise
Know the event information and/or information with incidence relation.
It is appreciated that server can be made iteratively machine learning training previously according to sample data, abnormal point is obtained
Analyse model.
Specifically, when there is level-one affiliated enterprise mark to be not present in enterprise's blacklist, server can be closed with the level-one
Connection enterprise is identified as key, searches the first anomaly analysis basic data corresponding with the key, and the first anomaly analysis basic data is defeated
Enter in anomaly analysis model trained in advance, output is directed to the different of the enterprise to be detected of level-one affiliated enterprise mark institute's unique identification
Often analysis result.When there is second level affiliated enterprise mark to be not present in enterprise's blacklist, server can be associated with the second level and be looked forward to
Industry is identified as key, searches the second anomaly analysis basic data corresponding with the key, the second anomaly analysis basic data is inputted pre-
First in trained anomaly analysis model, exception point of the output for the enterprise to be detected of second level affiliated enterprise mark institute's unique identification
Analyse result.
In one embodiment, anomaly analysis as a result, be characterization enterprise whether Yi Chang result.In one embodiment,
Anomaly analysis result may include the Exception Type of enterprise.
In one embodiment, Exception Type may include that address is abnormal, the age is abnormal, abnormal register, executed person are black
List is not managed, frequently at least one of change and the types such as illegal fund collection for a long time.In one embodiment, frequently change,
It is frequently changed including equity, address is frequently changed and at least one of types such as legal person frequently changes.
In above-described embodiment, marked when by enterprise's blacklist identification Bu Chu level-one affiliated enterprise mark or second level affiliated enterprise
Know whether it is abnormal when, then available anomaly analysis basic data and anomaly analysis model is combined, to enterprise's mark or second level
The enterprise to be detected that affiliated enterprise identifies institute's unique identification carries out anomaly analysis, and model analysis and enterprise's blacklist are combined
Come, excavate abnormal enterprise, further increases the accuracy that abnormal enterprise excavates.
In one embodiment, obtaining the first corresponding anomaly analysis basic data of level-one affiliated enterprise mark includes:
From association map, searches and there is level-one affiliated enterprise mark the first event information of incidence relation and/or the first information to believe
Breath, obtain include the first event information and/or the first information the first anomaly analysis basic data.
In the present embodiment, the incidence relation that can also be identified including enterprise with event information is associated in map, and/or, enterprise
The incidence relation of industry mark and information.First anomaly analysis basic data may include identifying to have with level-one affiliated enterprise
Relevant first event information and/or the first information.The incidence relation of enterprise mark and event information, can wrap
Include at least one of lawsuit, debt promise breaking, break and the types such as circulate a notice of commendation.
Specifically, when there is level-one affiliated enterprise mark to be not present in enterprise's blacklist, server can be from association map
Middle lookup and first event information of the level-one affiliated enterprise mark with incidence relation and // or the first information, are wrapped
First event information and the first information anomaly analysis basic data are included, and anomaly analysis basic data is inputted into exception
In analysis model, anomaly analysis processing is carried out with the enterprise to be detected to level-one affiliated enterprise mark institute's unique identification.
In one embodiment, obtaining the second corresponding anomaly analysis basic data of second level affiliated enterprise mark includes:
From association map, searches and there is second level affiliated enterprise mark the second event information of incidence relation and/or the second information to believe
Breath, obtain include second event information and/or the second information the second anomaly analysis basic data.
It is appreciated that information includes Domestic News.
In above-described embodiment, the event information and/or information with incidence relation will be identified with enterprise, as exception
Analysis foundation data.Event information and information often more can accurately reflect the management state of enterprise, therefore, by event
Information and/or information carry out anomaly analysis processing as anomaly analysis basic data, improve the standard of anomaly analysis result
True property.
As shown in figure 3, in one embodiment, this method further includes risk conduct the relation figure generation step, specifically include
Following steps:
S302 obtains negative operation event associated with abnormal enterprise's mark according to association map, and establishes negative warp
First degree of risk conduct the relation between battalion's event and abnormal enterprise's mark.
Wherein, event is negatively managed, is the event that there is negative effect to enterprise operation.Risk conduct the relation, for retouching
State the trend and trend of risk conduction.
