CN108596439A - A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates - Google Patents
A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates Download PDFInfo
- Publication number
- CN108596439A CN108596439A CN201810271489.4A CN201810271489A CN108596439A CN 108596439 A CN108596439 A CN 108596439A CN 201810271489 A CN201810271489 A CN 201810271489A CN 108596439 A CN108596439 A CN 108596439A
- Authority
- CN
- China
- Prior art keywords
- enterprise
- knowledge
- company
- illustrative plates
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Abstract
The invention discloses a kind of business risk prediction technique of knowledge based collection of illustrative plates and system, this method step includes：1) it builds the entity of Company Knowledge collection of illustrative plates and establishes the relationship between entity and entity, knowledge extraction is carried out from each setting data source, forms Company Knowledge collection of illustrative plates；2) all kinds of news informations with enterprise and associated entity are captured, and the news information of crawl is handled based on Company Knowledge collection of illustrative plates, mark the relationship of related entities and event；By in markup information storage to the knowledge base of structuring, Company News information knowledge mapping is formed；3) it is based on Company Knowledge collection of illustrative plates and carries out business risk prediction with Company News information knowledge mapping.The present invention has filled up current knowledge mapping in the blank of business risk analysis field, and the Company Knowledge collection of illustrative plates and Company News information knowledge mapping of structure have compared with high practicability.
Description
Technical field
Application the present invention relates to knowledge mapping in business risk early warning analysis field, particular by knowledge mapping to enterprise
One kind itself and affiliated enterprise's risk is found and early warning point that portion's management data and real-time event are extracted and analyzed in the industry
The method of analysis.
Background technology
With the continuous development of artificial intelligence (Artificial Intelligence, AI) technology, base of the data as AI
Plinth is increasingly paid attention to by enterprise, data can be made to form considerable value by algorithm mining analysis, and the core of AI is to grind
Study carefully and how with the easy-to-handle mode of computer to indicate various knowledge, which results in since 2017 " knowledge " or
The attraction of person's " knowledge mapping " has greatly exceeded " data " in itself.
Knowledge mapping (Knowledge Graph) is also known as mapping knowledge domains, is explicit knowledge's development process and structure
A series of a variety of different figures of relationship are excavated, analyze, build, are painted with visualization technique Description of Knowledge resource and its carrier
System and explicit knowledge and connecting each other between them.
The Conceptual evolution of knowledge mapping have passed through the stages such as semantic network, ontology, Web, semantic net, link data, and
It was proposed in 2012 by Google, Google wishes to build follow-on search engine by knowledge mapping, to which optimization is searched
Hitch fruit.In general meaning, the main target of knowledge mapping is for describing various entities present in real world and general
Thought and the incidence relation between them.However, knowledge mapping is not a completely new thing, but in pervious technology
Or one carried out in theoretical foundation redefines.Knowledge mapping can regard as done on the basis of ontology one it is abundant
And expansion, the ontology describing data pattern of knowledge mapping, the dynamic characteristic of ontology impart knowledge mapping dynamic data schema
The ability of support.Knowledge mapping has benefited from the development of Web, has from the representation of knowledge, natural language processing, more of Web, AI
The gene of aspect.Knowledge mapping is the foundation stone of artificial intelligence, theoretically for each AI scene be knowledge mapping scene,
Including search, chat robots, question and answer, decision support, wearable device etc..A knowledge mapping not instead of single subject,
Including Knowledge Extraction, the representation of knowledge, knowledge fusion, knowledge crowdsourcing, knowledge reasoning, knowledge linking, visualization, semantic search, know
Know the synthesis of the relevant technologies such as question and answer.Knowledge mapping plays bridge beam action, Ke Yigeng between data and artificial intelligence
Good passes through knowledge by Various types of data (text data, structural data, multi-medium data, sensing data, crowdsourcing data etc.)
Fusion forms the knowledge that machine is appreciated that, so that artificial intelligence is more intelligent.
Currently, enterprise has become the mainstay of national economy, become the great power for pushing national development.State
Family is constantly updating the reform of the industrial structure of industry-by-industry and optimization policy, and enterprise is responding and coordinating these political affairs of implementation
While plan, the opportunity and risk for needing the development according to enterprise itself to find that new policy may be brought in time, because safety,
It is efficient to carry out the basis that Production Gain is each enterprise.But no due to scope of the enterprise, property, the industry etc.
Together, enterprise itself can all have some risk problems, and national policy and relevant regulations update are very fast, this allows for enterprise and is locating
Certain loophole and error are had when managing relevant issues, and these loopholes and error are likely to cause not the normal operation of enterprise
Good or even ill effect, this is all not desired to occur for enterprise itself and country.Business risk mainly relies on enterprise certainly
Body related data and its associated data, and these data have certain particularity and professional, only rely on the theory of profession
These data could be handled with practical knowledge, to find enterprise in time, there may be risks, this just needs to slap in time
The information such as enterprise's initial data, industry data and Policy Conditions are held, and this is more difficult for enterprise administrator, simultaneously
But also the cost of enterprise itself can greatly improve, this is more difficult for some venture companies or medium-sized and small enterprises
's.But can efficiently realize that the early warning analysis of business risk has higher meaning for enterprise's own operations, this for
The sound development of enterprise plays certain protective effect.
Due to the problems such as professional knowledge is short of, business data dimension is high and business data amount is big, there is presently no preferable
Method realize effective forecast analysis carried out to business risk, for potential wind existing for enterprise itself, affiliated enterprise of enterprise
Danger can not give warning in advance, and enterprise can not accomplish effective risk averse, this is likely to result in the bad development of enterprise.
Since knowledge mapping the relevant technologies system proposes that the time is not grown, entire technical system is also not perfect enough, and enterprise's wind
Dangerous forecast analysis is more and more important for enterprise and national development, including the companies such as Google, Baidu, Ali are all endeavouring
It is preferably serviced in being provided enterprise by knowledge mapping technology.However, with the rapid growth of business data scale, in reality
Some urgent problems in the application of border also expose therewith, wherein the demand in terms of business risk forecast analysis is the most aobvious
It writes, forecast analysis is carried out to business risk by using knowledge mapping, industry is almost or blank.Therefore known by building enterprise
Knowing collection of illustrative plates and carrying out forecast analysis to business risk just seems particularly urgent.
Invention content
It is of the invention for the application blank of prior art defect and knowledge mapping in terms of business risk forecast analysis
It is designed to provide a kind of the business risk prediction prediction technique and system of knowledge based collection of illustrative plates.To solve business risk prediction
The problem of high cost, poor efficiency, high threshold and low timeliness for analyzing.
The technical scheme is that：
A kind of business risk prediction technique of knowledge based collection of illustrative plates, step include：
1) it builds the entity of Company Knowledge collection of illustrative plates and establishes the relationship between entity and entity, carried out from each setting data source
Knowledge is extracted, and Company Knowledge collection of illustrative plates is formed；
2) all kinds of news informations with enterprise and associated entity are captured, and based on Company Knowledge collection of illustrative plates to grabbing
The news information taken is handled, and the relationship of related entities and event is marked；By the knowledge base of markup information storage to structuring
In, form Company News information knowledge mapping；
3) it is based on Company Knowledge collection of illustrative plates and carries out business risk prediction with Company News information knowledge mapping.
Further, the method for forming the Company News information knowledge mapping is：All kinds of news informations are carried out first
Acquisition and storage, and build text data table；Then by natural language processing method to the information in text tables of data into
Row participle and mark form corresponding entity/relational sequence by the method that pipeline model and deep learning combine, and to entity
Vectorization expression is carried out, the entity vector value that will be obtained in entity/relational sequence and Company Knowledge figure are then calculated by vector
The entity vector value of spectrum compares, to filter out that vector value is equal or the difference of vector value is less than the entity pair of setting value, then again
Entity to filtering out determines identical two entities pair and using correspondent entity as structure Company News money to being compared
The mark entity for interrogating knowledge mapping stores mark entity in the form of the knowledge base of structuring, forms real-time enterprise
Domestic News knowledge mapping.
Further, the entity includes enterprise, people, patent, product；In the Company Knowledge collection of illustrative plates, each entity tool
There is an attributed graph of oneself, mutual relational graph is constituted by setting attribute between entity.
Further, the business risk is predicted as corporate tax risk profile, and method is：In conjunction with receiving for enterprise's former years
Storage of the tax affairs in Company Knowledge collection of illustrative plates, and the storage to the tax affairs of enterprise at this stage in Company Knowledge collection of illustrative plates
Knowledge mapping association analysis is carried out, if the difference of pay taxes project and the amount of money in pay taxes project and the amount of money and former years at this stage is big
In given threshold, then corporate tax risk information warning is generated.
Further, the business risk is predicted as the grading prediction of bidding enterprise qualification, and method is：According to bidding
Information, the related several affiliated enterprises of enterprise A of searching and call for bid in Company Knowledge collection of illustrative plates, and pass through Company Knowledge collection of illustrative plates
Obtain information of these affiliated enterprises in terms of management, determine in affiliated enterprise itself there are the didding enterprise of risk into
Row early warning.
Further, the business risk is predicted as affiliated enterprise's interaction risk profile, and method is：Based on Company Knowledge
Collection of illustrative plates generates enterprise's social graph of Target Enterprise；The most short relation path between enterprise is inquired according to enterprise's social graph,
It determines the close relation degree between each enterprise, affiliated enterprise's interaction risk is predicted.
Further, the business risk is predicted as abnormal investment risk prediction, and method is：Based on Company Knowledge collection of illustrative plates
In investment and financing event occur time sequencing, record the financing development course of enterprise；Then according to financing development course to enterprise
The abnormal investment risk of industry carries out early warning analysis, and abnormal investment risk prediction is carried out to enterprise based on early warning analysis result.
Further, the business risk is predicted as the buying business risk prediction of enterprise, and method is：According to knowledge graph
Upstream-downstream relationship between Pu Zhong enterprises and enterprise determines the buying enterprise B of enterprise A；Pass through Company Knowledge collection of illustrative plates and enterprise
The association of Domestic News knowledge mapping obtains enterprise B itself harmful effect information or related to enterprise B and can be caused to enterprise B
Dysgenic news information predicts enterprise A according to obtained information.
Further, the knowledge of the relationship and extraction using RDF triple store formats between entity, entity carries out
Storage, generates the Company Knowledge collection of illustrative plates.
Further, the information in the Company Knowledge collection of illustrative plates includes enterprise's summary info, business background information, enterprise's hair
Open up information, judicial risk information, business risk information, management state information, intellectual property information, launch information industry and commerce information.
A kind of business risk forecasting system of knowledge based collection of illustrative plates, which is characterized in that generate mould including Company Knowledge collection of illustrative plates
Block, Company News information knowledge mapping generation module and business risk prediction module；Wherein,
The Company Knowledge collection of illustrative plates generation module, entity for building Company Knowledge collection of illustrative plates are simultaneously established between entity and entity
Relationship, from each setting data source carry out knowledge extraction, formed Company Knowledge collection of illustrative plates；
The Company News information knowledge mapping generation module, for the news to all kinds of and enterprise and associated entity
Information is captured, and is handled the news information of crawl based on Company Knowledge collection of illustrative plates, and related entities and event are marked
Relationship；By in markup information storage to the knowledge base of structuring, Company News information knowledge mapping is formed；
The business risk prediction module is looked forward to for being based on Company Knowledge collection of illustrative plates with Company News information knowledge mapping
Industry risk profile.
The present invention builds corresponding Company Knowledge collection of illustrative plates first against enterprise.Pass through basic information, the letter of complaint to enterprise
Breath, lawsuit, the various dimensions associated data such as break one's promise are integrated, and realize Knowledge Extraction and the storage of Company Knowledge collection of illustrative plates.Then lead to
It crosses knowledge mapping and analysis is associated to enterprise's related data, enterprise itself and related information are built finally by knowledge mapping
Displaying, realize association analysis to real time information, to have found that it is likely that existing risk factors, provide risk profile analysis knot
Fruit, and eventually by figure calculate the methods of structure science, rigorous business risk system, effectively evade potential business risk,
Financial risks equivalent risk.
The present invention has extensively studied the building process of Company Knowledge collection of illustrative plates.First, Company Knowledge collection of illustrative plates entity is built, including
The related entities such as enterprise, people, patent, product then build the relationship between entity and entity, and analysis, pass are associated in the later stage
System's excavation, Risk-warning etc. can all be carried out according to the relationship iteration between these entities and entity, such as enterprise and enterprise
Between existing upstream-downstream relationship, ownership and membership relations, investment by investment relation etc., there are ownership and membership relations, legal persons between enterprise and people
, there is kinship etc. in relationship, supervisor's relationship etc., existing belonging relation etc. between enterprise and patent between men, these
Relationship between entity and entity will shortest path discovery, interindustrial relations analysis and enterprise practical control between carrying out enterprise
It is utilized when people.Finally, by carrying out knowledge extraction in the data to separate sources, different structure, wherein data source includes work
Quotient data, tax data, law DOC DATA, public sentiment data etc., data structure mainly include structural data (including link number
According to, enterprise database data), semi-structured data (including list data, table data, data etc. with certain format),
Plain text data, to these data respectively by scheming mapping, D2R (Database to RDF) conversion, wrapper, information extraction
Knowledge Extraction is realized etc. existing mature technology, and forms knowledge and is deposited into Company Knowledge collection of illustrative plates, is used in Company Knowledge collection of illustrative plates
Existing RDF (Resource Description Framework) triple store format is stored.Ultimately form packet
Include enterprise's summary info, business background information (including essential information, business connection, key personnel, shareholder's information, investments abroad,
Branch etc.), enterprise development information (financing history, Core Team, business event, investment event etc.), judicial risk information
(lawsuit, legal, the people that breaks one's promise, executed person, announcement of court session etc.), business risk information (manage abnormal, administrative service
Penalize, break the law on a serious scale, equity pledge, chattel mortgage, tax arrear bulletin, judicial auction etc.), management state information (bidding, bond letter
Breath, the grading of land purchase information, recruitment information, the tax, sampling observation inspections, product information, inlet and outlet credit, qualification certificates etc.), knowledge produces
Weigh information (trademark information, patent, software copyright, Copyright, website are put on record), launch information industry and commerce information (stock
Market participate in holding, listing bulletin, ten big shareholders, equity structure, capital stock variation, dividend situation by shares etc.) etc. enterprise including information
Knowledge mapping, as shown in Figure 1.
Secondly, the present invention has extensively studied the building process of Company News event collection of illustrative plates.So-called event refers to the thing occurred
Feelings usually have the attributes such as time, place, participant, and the generation of event is probably due to a generation acted or system shape
The change of state.Event extraction is exactly that (language that i.e. people is appreciated that, form include voice, word etc., interior from natural language form
It includes evental news to hold) evental news in extract the interested event information of user, and showed in the form of structuring
Come.In the present invention, by all kinds of News Finance and Economy websites, enterprise official website, government website, industrial and commercial taxation website, patent network, method
The real time monitoring for restraining document related web site, captures all kinds of news informations with enterprise and associated entity, and use
Pipeline carries out the news information of crawl on the basis of Company Knowledge collection of illustrative plates with the method that deep learning is combined related
Processing, and finally by treated, news information is stored into the knowledge base of structuring, to form real-time Company News money
Knowledge mapping is interrogated, it is specific as follows：All kinds of news informations are acquired and are stored first, and build text data table, by certainly
Right language processing method is segmented and is marked, and forms corresponding reality by the method that Pipeline and deep learning combine
Body/relational sequence, and vectorization expression is carried out to entity, the reality in entity/relational sequence then will be obtained by vector calculating
Body vector value and the entity vector value of Company Knowledge collection of illustrative plates compare, equal or close to (such as vector value to filter out vector value
Difference be less than setting value) entity pair, then again to the entity that filters out to being compared, to will be with invalid or inefficient information
It excludes, finally determine identical two entities pair and returns, and using correspondent entity as structure Company News information knowledge mapping
Mark entity, complete the information high to accuracy and mark entity stored in the form of the knowledge base of structuring, finally
Real-time Company News information knowledge mapping is formed, and Company Knowledge collection of illustrative plates can be reached by the entity and provided with Company News
News knowledge mapping is mutually related purpose.Its process is as shown in Figure 2.
Finally, the present invention has studied the business risk based on Company Knowledge collection of illustrative plates and Company News information knowledge mapping and predicts
Analysis method.Knowledge mapping is the graph model structure of entity and its correlation, it can more intuitively show entity and reality
Relationship between body, and it can be found that by relation transmission the potential relationship between entity and entity.In the present invention, pass through
Company Knowledge collection of illustrative plates and Company News information knowledge mapping are established, in Company Knowledge collection of illustrative plates, enterprise, people, patent etc. have certainly
Oneself attributed graph, and mutual relational graph is constituted by a certain attribute between enterprise and enterprise (or with people, patent etc.).
Business risk prediction, basic ideas can be carried out based on Company Knowledge collection of illustrative plates and Company News information knowledge mapping：Enterprise is known
Know collection of illustrative plates be associated by entity attribute with Company News information knowledge mapping, enterprise have directly (enterprise itself) or
When connecing the media event generation (with relevant enterprise of enterprise or individual), the phase in entity associated triggering Company Knowledge collection of illustrative plates can be passed through
It closes entity directly to be analyzed by the entity attributes value of Company Knowledge collection of illustrative plates in Company Knowledge collection of illustrative plates, is finding news
When the value in the attributed graph with Company Knowledge collection of illustrative plates in description is variant, the difference of such value will be analyzed according to practical business
Whether risk can be caused to enterprise, risk profile is carried out if meeting, if it is not, subsequent indirect analysis can be carried out, led to
It crosses entity attributes value and entity relationship diagram is associated analysis, risk is carried out to all entities being associated to realize
Prediction.It can pass through single attribute or combination by the attributed graph in Company Knowledge collection of illustrative plates and in conjunction with respective associated analysis rule
Attribute is analyzed, for example, enterprise relates to the management state for telling that information may influence enterprise, relate to tell that information has update when,
Need whether it can cause undesirable influence to the operation of enterprise by analyzing judgement；In another example industrial and commercial information, the tax of enterprise
Information, assets information need and the essential information of enterprise is mutually unified, if a certain or a variety of in preceding several information is occurring
It when variation, needs to analyze the essential information of enterprise, judges whether it meets the essential information of enterprise, if with enterprise
Essential information has conflict, then needs to be updated essential information or the industrial and commercial information to enterprise, tax information and assets are believed
Breath is verified, and enterprise is avoided to have illegal behavior；Furthermore the patent information of enterprise may be to a variety of letters of enterprise
Breath impacts, if the scientific achievement information of enterprise changes, may to the financing situation of enterprise, stock price with
And product sales situation impacts, the variation of this single attribute may be caused by other attributes, including science research input, personnel
Input etc., but it equally causes the variation of a variety of attributes.It can pass through a certain attribute or group of enterprise by relational graph
Other associated entities (enterprise, individual, patent etc.) are analyzed in the variation for closing attribute, for example, relating to for enterprise tells information more
When new, it may affect to downstream distributor thereon and shareholder enterprise or individual, it can be very by relational graph
Fast finds these enterprises or individual, then causes to analyze to it；In another example shareholder's information or the equity structure letter of enterprise
Breath change, may affect to its cooperative enterprise or individual, shareholder's factor may influence enterprise and enterprise
Cooperative relationship between (individual), this just need by relational graph find with the relevant enterprise of the enterprise shareholder or individual, both
It needs enterprise itself to accomplish that business risk is taken precautions against, is also required to understand this information in time simultaneously for cooperative enterprise or individual,
With judge whether to continue will the business tie-up；Furthermore the variation of the information such as product, patent, the software copyright of enterprise, same meeting
Influencing its affiliated enterprise, either individual but will allow especially for the enterprise or individual, the change of these information for investing the enterprise
Investment enterprise or it is personal understand the enterprise whether benign development, it is invested whether rationally beneficial, or even is related to and whether needs
Increase investment etc..The methods of by the combination of Company Knowledge collection of illustrative plates and Company News information knowledge mapping, and utilize figure calculating,
In conjunction with structure of knowledge structure science, the rigorous business risk evaluation system of profession, effectively evade potential business risk and money
Golden risk.It is specifically including but not limited to：
(1) corporate tax risk profile：In conjunction with the storage of the tax affairs in Company Knowledge collection of illustrative plates in enterprise's former years, and
Knowledge mapping association analysis is carried out to the storage of the tax affairs of enterprise at this stage in Company Knowledge collection of illustrative plates, if at this stage
The difference of pay taxes project and the amount of money in project of paying taxes and the amount of money and former years is more than given threshold, then there may be tax wind for enterprise
Danger carries out risk warning, to avoid the generation of the unreasonable tax affairs caused by maloperation to enterprise and the tax authority；
(2) the buying business risk audit of enterprise：By the upstream-downstream relationship between enterprise and enterprise in knowledge mapping
Embodiment, it is and new by Company Knowledge collection of illustrative plates and enterprise if finding the buying enterprise B of enterprise A in Company Knowledge collection of illustrative plates
The association for hearing information knowledge mapping finds that enterprise B itself or other and enterprise B related news information may cause enterprise B
The harmful effect of fund, operation, law etc., then by enterprise A and incidence relation of the enterprise B in Company Knowledge collection of illustrative plates,
Enterprise A can be allow to understand concrete condition in time, if enterprise B itself be implicitly present in operation or financial risks (such as
Enterprise B itself capital chain rupture, then its can not continue buying production raw material used, i.e. product will stop production, if enterprise A to
Enterprise B carries out product purchasing, then enterprise B can not carry out product delivery in theory, this can cause to prolong to the work of enterprise A
Mistake or direct losses), then enterprise A needs to consider whether such risk can cause harmful effect to itself, to realize to enterprise
The risk of industry B is audited；
(3) bidding enterprise qualification is graded：By the bidding information between enterprise and enterprise, bid enterprise A can be
It realizes in Company Knowledge collection of illustrative plates and to be associated with the didding enterprises such as enterprise B, enterprise C, enterprise D, and pass through Company Knowledge collection of illustrative plates
Concrete condition of these enterprises in terms of management is analyzed in real time, and finding in these enterprises itself in time, there are the bids of risk
Enterprise carries out early warning, and bid enterprise is avoided to cause unnecessary loss；
(4) customer resources Classification Management：In Company Knowledge collection of illustrative plates, enterprise A can throw its all upstream and downstream firms, trick
Mark enterprise, investment enterprise, industry relevant enterprise carries out resource management and potential customers seek, and helps enterprise A to find in advance potential
Client and bad client, avoid capital loss；
(5) enterprise's social graph is inquired：Based on investment, tenure, patent, bidding, the relationship of telling is related to using Target Enterprise as core
The heart is spread layer by layer outward, forms a cyberrelationship figure, and intuitive solid shows being associated between enterprise and enterprise, enterprise and personnel
Relationship；
(6) enterprise finally controls people's inquiry：The maximum shareholder of shareholding ratio is found with equity investment relationship, it is final to trace
To natural person or management of state-owned property department, determine that enterprise finally controls people, auxiliary carries out forecast analysis to business risk；
(7) path discovery between enterprise：Based on equity, tenure, patent, bidding, relates to and tell etc. that the network that relationships are formed closes
In system, inquire enterprise between most short relation path, weigh enterprise between close relation degree, to affiliated enterprise interact risk into
Row forecast analysis, can help revenue department investigate and prosecute tax evasion, illegal fund transfer situations such as；
(8) newly established enterprise's financing development course：Based in Company Knowledge collection of illustrative plates investment and financing event occur time sequencing,
The financing development course of enterprise is recorded, helps enterprise preferably to show self-growth process, equally helps other investment enterprise straight
It sees and checks the development course of enterprise, (such as enterprise A has possessed more wheel financings in early period, but does not obtain to abnormal investment
Apparent achievement and profit are obtained, then proves enterprise A from being problematic in operation or management aspect, this is to subsequent throwing
Money has larger risk) carry out early warning analysis；, abnormal investment risk prediction is carried out to enterprise based on early warning analysis result；
(9) marketing enterprises share price early warning analysis：Based on Company Knowledge collection of illustrative plates and Company News information knowledge mapping to upper
The news data of enterprise of city is associated analysis, and early warning analysis is carried out to the abnormal of its stock share price.
Implementation procedure of the present invention is as follows, as shown in Figure 3：
(1) Company Knowledge collection of illustrative plates physical model is built, existing relationship between all kinds of entities is marked.
(2) by business taxation report, industrial and commercial report, relate to and tell the open source resources such as bulletin, media event text to these enterprises
The example of the relevant structural data of industry, semi-structured data, the Knowledge Extraction realization physical model of text data, relational model
Change, forms Company Knowledge collection of illustrative plates, and stored in the form of RDF triples.
(3) structure reptile captures all kinds of enterprise web sites in real time, is captured to news information, and relational database is arrived in storage
In.
(4) it uses at news information of the method that Pipeline (pipeline model) is combined with deep learning to crawl
Reason is extracted relevant event information and forms Company News information knowledge mapping, and stored in the form of RDF triples, together
When by the unique mark (such as identification card number of enterprise name or social credibility Unicode, people) of entity by itself and Company Knowledge
Collection of illustrative plates is associated, and marks the relationship of related entities and event；By in markup information storage to the knowledge base of structuring, enterprise is formed
Industry Domestic News knowledge mapping.
(5) kinds of relationships in Company Knowledge collection of illustrative plates is analyzed, including equity relationship between enterprise and enterprise, on
Between investment relation, actual controller, employer-employee relationship between downstream relationship etc., enterprise and people etc., enterprise and intellectual property
The kinds of relationships such as the belonging relation between belonging relation, people and intellectual property, in conjunction with pass of the types of applications model between entity
Connection relationship carries out iteration analysis, and by the transmission, verification and storage of analysis result implementation relation, is that the enterprise in later stage closes
It is that atlas analysis, the analysis of Company News information knowledge mapping and risk profile analysis etc. provide data support.
(6) Company News information knowledge mapping is analyzed, and combines the Company Knowledge collection of illustrative plates being associated, according to enterprise
The analysis result of kinds of relationships in industry knowledge mapping, between affiliated enterprise and enterprise, enterprise and people and enterprise and other realities
Correlation between body carries out profound iterative analysis, and finally will likely existing business risk progress early warning.
(7) Various types of data, model and risk profile analysis situation are shown by Web browser.
Compared with prior art, the present invention has the advantage that：
(1) high innovative.The present invention is concrete application of the knowledge mapping in business risk forecast analysis field, has filled up mesh
Preceding knowledge mapping is in the blank of business risk analysis field, Company Knowledge collection of illustrative plates and Company News information the knowledge mapping tool of structure
There is higher practicability, the model construction and analysis work for Company Knowledge collection of illustrative plates had both combined current knowledge mapping field
Advanced technology, while also preferably in conjunction with the particularity of business data and professional business risk forecast analysis model is carried out
The analysis of various dimensions is verified, and has certain novelty.
(2) low threshold.Since the business risk prediction analysis method of knowledge based collection of illustrative plates of the present invention is to finally using
Family makes to be used to say that black box, terminal user are not necessarily to be concerned about the building process of Company Knowledge collection of illustrative plates, it is only necessary to according to specific need
It to be associated analysis in conjunction with Company Knowledge collection of illustrative plates and Company News information knowledge mapping and can be obtained corresponding analysis result, this
Outside, a large amount of analysis model has been had been built up, disclosure satisfy that the needs of user substantially.The present invention, will be each by web interface simultaneously
The analysis result of class model is supplied to user by data with the means that visualization is combined, and analysis is intuitively checked convenient for user
As a result, greatly reducing the use threshold of user.
(3) have specific aim, accuracy high.The present invention is different from this stage carrying out business risk by artificial means pre-
Survey the mode of analysis, data scale and data accuracy higher, more targetedly.Pass through the side of big data and deep learning
Method is trained all kinds of methods in model, forms ripe scoring model, and the method by scheming to calculate is to knowledge mapping
In all kinds of knowledge carry out mining analysis, actively discover some potential relationships, can than artificial means faster, deeper into discovery
Risk that may be present, it is also more rapid direct to the processing of data knowledge, and to visualize in such a way that data are combined
Terminal user is showed, the risk profile analysis result that enterprise is faced can be more intuitively embodied, avoid to the greatest extent
Performance bottleneck caused by human factor so that analytical performance is maximized with accuracy.
(4) stable, it is expansible.This method is that knowledge based graphical spectrum technology is realized, and knowledge mapping has high expand
Malleability enables to knowledge mapping scale increasing in conjunction with all kinds of Knowledge Extractions and Knowledge Fusion Technology, is based on RDF ternarys
The storage mode of group can support cross-platform mode, can the stable operation under Spark platforms, and can be flat by Spark
GraphX under platform, which is realized, to be excavated and analyzes to the figure of knowledge mapping, and efficiency is more preferable.And the mode of RDF triples support it is a variety of
The extension of form can preferably increase new knowledge in the case where not influencing existing knowledge collection of illustrative plates, also can be to working as
The update of preceding knowledge mapping.
Description of the drawings
Fig. 1 is the knowledge type figure of the present invention；
Fig. 2 is that the media event of the present invention extracts flow chart；
Fig. 3 is the overall flow figure of the present invention.
Specific implementation mode
Below in conjunction with the accompanying drawings with specific implementation case, the present invention is furture elucidated, it should be understood that these case study on implementation are only used for
Illustrate the present invention rather than limit the scope of the invention, after having read the present invention, those skilled in the art are to the present invention
The modifications of various equivalent forms fall within the application range as defined in the appended claims.
As shown in figure 3, the present invention carries out the model construction of Company Knowledge collection of illustrative plates, including physical model and relationship mould first
Type then instantiates physical model and relational model by information collection, the information of acquisition include enterprise's summary info,
Business background information (including essential information, business connection, key personnel, shareholder's information, investments abroad, branch etc.), enterprise
Industry Information of Development (financing history, Core Team, business event, investment event etc.), judicial risk information (lawsuit, law
Announce, the people that breaks one's promise, executed person, announcement of court session etc.), business risk information (manages exception, administrative penalty, breaks the law on a serious scale, equity
Pledge, chattel mortgage, tax arrear bulletin, judicial auction etc.), management state information (bidding, bond information, land purchase information, recruitment
Information, sampling observation inspections, product information, imports and exports credit, qualification certificates etc. at tax grading), intellectual property information (trademark information,
Patent, software copyright, Copyright, website are put on record), launch information industry and commerce information (stock market, participate in by shares it is holding, on
City's bulletin, ten big shareholders, equity structure, capital stock variation, dividend situation etc.) etc., it is specific as shown in Figure 2.
Secondly, by all kinds of News Finance and Economy websites, enterprise official website, government website, industrial and commercial taxation website, patent network, method
The real time monitoring for restraining document related web site captures all kinds of media events, and combines Company Knowledge collection of illustrative plates, builds Company News information
Knowledge mapping；
Third carries out entity associated to Company Knowledge collection of illustrative plates and Company News information knowledge mapping；
Finally, it is excavated and is divided by the figure of figure mining analysis and Company News information knowledge mapping to Company Knowledge collection of illustrative plates
The association analysis to basic model is realized in analysis, is shown to the relationship of all kinds of entity occurrences, to by Company News information knowledge mapping
The event of triggering is associated analysis, carries out forecast analysis to risk that may be present, and all kinds of analysis results are fed back to use
Family.
It is above to implement to be merely illustrative of the technical solution of the present invention rather than be limited, the ordinary skill people of this field
Member can be modified or replaced equivalently technical scheme of the present invention, without departing from the spirit and scope of the present invention, this hair
Bright protection domain should be subject to described in claims.
Claims (10)
1. a kind of business risk prediction technique of knowledge based collection of illustrative plates, step include：
1) it builds the entity of Company Knowledge collection of illustrative plates and establishes the relationship between entity and entity, knowledge is carried out from each setting data source
Extraction forms Company Knowledge collection of illustrative plates；
2) all kinds of news informations with enterprise and associated entity are captured, and based on Company Knowledge collection of illustrative plates to crawl
News information is handled, and the relationship of related entities and event is marked；Markup information is stored into the knowledge base of structuring, shape
At Company News information knowledge mapping；
3) it is based on Company Knowledge collection of illustrative plates and carries out business risk prediction with Company News information knowledge mapping.
2. the method as described in claim 1, which is characterized in that the method for forming the Company News information knowledge mapping is：
All kinds of news informations are acquired and are stored first, and build text data table；Then pass through natural language processing method pair
Information in text tables of data is segmented and is marked, and is formed accordingly by the method that pipeline model and deep learning combine
Entity/relational sequence, and vectorization expression is carried out to entity, then it will be obtained in entity/relational sequence by vector calculating
Entity vector value and the entity vector value of Company Knowledge collection of illustrative plates compare, and to filter out, vector value is equal or the difference of vector value is less than
The entity pair of setting value, then again to the entity that filters out to being compared, determining identical two entities pair and corresponding to
Entity as structure Company News information knowledge mapping mark entity, in the form of the knowledge base of structuring to mark entity into
Row storage, forms real-time Company News information knowledge mapping.
3. method as claimed in claim 1 or 2, which is characterized in that the entity includes enterprise, people, patent, product；It is described
In Company Knowledge collection of illustrative plates, each entity has the attributed graph of oneself, constitutes mutual pass by setting attribute between entity
System's figure.
4. the method as described in claim 1, which is characterized in that the business risk is predicted as corporate tax risk profile,
Method is：In conjunction with the storage of the tax affairs in Company Knowledge collection of illustrative plates in enterprise's former years, and the feelings of paying taxes to enterprise at this stage
Storage of the condition in Company Knowledge collection of illustrative plates carries out knowledge mapping association analysis, if paying taxes project and the amount of money and former years at this stage
The difference of pay taxes project and the amount of money be more than given threshold, then generate corporate tax risk information warning.
5. the method as described in claim 1, which is characterized in that it is pre- that the business risk is predicted as the grading of bidding enterprise qualification
It surveys, method is：According to bidding information, searches in Company Knowledge collection of illustrative plates and looked forward to the related several associations of bid enterprise A
Industry, and information of these affiliated enterprises in terms of management is obtained by Company Knowledge collection of illustrative plates, it determines in affiliated enterprise
There are the didding enterprises of risk to carry out early warning for itself.
6. the method as described in claim 1, which is characterized in that it is pre- that the business risk is predicted as affiliated enterprise's interaction risk
It surveys, method is：Enterprise's social graph of Target Enterprise is generated based on Company Knowledge collection of illustrative plates；According to enterprise's social graph inquiry
Most short relation path between enterprise, determines the close relation degree between each enterprise, predicts affiliated enterprise's interaction risk.
7. the method as described in claim 1, which is characterized in that the business risk is predicted as abnormal investment risk prediction,
Method is：Based on the time sequencing that the investment and financing event in Company Knowledge collection of illustrative plates occurs, the financing development course of enterprise is recorded；So
Early warning analysis is carried out to the abnormal investment risk of enterprise according to financing development course afterwards, enterprise is carried out based on early warning analysis result
Abnormal investment risk prediction.
8. the method as described in claim 1, which is characterized in that the buying business risk that the business risk is predicted as enterprise is pre-
It surveys, method is：According to the upstream-downstream relationship in knowledge mapping between enterprise and enterprise, the buying enterprise B of enterprise A is determined；
By Company Knowledge collection of illustrative plates and Company News information knowledge mapping be associated with to obtain enterprise B itself harmful effect information or with enterprise
Industry B is related and dysgenic news information can be caused to enterprise B, is predicted enterprise A according to obtained information.
9. the method as described in claim 1, which is characterized in that using RDF triple store formats between entity, entity
Relationship and the knowledge of extraction are stored, and the Company Knowledge collection of illustrative plates is generated；Information in the Company Knowledge collection of illustrative plates includes
Enterprise's summary info, business background information, enterprise development information, judicial risk information, business risk information, management state letter
Breath, intellectual property information, launch information industry and commerce information.
10. a kind of business risk forecasting system of knowledge based collection of illustrative plates, which is characterized in that generate mould including Company Knowledge collection of illustrative plates
Block, Company News information knowledge mapping generation module and business risk prediction module；Wherein,
The Company Knowledge collection of illustrative plates generation module, entity for building Company Knowledge collection of illustrative plates simultaneously establish the pass between entity and entity
System carries out knowledge extraction from each setting data source, forms Company Knowledge collection of illustrative plates；
The Company News information knowledge mapping generation module, for the news information to all kinds of and enterprise and associated entity
It is captured, and the news information of crawl is handled based on Company Knowledge collection of illustrative plates, mark the relationship of related entities and event；
By in markup information storage to the knowledge base of structuring, Company News information knowledge mapping is formed；
The business risk prediction module, for carrying out enterprise's wind based on Company Knowledge collection of illustrative plates and Company News information knowledge mapping
Danger prediction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810271489.4A CN108596439A (en) | 2018-03-29 | 2018-03-29 | A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810271489.4A CN108596439A (en) | 2018-03-29 | 2018-03-29 | A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108596439A true CN108596439A (en) | 2018-09-28 |
Family
ID=63624932
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810271489.4A Pending CN108596439A (en) | 2018-03-29 | 2018-03-29 | A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108596439A (en) |
Cited By (103)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109165337A (en) * | 2018-10-17 | 2019-01-08 | 珠海市智图数研信息技术有限公司 | A kind of method and system of knowledge based map construction bidding field association analysis |
| CN109189867A (en) * | 2018-10-23 | 2019-01-11 | 中山大学 | Relationship discovery method, apparatus and storage medium based on Corporate Intellectual map |
| CN109191015A (en) * | 2018-10-17 | 2019-01-11 | 大国创新智能科技(东莞)有限公司 | New high-tech enterprise's identification and robot system based on big data and deep learning |
| CN109359133A (en) * | 2018-10-17 | 2019-02-19 | 大国创新智能科技(东莞)有限公司 | Personalized identification and robot system based on big data and deep learning |
| CN109472485A (en) * | 2018-11-01 | 2019-03-15 | 成都数联铭品科技有限公司 | Enterprise breaks one's promise Risk of Communication inquiry system and method |
| CN109558492A (en) * | 2018-10-16 | 2019-04-02 | 中山大学 | A kind of listed company's knowledge mapping construction method and device suitable for event attribution |
| CN109584045A (en) * | 2018-11-19 | 2019-04-05 | 平安科技（深圳）有限公司 | Accrediting amount configuration method, device, computer equipment and storage medium |
| CN109583738A (en) * | 2018-11-22 | 2019-04-05 | 第创业证券股份有限公司 | A kind of device and method for bond risk control |
| CN109636584A (en) * | 2018-11-19 | 2019-04-16 | 平安科技（深圳）有限公司 | Default Probability methods of exhibiting, device, computer equipment and storage medium |
| CN109657066A (en) * | 2018-11-19 | 2019-04-19 | 平安科技（深圳）有限公司 | Knowledge mapping construction method, device and computer equipment based on multi-angle of view |
| CN109657837A (en) * | 2018-11-19 | 2019-04-19 | 平安科技（深圳）有限公司 | Default Probability prediction technique, device, computer equipment and storage medium |
| CN109670048A (en) * | 2018-11-19 | 2019-04-23 | 平安科技（深圳）有限公司 | Map construction method, apparatus and computer equipment based on air control management |
| CN109670944A (en) * | 2018-12-19 | 2019-04-23 | 信雅达系统工程股份有限公司 | A kind of rating business credit method and system based on map relational network |
| CN109726002A (en) * | 2018-12-30 | 2019-05-07 | 联想(北京)有限公司 | A kind of process flow method of adjustment and device |
| CN109828965A (en) * | 2019-01-09 | 2019-05-31 | 北京小乘网络科技有限公司 | A kind of method and electronic equipment of data processing |
| CN109840547A (en) * | 2019-01-04 | 2019-06-04 | 三峡大学 | A kind of identification of intellectual property feature and working method based on Quantum fourier transform |
| CN109858740A (en) * | 2018-12-21 | 2019-06-07 | 中化资本有限公司 | Appraisal procedure, device, computer equipment and the storage medium of business risk |
| CN109858762A (en) * | 2018-12-29 | 2019-06-07 | 重庆誉存大数据科技有限公司 | A kind of business risk prediction technique and device |
| CN109918452A (en) * | 2019-02-14 | 2019-06-21 | 北京明略软件系统有限公司 | A kind of method, apparatus of data processing, computer storage medium and terminal |
| CN110046973A (en) * | 2019-04-17 | 2019-07-23 | 成都市审计局 | It is a kind of that mark string mark detection method is enclosed based on incidence relation big data analysis |
| CN110175239A (en) * | 2019-04-23 | 2019-08-27 | 成都数联铭品科技有限公司 | A kind of construction method and system of knowledge mapping |
| CN110197280A (en) * | 2019-05-20 | 2019-09-03 | 中国银行股份有限公司 | A kind of knowledge mapping construction method, apparatus and system |
| CN110209930A (en) * | 2019-04-30 | 2019-09-06 | 平安科技（深圳）有限公司 | The investee's analysis method and device of knowledge based map |
| CN110263233A (en) * | 2019-05-06 | 2019-09-20 | 平安科技（深圳）有限公司 | Enterprise's public sentiment base construction method, device, computer equipment and storage medium |
| CN110363449A (en) * | 2019-07-25 | 2019-10-22 | 中国工商银行股份有限公司 | A kind of Risk Identification Method, apparatus and system |
| CN110413858A (en) * | 2019-06-19 | 2019-11-05 | 深圳壹账通智能科技有限公司 | Enterprise's public feelings information querying method, device, computer equipment and storage medium |
| CN110442731A (en) * | 2019-07-24 | 2019-11-12 | 中电科新型智慧城市研究院有限公司 | A kind of traffic operation system based on traffic administration knowledge mapping |
| CN110489520A (en) * | 2019-07-08 | 2019-11-22 | 平安科技（深圳）有限公司 | Event-handling method, device, equipment and the storage medium of knowledge based map |
| CN110503236A (en) * | 2019-07-08 | 2019-11-26 | 中国平安人寿保险股份有限公司 | Risk Forecast Method, device, equipment and the storage medium of knowledge based map |
| CN110503295A (en) * | 2019-07-05 | 2019-11-26 | 深圳壹账通智能科技有限公司 | Risk analysis method, device, computing terminal and the storage medium of supply chain finance |
| CN110597999A (en) * | 2019-08-01 | 2019-12-20 | 湖北工业大学 | Judicial case knowledge graph construction method of dependency syntactic analysis relation extraction model |
| CN110659981A (en) * | 2019-09-26 | 2020-01-07 | 北京明略软件系统有限公司 | Enterprise dependency relationship identification method and device and electronic equipment |
| CN110674970A (en) * | 2019-08-19 | 2020-01-10 | 广州荔支网络技术有限公司 | Enterprise legal risk early warning method, device, equipment and readable storage medium |
| CN110765317A (en) * | 2019-09-18 | 2020-02-07 | 上海生腾数据科技有限公司 | Enterprise beneficiary operation system and method |
| CN110781311A (en) * | 2019-09-18 | 2020-02-11 | 上海生腾数据科技有限公司 | Enterprise consistent action calculation system and method |
| CN110866057A (en) * | 2019-11-12 | 2020-03-06 | 北京明略软件系统有限公司 | Method and device for realizing data processing, computer storage medium and terminal |
| CN110889556A (en) * | 2019-11-28 | 2020-03-17 | 福建亿榕信息技术有限公司 | Enterprise operation risk prediction method and system |
| CN110971674A (en) * | 2019-11-15 | 2020-04-07 | 北京明略软件系统有限公司 | Method, device, computer storage medium and terminal for realizing information processing |
| WO2020073727A1 (en) * | 2018-10-11 | 2020-04-16 | 平安科技（深圳）有限公司 | Risk forecast method, device, computer apparatus, and storage medium |
| CN111027832A (en) * | 2019-11-28 | 2020-04-17 | 卓尔智联(武汉)研究院有限公司 | Tax risk determination method, apparatus and storage medium |
| CN111046192A (en) * | 2019-12-25 | 2020-04-21 | 中国建设银行股份有限公司 | Identification method and device for bank case-involved account |
| CN111061814A (en) * | 2019-12-10 | 2020-04-24 | 北京明略软件系统有限公司 | Modeling analysis method and device, electronic equipment and storage medium |
| CN111105311A (en) * | 2019-12-19 | 2020-05-05 | 第一创业证券股份有限公司 | Dynamic credit rating method and device for bond body |
| CN111160841A (en) * | 2019-11-29 | 2020-05-15 | 广东轩辕网络科技股份有限公司 | Organization architecture construction method and device based on knowledge graph |
| CN111191853A (en) * | 2020-01-06 | 2020-05-22 | 支付宝(杭州)信息技术有限公司 | Risk prediction method and device and risk query method and device |
| CN111222681A (en) * | 2019-11-05 | 2020-06-02 | 量子数聚（北京）科技有限公司 | Data processing method, device, equipment and storage medium for enterprise bankruptcy risk prediction |
| CN111241300A (en) * | 2020-01-09 | 2020-06-05 | 中信银行股份有限公司 | Public opinion early warning and risk propagation analysis method, system, equipment and storage medium |
| CN111259160A (en) * | 2018-11-30 | 2020-06-09 | 百度在线网络技术（北京）有限公司 | Knowledge graph construction method, device, equipment and storage medium |
| CN111325355A (en) * | 2020-03-19 | 2020-06-23 | 中国建设银行股份有限公司 | Method and device for determining actual control persons of enterprises, computer equipment and medium |
| CN111383102A (en) * | 2020-03-27 | 2020-07-07 | 北京明略软件系统有限公司 | Financial credit risk identification method, model construction method and device |
| CN111400504A (en) * | 2020-03-12 | 2020-07-10 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying enterprise key people |
| CN111414485A (en) * | 2020-03-17 | 2020-07-14 | 北京恒通慧源大数据技术有限公司 | Enterprise customer association relation map construction method and device, storage and computer |
| CN111583033A (en) * | 2020-04-01 | 2020-08-25 | 北京智信度科技有限公司 | Association analysis method and device based on relation between listed company and stockholder |
| 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 |
| CN111582643A (en) * | 2020-04-08 | 2020-08-25 | 北京明略软件系统有限公司 | Method, device and equipment for collecting enterprise risk information |
| CN111598702A (en) * | 2020-04-14 | 2020-08-28 | 徐佳慧 | Knowledge graph-based method for searching investment risk semantics |
| CN111709235A (en) * | 2020-05-28 | 2020-09-25 | 上海发电设备成套设计研究院有限责任公司 | Text data statistical analysis system and method based on natural language processing |
| CN111767370A (en) * | 2020-06-24 | 2020-10-13 | 北京墨丘科技有限公司 | Associated entity mining method, system and computer readable medium |
| CN111858903A (en) * | 2020-06-11 | 2020-10-30 | 创新工场(北京)企业管理股份有限公司 | Method and device for negative news early warning |
| CN111899089A (en) * | 2020-07-01 | 2020-11-06 | 苏宁金融科技(南京)有限公司 | Enterprise risk early warning method and system based on knowledge graph |
| CN111932131A (en) * | 2020-08-12 | 2020-11-13 | 上海冰鉴信息科技有限公司 | Service data processing method and device |
| CN111949834A (en) * | 2019-05-17 | 2020-11-17 | 上海树融数据科技有限公司 | Site selection method and site selection platform |
| CN111951079A (en) * | 2020-08-14 | 2020-11-17 | 国网电子商务有限公司 | Credit rating method and device based on knowledge graph and electronic equipment |
| CN111967976A (en) * | 2020-08-19 | 2020-11-20 | 中国银行股份有限公司 | Risk enterprise determination method and device based on knowledge graph |
| CN111984797A (en) * | 2020-09-07 | 2020-11-24 | 中国银行股份有限公司 | Customer identity recognition device and method |
| CN112015909A (en) * | 2020-08-19 | 2020-12-01 | 普洛斯科技(重庆)有限公司 | Knowledge graph construction method and device, electronic equipment and storage medium |
| CN112115278A (en) * | 2020-09-28 | 2020-12-22 | 中国建设银行股份有限公司 | Actual control person relation mining method and device based on knowledge graph |
| CN112131275A (en) * | 2020-09-23 | 2020-12-25 | 中国科学技术大学智慧城市研究院(芜湖) | Enterprise portrait construction method of holographic city big data model and knowledge graph |
| CN112131392A (en) * | 2020-08-01 | 2020-12-25 | 赛飞特工程技术集团有限公司 | Public health epidemic situation early warning method and system based on knowledge graph |
| CN112214614A (en) * | 2020-10-16 | 2021-01-12 | 民生科技有限责任公司 | Method and system for mining risk propagation path based on knowledge graph |
| CN112286986A (en) * | 2020-10-14 | 2021-01-29 | 北京乾唐伟业科技股份公司 | Property right analysis management system based on enterprise genealogy |
| CN112465411A (en) * | 2021-01-27 | 2021-03-09 | 支付宝(杭州)信息技术有限公司 | Risk prediction method, device and equipment |
| CN112487208A (en) * | 2020-12-14 | 2021-03-12 | 杭州安恒信息技术股份有限公司 | Network security data association analysis method, device, equipment and storage medium |
| CN112487209A (en) * | 2020-12-15 | 2021-03-12 | 厦门市美亚柏科信息股份有限公司 | String mark behavior analysis method based on knowledge graph, terminal equipment and storage medium |
| CN112487108A (en) * | 2020-11-30 | 2021-03-12 | 中冶赛迪工程技术股份有限公司 | Enterprise competition analysis method based on knowledge graph |
| CN112598507A (en) * | 2020-12-25 | 2021-04-02 | 北京知因智慧科技有限公司 | Excessive credit granting risk prediction system and method based on knowledge graph |
| CN112598302A (en) * | 2020-12-25 | 2021-04-02 | 北京知因智慧科技有限公司 | Enterprise data evaluation method and device and server |
| CN112734270A (en) * | 2021-01-19 | 2021-04-30 | 中国科学院地理科学与资源研究所 | Measuring method, system and data platform for energy risk conduction |
| CN112750028A (en) * | 2020-12-30 | 2021-05-04 | 北京知因智慧科技有限公司 | Risk early warning method and device of event text based on entity extraction |
| CN112800896A (en) * | 2021-01-18 | 2021-05-14 | 北京明略软件系统有限公司 | Security emergency measure self-response method and system based on knowledge graph |
| CN112836919A (en) * | 2020-11-30 | 2021-05-25 | 广东电网有限责任公司 | Supplier association analysis method and device based on knowledge graph |
| CN113051365A (en) * | 2020-12-10 | 2021-06-29 | 深圳证券信息有限公司 | Industrial chain map construction method and related equipment |
| CN113159796A (en) * | 2021-03-12 | 2021-07-23 | 国网英大国际控股集团有限公司 | Trade contract verification method and device |
| CN113297044A (en) * | 2020-06-11 | 2021-08-24 | 阿里巴巴集团控股有限公司 | Operation and maintenance risk early warning method and device |
| CN113344460A (en) * | 2021-07-07 | 2021-09-03 | 上海软中信息技术有限公司 | Intelligent risk prediction and identification system, equipment and device based on big data map calculation |
| CN113342904A (en) * | 2021-04-01 | 2021-09-03 | 山东省人工智能研究院 | Enterprise service recommendation method based on enterprise feature propagation |
| CN113362125A (en) * | 2021-04-19 | 2021-09-07 | 浙江锐驰网络科技有限公司 | Information screening system of electric business enterprise incubator |
| CN113361962A (en) * | 2021-06-30 | 2021-09-07 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying enterprise risk based on block chain network |
| CN113392228A (en) * | 2021-08-03 | 2021-09-14 | 广域铭岛数字科技有限公司 | Abnormity prediction and tracing method, system, equipment and medium based on automobile production |
| CN113761212A (en) * | 2020-06-01 | 2021-12-07 | 中国石油化工股份有限公司 | Knowledge graph construction method and device based on pipeline integrity |
| CN114022058A (en) * | 2022-01-06 | 2022-02-08 | 成都晓多科技有限公司 | Small and medium-sized enterprise confidence loss risk prediction method based on time sequence knowledge graph |
| CN114118779A (en) * | 2021-11-24 | 2022-03-01 | 武汉大学 | KGANN-based enterprise risk identification method facing Internet public sentiment events |
| CN114168757A (en) * | 2022-02-11 | 2022-03-11 | 子长科技(北京)有限公司 | Company event risk prediction method, device, storage medium and electronic equipment |
| US20220101461A1 (en) * | 2020-09-28 | 2022-03-31 | Tata Consultancy Services Limited | Method and system for sequencing asset segments of privacy policy |
| CN114328765A (en) * | 2022-03-04 | 2022-04-12 | 四川大学 | News propagation prediction method and device |
| CN114884727A (en) * | 2022-05-06 | 2022-08-09 | 天津大学 | Internet of things risk positioning method based on dynamic hierarchical knowledge graph |
| CN115018214A (en) * | 2022-08-09 | 2022-09-06 | 北京融信数联科技有限公司 | Enterprise risk analysis and prediction method, system and medium based on cognitive map |
| CN115964504A (en) * | 2021-12-28 | 2023-04-14 | 北方工业大学 | Food safety risk prediction method and system |
| CN116149885A (en) * | 2023-04-20 | 2023-05-23 | 北京神州邦邦技术服务有限公司 | Method and system for predicting risk of flood IT service |
| CN116663751A (en) * | 2023-07-31 | 2023-08-29 | 北京市科学技术研究院 | Three-network industry map construction method and system based on future industry enterprises |
| CN116757709A (en) * | 2023-08-22 | 2023-09-15 | 南京海关工业产品检测中心 | Knowledge graph-based copper concentrate import risk analysis method and system |
| CN117236521A (en) * | 2023-11-10 | 2023-12-15 | 中国联合网络通信集团有限公司 | Industry risk level prediction method, device, equipment and storage medium |
| CN114118779B (en) * | 2021-11-24 | 2024-05-10 | 武汉大学 | KGANN-based enterprise risk identification method for Internet public opinion event |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107066599A (en) * | 2017-04-20 | 2017-08-18 | 北京文因互联科技有限公司 | A kind of similar enterprise of the listed company searching classification method and system of knowledge based storehouse reasoning |
| CN107665252A (en) * | 2017-09-27 | 2018-02-06 | 深圳证券信息有限公司 | A kind of method and device of creation of knowledge collection of illustrative plates |
| CN107783973A (en) * | 2016-08-24 | 2018-03-09 | 慧科讯业有限公司 | The methods, devices and systems being monitored based on domain knowledge spectrum data storehouse to the Internet media event |
-
2018
- 2018-03-29 CN CN201810271489.4A patent/CN108596439A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107783973A (en) * | 2016-08-24 | 2018-03-09 | 慧科讯业有限公司 | The methods, devices and systems being monitored based on domain knowledge spectrum data storehouse to the Internet media event |
| CN107066599A (en) * | 2017-04-20 | 2017-08-18 | 北京文因互联科技有限公司 | A kind of similar enterprise of the listed company searching classification method and system of knowledge based storehouse reasoning |
| CN107665252A (en) * | 2017-09-27 | 2018-02-06 | 深圳证券信息有限公司 | A kind of method and device of creation of knowledge collection of illustrative plates |
Cited By (137)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020073727A1 (en) * | 2018-10-11 | 2020-04-16 | 平安科技（深圳）有限公司 | Risk forecast method, device, computer apparatus, and storage medium |
| CN109558492A (en) * | 2018-10-16 | 2019-04-02 | 中山大学 | A kind of listed company's knowledge mapping construction method and device suitable for event attribution |
| CN109165337A (en) * | 2018-10-17 | 2019-01-08 | 珠海市智图数研信息技术有限公司 | A kind of method and system of knowledge based map construction bidding field association analysis |
| CN109191015A (en) * | 2018-10-17 | 2019-01-11 | 大国创新智能科技(东莞)有限公司 | New high-tech enterprise's identification and robot system based on big data and deep learning |
| CN109359133A (en) * | 2018-10-17 | 2019-02-19 | 大国创新智能科技(东莞)有限公司 | Personalized identification and robot system based on big data and deep learning |
| CN109165337B (en) * | 2018-10-17 | 2021-10-15 | 珠海市智图数研信息技术有限公司 | Method and system for establishing bid and ask field association analysis based on knowledge graph |
| CN109359133B (en) * | 2018-10-17 | 2021-12-07 | 大国创新智能科技(东莞)有限公司 | Personalized identification method based on big data and deep learning and robot system |
| CN109189867A (en) * | 2018-10-23 | 2019-01-11 | 中山大学 | Relationship discovery method, apparatus and storage medium based on Corporate Intellectual map |
| CN109189867B (en) * | 2018-10-23 | 2021-09-17 | 中山大学 | Relation discovery method and device based on company knowledge graph and storage medium |
| CN109472485A (en) * | 2018-11-01 | 2019-03-15 | 成都数联铭品科技有限公司 | Enterprise breaks one's promise Risk of Communication inquiry system and method |
| CN109657837A (en) * | 2018-11-19 | 2019-04-19 | 平安科技（深圳）有限公司 | Default Probability prediction technique, device, computer equipment and storage medium |
| CN109670048A (en) * | 2018-11-19 | 2019-04-23 | 平安科技（深圳）有限公司 | Map construction method, apparatus and computer equipment based on air control management |
| CN109657066A (en) * | 2018-11-19 | 2019-04-19 | 平安科技（深圳）有限公司 | Knowledge mapping construction method, device and computer equipment based on multi-angle of view |
| CN109636584A (en) * | 2018-11-19 | 2019-04-16 | 平安科技（深圳）有限公司 | Default Probability methods of exhibiting, device, computer equipment and storage medium |
| CN109670048B (en) * | 2018-11-19 | 2023-06-23 | 平安科技（深圳）有限公司 | Atlas construction method and apparatus based on wind control management and computer device |
| CN109584045A (en) * | 2018-11-19 | 2019-04-05 | 平安科技（深圳）有限公司 | Accrediting amount configuration method, device, computer equipment and storage medium |
| CN109583738A (en) * | 2018-11-22 | 2019-04-05 | 第创业证券股份有限公司 | A kind of device and method for bond risk control |
| CN111259160A (en) * | 2018-11-30 | 2020-06-09 | 百度在线网络技术（北京）有限公司 | Knowledge graph construction method, device, equipment and storage medium |
| CN111259160B (en) * | 2018-11-30 | 2023-08-29 | 百度在线网络技术（北京）有限公司 | Knowledge graph construction method, device, equipment and storage medium |
| CN109670944A (en) * | 2018-12-19 | 2019-04-23 | 信雅达系统工程股份有限公司 | A kind of rating business credit method and system based on map relational network |
| CN109858740B (en) * | 2018-12-21 | 2022-03-25 | 中化资本有限公司 | Enterprise risk assessment method and device, computer equipment and storage medium |
| CN109858740A (en) * | 2018-12-21 | 2019-06-07 | 中化资本有限公司 | Appraisal procedure, device, computer equipment and the storage medium of business risk |
| CN109858762A (en) * | 2018-12-29 | 2019-06-07 | 重庆誉存大数据科技有限公司 | A kind of business risk prediction technique and device |
| CN109726002A (en) * | 2018-12-30 | 2019-05-07 | 联想(北京)有限公司 | A kind of process flow method of adjustment and device |
| CN109840547A (en) * | 2019-01-04 | 2019-06-04 | 三峡大学 | A kind of identification of intellectual property feature and working method based on Quantum fourier transform |
| CN109828965A (en) * | 2019-01-09 | 2019-05-31 | 北京小乘网络科技有限公司 | A kind of method and electronic equipment of data processing |
| CN109828965B (en) * | 2019-01-09 | 2021-06-15 | 千城数智(北京)网络科技有限公司 | Data processing method and electronic equipment |
| CN109918452A (en) * | 2019-02-14 | 2019-06-21 | 北京明略软件系统有限公司 | A kind of method, apparatus of data processing, computer storage medium and terminal |
| CN110046973A (en) * | 2019-04-17 | 2019-07-23 | 成都市审计局 | It is a kind of that mark string mark detection method is enclosed based on incidence relation big data analysis |
| CN110175239A (en) * | 2019-04-23 | 2019-08-27 | 成都数联铭品科技有限公司 | A kind of construction method and system of knowledge mapping |
| CN110209930A (en) * | 2019-04-30 | 2019-09-06 | 平安科技（深圳）有限公司 | The investee's analysis method and device of knowledge based map |
| CN110263233A (en) * | 2019-05-06 | 2019-09-20 | 平安科技（深圳）有限公司 | Enterprise's public sentiment base construction method, device, computer equipment and storage medium |
| CN110263233B (en) * | 2019-05-06 | 2023-04-07 | 平安科技（深圳）有限公司 | Enterprise public opinion library construction method and device, computer equipment and storage medium |
| CN111949834B (en) * | 2019-05-17 | 2024-04-05 | 嘉兴树融数据科技有限公司 | Site selection method and site selection platform system |
| CN111949834A (en) * | 2019-05-17 | 2020-11-17 | 上海树融数据科技有限公司 | Site selection method and site selection platform |
| CN110197280B (en) * | 2019-05-20 | 2021-08-06 | 中国银行股份有限公司 | Knowledge graph construction method, device and system |
| CN110197280A (en) * | 2019-05-20 | 2019-09-03 | 中国银行股份有限公司 | A kind of knowledge mapping construction method, apparatus and system |
| CN110413858A (en) * | 2019-06-19 | 2019-11-05 | 深圳壹账通智能科技有限公司 | Enterprise's public feelings information querying method, device, computer equipment and storage medium |
| CN110503295A (en) * | 2019-07-05 | 2019-11-26 | 深圳壹账通智能科技有限公司 | Risk analysis method, device, computing terminal and the storage medium of supply chain finance |
| CN110489520B (en) * | 2019-07-08 | 2023-05-16 | 平安科技（深圳）有限公司 | Knowledge graph-based event processing method, device, equipment and storage medium |
| CN110503236A (en) * | 2019-07-08 | 2019-11-26 | 中国平安人寿保险股份有限公司 | Risk Forecast Method, device, equipment and the storage medium of knowledge based map |
| CN110489520A (en) * | 2019-07-08 | 2019-11-22 | 平安科技（深圳）有限公司 | Event-handling method, device, equipment and the storage medium of knowledge based map |
| CN110442731A (en) * | 2019-07-24 | 2019-11-12 | 中电科新型智慧城市研究院有限公司 | A kind of traffic operation system based on traffic administration knowledge mapping |
| CN110363449A (en) * | 2019-07-25 | 2019-10-22 | 中国工商银行股份有限公司 | A kind of Risk Identification Method, apparatus and system |
| CN110597999A (en) * | 2019-08-01 | 2019-12-20 | 湖北工业大学 | Judicial case knowledge graph construction method of dependency syntactic analysis relation extraction model |
| CN110674970A (en) * | 2019-08-19 | 2020-01-10 | 广州荔支网络技术有限公司 | Enterprise legal risk early warning method, device, equipment and readable storage medium |
| CN110781311A (en) * | 2019-09-18 | 2020-02-11 | 上海生腾数据科技有限公司 | Enterprise consistent action calculation system and method |
| CN110765317A (en) * | 2019-09-18 | 2020-02-07 | 上海生腾数据科技有限公司 | Enterprise beneficiary operation system and method |
| CN110781311B (en) * | 2019-09-18 | 2024-02-27 | 上海合合信息科技股份有限公司 | Enterprise-consistent-person operation system and method |
| CN110765317B (en) * | 2019-09-18 | 2024-03-01 | 上海合合信息科技股份有限公司 | Enterprise beneficiary operation system and method |
| CN110659981A (en) * | 2019-09-26 | 2020-01-07 | 北京明略软件系统有限公司 | Enterprise dependency relationship identification method and device and electronic equipment |
| CN111222681A (en) * | 2019-11-05 | 2020-06-02 | 量子数聚（北京）科技有限公司 | Data processing method, device, equipment and storage medium for enterprise bankruptcy risk prediction |
| CN110866057A (en) * | 2019-11-12 | 2020-03-06 | 北京明略软件系统有限公司 | