CN110427406A - The method for digging and device of organization's related personnel's relationship - Google Patents
The method for digging and device of organization's related personnel's relationship Download PDFInfo
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- CN110427406A CN110427406A CN201910728123.XA CN201910728123A CN110427406A CN 110427406 A CN110427406 A CN 110427406A CN 201910728123 A CN201910728123 A CN 201910728123A CN 110427406 A CN110427406 A CN 110427406A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The present invention relates to the method for digging and device of a kind of organization related personnel relationship.The described method includes: obtaining each dimension data information aggregate of organization's correlation natural person and the affiliated organization of natural person；It obtains and is closed according to the character subset of each dimension of the affiliated organization of personnel after natural person's name or other attribute informations cluster；Organization belonging to similar natural person is combined, carries out vector conversion according to each combined similarity feature；According to similarity vectors training with famous person's disaggregated model, and use model predictive classification result；According to classification results, merge same natural person, polymerization is associated with natural person, the affiliated organization of natural person and is associated with organization's data acquisition system, generates organization related personnel relational structure.The embodiment of the present invention can accurately and intuitively excavate the correlation of different tissues mechanism related personnel, to meet the demand for establishing connection between the organization related personnel of isolated dispersion.
Description
Technical field
The present invention relates to computer science, technical field of Internet information more particularly to a kind of organization related personnel
The method for digging and device of relationship.
Background technique
Organization is the organization's form registered in accordance with the law, usually expression government offices, enterprises and institutions, society
Group and other organizations, by its daily operation management activity of natural person personnel actual participation.The so-called tissue of this patent
Mechanism includes its hetero-organization such as organ, enterprise and establishment, public organization, education and scientific research mechanism, employer's organization, charity
Form.The operation management activity of natural person participation organization direct or indirect usually in a manner of investment, equity participation, tenure etc..
Have cooperation, affiliation natural person and its organization held a post between often there is the linkage of risk, organization
Situations such as condition of assets of related personnel, fame and prestige reputation, qualification background all can involve in various degree collaboration other from
Right people and organization.
Organization related personnel relationship has certain concealment in reality, due to a large amount of different natural persons use it is identical
Name, can not determine the different identity of natural person of the same name in organization, especially same natural person hold a post in multi-layer, across
The different tissues mechanism in area, it is difficult to be screened one by one from large amount of data information；The mode for separately thering is natural person to take anonymous agency
To be associated with the name registration organization of natural person, living for share-holding part, application intellectual property, the operation such as finance and invest
It is dynamic, to mask connecting each other for different tissues mechanism related personnel.
Summary of the invention
To solve the above-mentioned problems and meet the demand for interconnection of organization related personnel, the present invention provides a kind of tissues
The method for digging and device of mechanism related personnel's relationship, this method and device can be with the phases in automatic distinguishing organization with famous person
With/different identity, and the organization personnel for showing same identity accordingly participate in different tissues mechanism run movable behavior and
Incidence relation between the organization personnel of different identity, without inquiring more agency informations repeatedly to know its personnel's group
At situation, the error manually inferred is also avoided, efficiency and accuracy are greatly improved.
In a first aspect, the embodiment of the invention provides a kind of method for digging of organization related personnel relationship.
Obtain each dimension data information aggregate of organization's correlation natural person and the affiliated organization of natural person；
Organization's data acquisition system is clustered according to natural person's name or other attribute informations；
Organization belonging to similar middle natural person is combined；
Each dimension data character subset of the similar affiliated organization of middle natural person is extracted to close；
The similitude for comparing organization's different dimensions data characteristics in each combination is converted into the expression of its vector；
It is marked according to sample, trains organization's correlation with the disaggregated model of famous person using the algorithm of machine learning；
According to the vector forecasting classification results of the model after training and input；
According to classification results, the same famous person in organization is sorted out respectively are as follows: different natural persons of the same name are also or together
One natural person；
Assign the identical id of same natural person；
Merge different tissues mechanism nature personal data according to id；
Organization's relevant people is established according to the incidence relation of the natural person or organization that extract in each dimensional information
Member's relationship.