Specifically, server can be closed according to the association between the enterprise's mark for including in association map and event information
Event information associated with abnormal enterprise's mark is searched by system, and negative operation thing is filtered out from the event information found
Part.Server can establish first degree of risk conduct the relation between negative operation event and abnormal enterprise's mark.It is appreciated that
First degree of risk conduct the relation is passed by negatively managing event to the corresponding known exception enterprise of abnormal enterprise's mark for indicating
Risk is led.
In one embodiment, it is associated in map and each event information is marked, server can be according to lookup
Label entrained by each event information arrived searches the event for carrying and negatively marking, as negative from each event information
Operation event.
In another embodiment, server can also carry out sentiment analysis to each event information, determine to correspond to
The event information of unfavorable ratings manages event as negative.
S304 regard level-one associate people mark as conducting spots, establishes abnormal enterprise's mark and identifies with second level affiliated enterprise
Between second degree of risk conduct the relation.
Wherein, conducting spots are the transition nodes that connection conduct the relation is established between the object by both ends.
Specifically, level-one associate people can be identified and be used as conducting spots by server, established and passed through level-one associate people mark
The conduction of knowledge, the risk that the known exception enterprise for keeping abnormal enterprise's mark corresponding has cause mark institute, second level affiliated enterprise right
Enterprise is answered to have risky conduct the relation, second degree of risk between as abnormal enterprise's mark and second level affiliated enterprise mark passes
Lead relationship.
S306 searches three-level associate people mark associated with second level affiliated enterprise mark from association map.
Wherein, three-level associate people identifies, and is and giver identification of the abnormal enterprise mark with three-level incidence relation.It can be with
Understand, three-level associate people mark passes sequentially through level-one associate people mark and second level affiliated enterprise mark, thus with abnormal enterprise
Industry mark establishes indirect association relationship, i.e., has three-level incidence relation between abnormal enterprise mark.
Specifically, server can be identified as association starting point with second level affiliated enterprise, from association map, lookup and second level
Affiliated enterprise's mark has the giver identification of incidence relation, identifies as three-level associate people.
S308 is obtained and is identified the associated level Four affiliated enterprise mark in association map with three-level associate people.
Wherein, level Four affiliated enterprise identifies, and is to identify with abnormal enterprise mark with the enterprise of level Four incidence relation.It can be with
Understand, level Four affiliated enterprise mark, passes sequentially through level-one associate people mark, second level affiliated enterprise mark and three-level affiliated person
Member's mark establishes indirect association relationship to identify with abnormal enterprise, i.e., between abnormal enterprise mark there is level Four to be associated with
System.
Specifically, server can search the enterprise for having incidence relation with three-level associate people mark from association map
Industry mark, identifies as level Four affiliated enterprise.
S310 regard three-level associate people mark as conducting spots, establishes second level affiliated enterprise mark and level Four affiliated enterprise
Third degree risk conduct the relation between mark.
Specifically, three-level associate people can be identified and be used as conducting spots by server, established and passed through three-level associate people mark
The conduction of knowledge, the enterprise that the risk with the corresponding enterprise of second level affiliated enterprise mark causes level Four affiliated enterprise mark corresponding
Industry has risky conduct the relation, and the as third degree risk between second level affiliated enterprise mark and level Four affiliated enterprise mark passes
Lead relationship.
S312 constructs risk conduct the relation figure according to first degree, second degree and third degree risk conduct the relation.
Specifically, server can be by first degree of risk conduct the relation, second degree of risk conduct the relation and third degree wind
Dangerous conduct the relation is patterned expression processing, and building obtains risk conduct the relation figure.
In one embodiment, risk conduct the relation figure can be exported to terminal and be shown by server, supervisor
It can be based on risk conduct the relation figure, sampling observation investigation is targetedly carried out to these potential abnormal enterprises.
In order to make it easy to understand, risk conduct the relation figure is illustrated now in conjunction with Fig. 4.Referring to Fig. 4, enterprise A is different
The corresponding known exception enterprise of Chang Qiye mark.7 negative operation events occur for enterprise A, for example, senior executive is abnormal, debt is disobeyed
About equal negative operation event, then negative operation event can cause certain risk, therefore negative operation event and enterprise to enterprise A
First degree of risk conduct the relation is produced between A.There are incidence relations (counterparty, investment, shareholder and to be carried on a shoulder pole with enterprise A
The incidence relations such as guarantor) enterprise be respectively enterprise B to enterprise D.It is appreciated that enterprise A is caused due to 7 negative operation events
Risk, may further to enterprise B to enterprise D, this several company generates certain risk, therefore, can establish enterprise
A and enterprise B are to second degree of risk conduct the relation between this Ji Jia enterprise of enterprise D.Enterprise C is since this is several with enterprise E to enterprise G
There are incidence relation (incidence relations such as shareholder and guarantee) between company.The risk that enterprise C is conducted to, may
It can conduct by incidence relations such as shareholder and guarantees as conducting spots to enterprise E to enterprise G, accordingly, it is possible to establish
Enterprise C and enterprise E is to the third degree risk conduct the relation between enterprise G.Based on this three degree of risk conduct the relation, so that it may establish
Above-mentioned risk conduct the relation figure, intuitively to embody the potential abnormal enterprise that negative operation event may cause.
It is appreciated that risk conduct the relation figure is to have carried out a series of risk conduction point on the basis of being associated with map
Analysis, the new figure that can characterize risk conducting path of one obtained.
In above-described embodiment, based on event information and enterprise's mark in association map, enterprise's mark and enterprise's mark, people
Member's mark and the multidimensional incidence relation between giver identification, enterprise and giver identification, construct risk conduct the relation figure, can be accurate
Ground intuitively embodies the potential abnormal enterprise that negative operation event may cause.
It should be understood that although each step in the flow chart of Fig. 2 and Fig. 3 is successively shown according to the instruction of arrow,
But these steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly state otherwise herein, these
There is no stringent sequences to limit for the execution of step, these steps can execute in other order.Moreover, in Fig. 2 and Fig. 3
At least part step may include that perhaps these sub-steps of multiple stages or stage are not necessarily same to multiple sub-steps
One moment executed completion, but can execute at different times, and the execution in these sub-steps or stage sequence is also not necessarily
Be successively carry out, but can at least part of the sub-step or stage of other steps or other steps in turn or
Alternately execute.
In one embodiment, as shown in figure 5, providing a kind of abnormal enterprise excavating gear 500, comprising: obtain module
502, associative search module 504 and abnormal enterprise determination module 506；Wherein:
Module 502 is obtained, the abnormal enterprise for obtaining known exception enterprise identifies.
Associative search module 504 is associated with for from the association map pre-established, searching to exist with abnormal enterprise's mark
The level-one affiliated enterprise mark and level-one associate people mark of relationship；It is identified as association starting point with level-one associate people, from association
There are the second level affiliated enterprise of incidence relation marks with level-one associate people mark for lookup in map.
Abnormal enterprise's determination module 506, for respectively identifying level-one affiliated enterprise mark and second level affiliated enterprise and in advance
If enterprise's blacklist in include enterprise mark be compared；The level-one affiliated enterprise being included in enterprise's blacklist is identified
The enterprise for identifying unique identification respectively with second level affiliated enterprise is determined as abnormal enterprise.
In one embodiment, associative search module 504 is also used to be identified as association starting point with level-one associate people, from pass
Join in map, there are the second level associate people of incidence relation marks with level-one associate people mark for lookup；By second level associate people
Mark is as association starting point, and from association map, there are the three-levels of incidence relation to be associated with enterprise with second level associate people mark for lookup
Industry mark；Abnormal enterprise's determination module 506 is also used to then determine when three-level affiliated enterprise identifies and is included in enterprise's blacklist
The enterprise to be detected that three-level affiliated enterprise identifies institute's unique identification is abnormal enterprise.
In one embodiment, abnormal enterprise's determination module 506 is also used to when there is no level-ones to be associated in enterprise's blacklist
When enterprise's mark or second level affiliated enterprise identify, then obtain corresponding to level-one affiliated enterprise mark or second level affiliated enterprise mark
Anomaly analysis basic data；By in anomaly analysis basic data input anomaly analysis model trained in advance, output is directed to level-one
The anomaly analysis result of the enterprise to be detected of affiliated enterprise's mark or second level affiliated enterprise mark institute's unique identification.
In one embodiment, obtain module 502 be also used to from association map in, search with level-one affiliated enterprise mark or
Second level affiliated enterprise mark has the event information of incidence relation；Using event information as anomaly analysis basic data；And/or
From association map, the information that there is incidence relation with level-one affiliated enterprise mark or second level affiliated enterprise mark is searched,
Using information as anomaly analysis basic data.
As shown in fig. 6, in one embodiment, the device 500 further include:
Risk conduction building module 508, for obtaining negative warp associated with abnormal enterprise's mark according to association map
Battalion's event, and establish the negative first degree of risk conduct the relation managed between event and abnormal enterprise's mark；By level-one affiliated person
Member's mark is used as conducting spots, establishes second degree of risk conduct the relation between abnormal enterprise's mark and second level affiliated enterprise mark；
Three-level associate people mark associated with second level affiliated enterprise mark is searched from association map；It obtains and three-level associate people
Mark associated level Four affiliated enterprise mark in association map；It regard three-level associate people mark as conducting spots, establishes two
Third degree risk conduct the relation between grade affiliated enterprise mark and level Four affiliated enterprise mark；According to first degree, second degree and
Third degree risk conduct the relation constructs risk conduct the relation figure.
In one embodiment, it includes that company information and enterprise key personnel believe that associative search module 504, which is also used to obtain,
The association analysis basic data of breath；Analysis processing is associated to association analysis basic data；According to association analysis as a result, from enterprise
Enterprise's mark is extracted in industry information, and extracts giver identification from enterprise key personal information, and establishes enterprise's mark and enterprise
Incidence relation between mark, enterprise's mark and giver identification；According to the incidence relation of foundation, building association map.
Specific about abnormal enterprise's excavating gear limits the limit that may refer to above for abnormal enterprise's method for digging
Fixed, details are not described herein.Modules in above-mentioned exception enterprise excavating gear can fully or partially through software, hardware and its
Combination is to realize.Above-mentioned each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also be with
It is stored in the memory in computer equipment in a software form, in order to which processor calls the above modules of execution corresponding
Operation.
In one embodiment, a kind of computer equipment is provided, which can be the server in Fig. 1
110, internal structure chart can be as shown in Figure 7.The computer equipment includes processor, the memory connected by system bus
And network interface.Wherein, memory includes non-volatile memory medium and built-in storage.The non-volatile of the computer equipment is deposited
Storage media can storage program area and computer program.The computer program is performed, and it is a kind of different to may make that processor executes
Chang Qiye method for digging.The processor of the computer equipment supports entire computer equipment for providing calculating and control ability
Operation.Computer program can be stored in the built-in storage, when which is executed by processor, may make processor
Execute a kind of abnormal enterprise method for digging.The network interface of computer equipment is for carrying out network communication.
It will be understood by those skilled in the art that structure shown in Fig. 7, only part relevant to application scheme is tied
The block diagram of structure does not constitute the restriction for the computer equipment being applied thereon to application scheme, specific computer equipment
It may include perhaps combining certain components or with different component layouts than more or fewer components as shown in the figure.
In one embodiment, a kind of computer equipment, including memory and processor are provided, memory is stored with meter
Calculation machine program, when computer program is executed by processor, so that the step of processor executes above-mentioned abnormal enterprise's method for digging.This
The step of locating abnormal enterprise's method for digging can be the step in abnormal enterprise's method for digging of above-mentioned each embodiment.
In one embodiment, a kind of computer readable storage medium is provided, computer program, computer journey are stored with
When sequence is executed by processor, so that the step of processor executes above-mentioned abnormal enterprise's method for digging.Excavation side, abnormal enterprise herein
The step of method, can be the step in abnormal enterprise's method for digging of above-mentioned each embodiment.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
Each technical characteristic of above embodiments can be combined arbitrarily, for simplicity of description, not to above-described embodiment
In each technical characteristic it is all possible combination be all described, as long as however, the combination of these technical characteristics be not present lance
Shield all should be considered as described in this specification.
The several embodiments of the application above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the concept of this application, various modifications and improvements can be made, these belong to the protection of the application
Range.Therefore, the scope of protection shall be subject to the appended claims for the application patent.
Claims (10)
1. a kind of exception enterprise method for digging, which comprises
Obtain the abnormal enterprise mark of known exception enterprise；
From the association map pre-established, there are the level-one affiliated enterprise of incidence relation marks with abnormal enterprise's mark for lookup
Know and level-one associate people identifies；
It is identified as association starting point with the level-one associate people, is searched and the level-one associate people mark from the association map
There are the second level affiliated enterprise of incidence relation marks for knowledge；
Respectively by level-one affiliated enterprise mark and second level affiliated enterprise mark and preset enterprise's blacklist in enterprise identify into
Row compares；
By the level-one affiliated enterprise being included in enterprise's blacklist mark and second level affiliated enterprise mark respectively unique identification to
Detection enterprise is determined as abnormal enterprise.
2. the method according to claim 1, wherein the method also includes:
It is identified as association starting point with the level-one associate people, from the association map, is searched and the level-one associate people
There are the second level associate people of incidence relation marks for mark；
The second level associate people is identified as association starting point, from the association map, is searched and the second level affiliated person
There are the three-level affiliated enterprise of incidence relation marks for member's mark；
When determining that enterprise's blacklist is identified there are the three-level affiliated enterprise, then the three-level affiliated enterprise mark is determined
The enterprise to be detected of institute's unique identification is abnormal enterprise.
3. the method according to claim 1, wherein the method also includes:
When level-one affiliated enterprise mark is not present in enterprise's blacklist, then obtain first corresponding to level-one affiliated enterprise mark
Anomaly analysis basic data；By in the first anomaly analysis basic data input anomaly analysis model trained in advance, export
For the anomaly analysis result of the enterprise to be detected of level-one affiliated enterprise mark institute's unique identification；
When second level affiliated enterprise mark is not present in enterprise's blacklist, then obtain second corresponding to second level affiliated enterprise mark
Anomaly analysis basic data；The second anomaly analysis basic data is inputted in the anomaly analysis model, output is directed to institute
State the anomaly analysis result of the enterprise to be detected of second level affiliated enterprise mark institute's unique identification.
4. according to the method described in claim 3, it is characterized in that, described obtain first corresponding to level-one affiliated enterprise mark
Anomaly analysis basic data includes: from association map, and searching has the of incidence relation with level-one affiliated enterprise mark
One event information and/or the first information obtain including the first different of the first event information and/or the first information
Normal analysis foundation data.
5. according to the method described in claim 3, it is characterized in that, described obtain second corresponding to second level affiliated enterprise mark
Anomaly analysis basic data includes:
From association map, search and second event information and/or second money of the second level affiliated enterprise mark with incidence relation
Interrogate information, obtain include the second event information and/or the second information the second anomaly analysis basic data.
6. the method according to claim 1, wherein the method also includes:
Negative operation event associated with abnormal enterprise's mark is obtained according to the association map, and establishes the negative operation
First degree of risk conduct the relation between event and abnormal enterprise's mark；
It regard level-one associate people mark as conducting spots, establishes between abnormal enterprise's mark and second level affiliated enterprise mark
Second degree of risk conduct the relation；
Three-level associate people mark associated with the second level affiliated enterprise mark is searched from association map；
It obtains and identifies the associated level Four affiliated enterprise mark in association map with the three-level associate people；
It regard three-level associate people mark as conducting spots, establishes the second level affiliated enterprise mark and marked with level Four affiliated enterprise
Third degree risk conduct the relation between knowledge；
According to first degree, second degree and third degree risk conduct the relation, risk conduct the relation figure is constructed.
7. method according to any one of claim 1 to 6, which is characterized in that from the association map pre-established,
Before lookup is identified with abnormal enterprise's mark there are the level-one affiliated enterprise of incidence relation mark and level-one associate people, institute
State method further include:
Obtain the association analysis basic data including company information and enterprise key personal information；
Analysis processing is associated to the association analysis basic data；
According to association analysis as a result, extracting enterprise's mark from company information, and personnel are extracted from enterprise key personal information
Mark, and establish the incidence relation between enterprise's mark and enterprise's mark, enterprise's mark and giver identification；
According to the incidence relation of foundation, building association map.
8. a kind of exception enterprise excavating gear, which is characterized in that described device includes:
Module is obtained, the abnormal enterprise for obtaining known exception enterprise identifies；
Associative search module is associated with for from the association map pre-established, searching to exist with abnormal enterprise's mark
The level-one affiliated enterprise mark and level-one associate people mark of system；It is identified as association starting point with the level-one associate people, from institute
Stating lookup and level-one associate people mark in association map, there are the second level affiliated enterprise of incidence relation marks；
Abnormal enterprise's determination module, for respectively by level-one affiliated enterprise mark and second level affiliated enterprise mark and preset enterprise
The enterprise's mark for including in blacklist is compared；The level-one affiliated enterprise being included in enterprise's blacklist mark and second level are closed
The enterprise that connection enterprise identifies unique identification respectively is determined as abnormal enterprise.
9. a kind of computer equipment, including memory and processor, the memory are stored with computer program, feature exists
In the step of processor realizes any one of claims 1 to 7 the method when executing the computer program.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
The step of method described in any one of claims 1 to 7 is realized when being executed by processor.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110245165A (en) * | 2019-05-20 | 2019-09-17 | 平安科技（深圳）有限公司 | Risk conduction association map optimization method, device and computer equipment |
| CN110442654A (en) * | 2019-07-08 | 2019-11-12 | 深圳壹账通智能科技有限公司 | Promise breaking information query method, device, computer equipment and storage medium |
| CN110442607A (en) * | 2019-07-26 | 2019-11-12 | 中国建设银行股份有限公司 | The local search method, apparatus and electronic equipment of affiliated enterprise's information |
| CN111062732A (en) * | 2019-12-24 | 2020-04-24 | 中科金审(北京)科技有限公司 | Method, device, equipment and storage medium for inquiring fake bearing production address |
| CN111583037A (en) * | 2020-04-30 | 2020-08-25 | 支付宝(杭州)信息技术有限公司 | Method and device for determining risk associated object and server |
| CN112541698A (en) * | 2020-12-22 | 2021-03-23 | 北京中数智汇科技股份有限公司 | Method and system for identifying enterprise risks based on external characteristics of enterprise |
| CN112988762A (en) * | 2021-05-07 | 2021-06-18 | 江苏中辰软件科技有限公司 | Real-time identification and early warning method suitable for unit of losing message |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110245165A (en) * | 2019-05-20 | 2019-09-17 | 平安科技（深圳）有限公司 | Risk conduction association map optimization method, device and computer equipment |
| CN110245165B (en) * | 2019-05-20 | 2023-04-11 | 平安科技（深圳）有限公司 | Risk conduction associated graph optimization method and device and computer equipment |
| CN110442654A (en) * | 2019-07-08 | 2019-11-12 | 深圳壹账通智能科技有限公司 | Promise breaking information query method, device, computer equipment and storage medium |
| CN110442607A (en) * | 2019-07-26 | 2019-11-12 | 中国建设银行股份有限公司 | The local search method, apparatus and electronic equipment of affiliated enterprise's information |
| CN111062732A (en) * | 2019-12-24 | 2020-04-24 | 中科金审(北京)科技有限公司 | Method, device, equipment and storage medium for inquiring fake bearing production address |
| CN111583037A (en) * | 2020-04-30 | 2020-08-25 | 支付宝(杭州)信息技术有限公司 | Method and device for determining risk associated object and server |
| CN112541698A (en) * | 2020-12-22 | 2021-03-23 | 北京中数智汇科技股份有限公司 | Method and system for identifying enterprise risks based on external characteristics of enterprise |
| CN112988762A (en) * | 2021-05-07 | 2021-06-18 | 江苏中辰软件科技有限公司 | Real-time identification and early warning method suitable for unit of losing message |
| CN112988762B (en) * | 2021-05-07 | 2021-09-14 | 江苏中辰软件科技有限公司 | Real-time identification and early warning method suitable for unit of losing message |
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