Second aspect, the embodiment of the invention provides a kind of excavating gear of organization related personnel relationship, the devices
Include:
Characteristic extracting module, for extract according to natural person's name or other attribute informations cluster after related natural person and
The characteristic of its affiliated each dimension of organization；
Vector conversion module organizes loom according in each combination for combining organization belonging to similar middle natural person
The degree of similarity of each dimensional characteristics of structure is translated into feature vector；
Model training module constructs disaggregated model for using vector to carry out the classification based training of machine learning；
Prediction module of classifying predicts output category result according to the disaggregated model of building for input feature value；
Relationship constructs module, is section with natural person, organization etc. for generating organization's related personnel's relational structure
Point, relatives, teachers and students, colleague, cooperation, infringement, lawsuit, credits between natural person, natural person and organization or organization,
The relationships such as guarantee, ownership, investment, equity participation, tenure connect each node as side.When building relationship, according to aforesaid class result
It assigns natural person's node respectively with identical or different id, merges the node of identical id.
The third aspect, the embodiment of the invention provides a kind of electronic equipments of organization related personnel relation excavation, should
Equipment includes processor, memory, any one of input/output (I/O) equipment etc. or multinomial.The memory is stored with can
The program instruction that can be executed by the processor, the processor call described program to instruct the side for being able to carry out above-mentioned various aspects
Method.
Fourth aspect is stored with computer program in the storage medium the embodiment of the invention provides a kind of storage medium,
The processor executes the method that the computer program executes above-mentioned various aspects.
Detailed description of the invention
Drawings in the following description are some embodiments of the invention, to those skilled in the art, not
Under the premise of making the creative labor, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is the flow diagram of organization related personnel relation excavation method in one embodiment of the invention；
Fig. 2 is the structural schematic diagram of organization's related personnel's relationship building in one embodiment of the invention；
Fig. 3 is the structural schematic diagram of organization related personnel relation excavation device in one embodiment of the invention；
Fig. 4 is the structural schematic diagram of electronic equipment in one embodiment of the invention.
Specific embodiment
In order to which the objects, technical solutions and advantages of the application are more clearly understood, below in conjunction in the embodiment of the present invention
Attached drawing, technical solution in the embodiment of the present invention is further elaborated.Specific embodiment described herein is this
A part of the embodiment of invention, and not all embodiments are only used for explaining and non-limiting the application.Based on the implementation in the present invention
Example, every other embodiment obtained by those of ordinary skill in the art without making creative efforts belong to
The scope of protection of the invention.
Fig. 1 is the flow diagram of organization related personnel relation excavation method in one embodiment of the invention, such as Fig. 1
It is shown, which comprises
Step 101, each dimension data information collection of organization's correlation natural person and the affiliated organization of natural person is obtained
It closes；
Specifically, natural person's information of acquisition includes but is not limited to the legal person, shareholder, senior executive, other tenures of organization
Natural person in member etc. and there are relatives, colleague, teachers and students, cooperation, infringement, lawsuit, credits, guarantee, power with aforementioned natural person
Natural person's set of the incidence relations such as category；The agency information of acquisition includes but is not limited to that organization's registration is relevant
Essential information, shareholder's information, investments abroad, change record, annual report etc., the relevant financing information of business activities, investment thing
Part, equity pledge, bond information, chattel mortgage, institution business, product information, recruitment information, land purchase information, bidding, news
Public sentiment, social account etc. receive the relevant administrative award of executive supervision, administrative supply, administrative permission, administrative penalty, seriously disobey
Method manages exception, the people that breaks one's promise, tax arrear bulletin, inlet and outlet credit etc., participate in the relevant judgement document of judicial activity, law court announces,
Court's bulletin, the judicial assistance, judicial auction etc., the relevant trademark information of intellectual property, patent information, software copyright, works
The data information set of each dimensions such as copyright, intellectual property pledge, website record information.
Step 102, organization's data are clustered according to natural person's name, is obtained after clustering belonging to each natural person
The character subset of each dimension data of organization closes.
Specifically, organization's natural person's data acquisition system that traversal step 101 obtains obtains same name natural person respectively
The feature field of affiliated each dimensional information of organization.For example, the natural person that name is " Zhang San " belongs to A, B, C tri- tissues
Mechanism, name are that the natural person of " Li Si " belongs to B, and tri- organizations of C, D obtain A, B, C respectively, organization, D family
Contact method, business scope, registration and operation address in essential information, with aforementioned tissues mechanism have investment, equity participation, ownership,
Other organization's titles of the incidence relations such as lawsuit, credits, guarantee, in change record before changing after aforementioned tissues mechanism it is natural
The list of names of people, the tagged words such as the related natural person's list of names extracted in news public sentiment and linked groups' organization names list
Section.Pretreatment is formatted to above-mentioned all feature fields, removes repetition values, obtains each dimension of the affiliated organization of natural person
Character subset closes.
Step 103, organization belonging to similar natural person is combined, according to each combined similarity feature into
Row vector conversion.
Specifically, combination is pairwise grouping in the affiliated organization of similar natural person that traversal step 102 obtains, according to every
The degree of similarity of a combination Zhong Liangjia organization different dimensions data is converted into mathematic vector.For example, aforementioned " Zhang San " point
Organization under class forms { A, B } after being grouped two-by-two, { A, C }, { B, C } three combinations.Such as A, B organization contact method warp
Identical or entirely different after formatting processing, which is converted into vector 1 or 0；Such as the text of Liang Jia organization
The parts such as feature such as business scope are same or similar, after being segmented to content of text using TF-IDF, Word2Vec or
Text object is converted feature vector by other Text character extraction algorithms of person, then uses cosine similarity, and Jaccard is similar
Degree or other similarity algorithms calculate the similarity between two vectors, similar with the text of Liang Jia organization business scope
Angle value is indicated as the vector of the dimension；Address statement mode such as Liang Jia organization is different, and geographical location is same or similar,
The geographical coordinate of available Liang Jia organization, the vector for calculating the distance between two coordinate points as the dimension indicate.
Similarly, the feature field for comparing all combination each dimensions of mechanism, undertissue, is separately converted to represent the dimension similitude
Feature vector.
Step 104, according to similarity vectors training with famous person's disaggregated model, and model predictive classification result is used.
Specifically, the part similarity feature vector that extraction step 103 obtains, mark sample label: 0 expression is of the same name not
Same natural person；1 indicates same natural person.Using the sorting algorithm of machine learning, including but not limited to decision tree and its relevant episode
At learning algorithm, Bayesian network, support vector machines, deep learning related algorithm etc., carry out classification based training, according to accuracy rate,
Accurate rate, recall rate, F1 value, ROC curve, the comprehensive evaluation indexs such as AUC value carry out parameter optimization and cross validation to determine most
Good disaggregated model.The feature vector that traversal step 103 obtains exports the training result of prediction as the input value of model.It is as follows
Shown in table:
Step 105, according to classification results, merge same natural person and its association natural person, the affiliated organization of natural person
And its association organization's data acquisition system, generate organization related personnel relational structure.Fig. 2 is in one embodiment of the invention
The structural schematic diagram of organization's related personnel's relationship building.Specifically, using natural person, organization as node, natural person,
Relatives, colleague, teachers and students, cooperation, infringement, lawsuit, credits, guarantee, ownership between natural person and organization and organization,
The relationships such as investment, equity participation, tenure connect each node as side, generate organization related personnel relation table.According to step 104
The prediction training result of acquisition assigns different natural person's difference id of the same name respectively；The identical id of same natural person, merges identical id
Natural person's node.For example, with A belonging to famous person Zhang San, tri- organizations of B, C with B belonging to famous person Li Si, C, D tri-
The sorted assignment id of organization, family is as shown in the table:
Claims (10)
1. a kind of method for digging of organization related personnel relationship characterized by comprising
Obtain each dimension data information aggregate of organization's correlation natural person and the affiliated organization of natural person；
Organization's data acquisition system is clustered according to natural person's name or other attribute informations；
Organization belonging to similar middle natural person is combined；
Each dimension data character subset of the similar affiliated organization of middle natural person is extracted to close；
The similitude for comparing organization's different dimensions data characteristics in each combination is converted into the expression of its vector；
It is marked according to sample, trains organization's correlation with the disaggregated model of famous person using the algorithm of machine learning；
According to the vector forecasting classification results of the model after training and input；
According to classification results, the same famous person in organization is sorted out respectively are as follows: different natural persons of the same name also or it is same from
Right people；
Assign the identical id of same natural person；
Merge different tissues mechanism nature personal data according to id；
It polymerize the incidence relation of the natural person or organization that extract in each dimensional information, establishes organization related personnel pass
System.
2. the method according to claim 1, wherein each dimension data information aggregate of the organization include but
It is not limited to:
Natural person in the legal person of organization, shareholder, senior executive, other tenure members etc. and with aforementioned natural person there are relatives,
The natural person of the incidence relations such as colleague, teachers and students, cooperation, infringement, lawsuit, credits, guarantee, ownership gathers；
Relevant essential information, shareholder's information, investments abroad, branch, change record, year report are registered by organization
Accuse etc., the relevant financing information of business activities, investment event, equity pledge, bond information, chattel mortgage, institution business, product
Information, recruitment information, land purchase information, bidding, news public sentiment, social account, Historic Evolution etc., it is relevant to receive executive supervision
Administrative award administrative supply, administrative permission, administrative penalty, breaks the law on a serious scale, manages exception, the people that breaks one's promise, tax arrear bulletin, inlet and outlet
Credit etc. participates in the relevant judgement document of judicial activity, law court's bulletin, court's bulletin, the judicial assistance, judicial auction etc., knowledge
The relevant trademark information of property right, patent information, software copyright, Copyright, intellectual property pledge, website record information etc.
The data information set of each dimension.
3. the method according to claim 1, wherein natural person's name includes each dimension of the organization
Any one the natural person's name occurred in degree data information set.
4. the method according to claim 1, wherein described will be according in similar after name or other hierarchical cluster attributes
Organization belonging to natural person is combined, comprising:
Organization belonging to name or the identical natural person of other attribute informations is grouped combination；
The feature field for obtaining same name or each dimensional information of the affiliated organization of natural person of other attribute informations respectively, into
Formatting lines pretreatment, removes repetition values, obtains each dimensional characteristics subclass of the affiliated organization of natural person.
5. the method according to claim 1, wherein it is special to compare organization's different dimensions information in each combination
The degree of similarity of sign is converted into mathematic vector, comprising:
It is identical or different indicated with 1 or 0；
Text similarity computing uses TF-IDF, Word2Vec or other Text character extraction algorithms by the text pair after participle
As being converted into feature vector, then use cosine similarity, Jaccard similarity or other similarity algorithms calculate two to
Similarity value between amount is indicated as similarity vectors；
The distance between two address coordinate points of address similarity calculation are indicated as its vector.
6. the method according to claim 1, wherein the sorting algorithm includes but is not limited to decision tree and its phase
Close Ensemble Learning Algorithms, Bayesian network, support vector machines, neural network or other machines study related algorithm etc..
7. -5 any method according to claim 1, which is characterized in that establish organization's related personnel's relationship include but
It is not limited to the relationships such as relatives, teachers and students, colleague, cooperation, infringement, lawsuit, credits, guarantee, ownership, investment, equity participation, tenure.
8. a kind of excavating gear of organization related personnel relationship characterized by comprising
Characteristic extracting module, for extracting according to affiliated group of related natural person after natural person's name or other attribute informations cluster
The characteristic of each dimension of loom structure；
Vector conversion module, it is each according to organization in each combination for combining organization belonging to similar middle natural person
The degree of similarity of dimensional characteristics is translated into feature vector；
Model training module constructs disaggregated model for using vector to carry out the classification based training of machine learning；
Prediction module of classifying predicts output category result according to the disaggregated model of building for input feature value；
Relationship constructs module, for according to the natural person or tissue extracted in each dimension data information of classification results and organization
The incidence relation of mechanism generates organization related personnel relational structure.
9. a kind of electronic equipment, which is characterized in that contain processor, memory, any one of input/output (I/O) equipment
Or it is multinomial.The memory is stored with the program instruction that may be executed by the processor, and the processor calls described program
Instruction is able to carry out method described in the claims 1 to 6.
10. a kind of storage medium, which is characterized in that be stored with computer program in the storage medium, the processor executes institute
State the method that computer program executes above-mentioned various aspects.
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Cited By (11)
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| CN111061754A (en) * | 2019-12-10 | 2020-04-24 | 北京明略软件系统有限公司 | Family map determining method and device, electronic equipment and storage medium |
| CN111241160A (en) * | 2020-01-15 | 2020-06-05 | 北京明略软件系统有限公司 | Method and device for determining hidden relation of people |
| CN111539605A (en) * | 2020-04-14 | 2020-08-14 | 鼎富智能科技有限公司 | Enterprise portrait construction method and device |
| CN111861361A (en) * | 2020-04-09 | 2020-10-30 | 河北利至人力资源服务有限公司 | Intelligent resume pushing system and method |
| CN112182240A (en) * | 2020-09-23 | 2021-01-05 | 成都数联铭品科技有限公司 | Method and system for identifying and processing same-name natural person entity super node and electronic equipment |
| CN112487819A (en) * | 2020-12-18 | 2021-03-12 | 成都数联铭品科技有限公司 | Method, system, electronic device and storage medium for identifying homonyms among enterprises |
| CN112836041A (en) * | 2021-01-29 | 2021-05-25 | 北京海卓飞网络科技有限公司 | Personnel relationship analysis method, device, equipment and storage medium |
| CN113129155A (en) * | 2021-05-11 | 2021-07-16 | 北京海卓飞网络科技有限公司 | Multi-type personnel information processing method, equipment and storage medium |
| CN113312895A (en) * | 2021-05-20 | 2021-08-27 | 北京邮电大学 | Organization mapping method and device of autonomous system AS and electronic equipment |
| CN113609346A (en) * | 2021-10-08 | 2021-11-05 | 企查查科技有限公司 | Natural person name disambiguation method, device and medium based on enterprise incidence relation |
| CN117708725A (en) * | 2023-12-15 | 2024-03-15 | 中国电子科技集团公司第十五研究所 | Distributed personnel relationship mining and evaluating method and device |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111061754B (en) * | 2019-12-10 | 2023-03-14 | 北京明略软件系统有限公司 | Family map determining method and device, electronic equipment and storage medium |
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| CN111861361A (en) * | 2020-04-09 | 2020-10-30 | 河北利至人力资源服务有限公司 | Intelligent resume pushing system and method |
| CN111539605A (en) * | 2020-04-14 | 2020-08-14 | 鼎富智能科技有限公司 | Enterprise portrait construction method and device |
| CN111539605B (en) * | 2020-04-14 | 2023-12-29 | 鼎富智能科技有限公司 | Enterprise portrait construction method and device |
| CN112182240A (en) * | 2020-09-23 | 2021-01-05 | 成都数联铭品科技有限公司 | Method and system for identifying and processing same-name natural person entity super node and electronic equipment |
| CN112182240B (en) * | 2020-09-23 | 2024-04-02 | 成都数联铭品科技有限公司 | Super node identification processing method and system for entities of same-name natural persons and electronic equipment |
| CN112487819A (en) * | 2020-12-18 | 2021-03-12 | 成都数联铭品科技有限公司 | Method, system, electronic device and storage medium for identifying homonyms among enterprises |
| CN112836041A (en) * | 2021-01-29 | 2021-05-25 | 北京海卓飞网络科技有限公司 | Personnel relationship analysis method, device, equipment and storage medium |
| CN113129155B (en) * | 2021-05-11 | 2024-02-27 | 北京海卓飞网络科技有限公司 | Multi-type personnel information processing method, equipment and storage medium |
| CN113129155A (en) * | 2021-05-11 | 2021-07-16 | 北京海卓飞网络科技有限公司 | Multi-type personnel information processing method, equipment and storage medium |
| CN113312895A (en) * | 2021-05-20 | 2021-08-27 | 北京邮电大学 | Organization mapping method and device of autonomous system AS and electronic equipment |
| CN113609346A (en) * | 2021-10-08 | 2021-11-05 | 企查查科技有限公司 | Natural person name disambiguation method, device and medium based on enterprise incidence relation |
| CN117708725A (en) * | 2023-12-15 | 2024-03-15 | 中国电子科技集团公司第十五研究所 | Distributed personnel relationship mining and evaluating method and device |
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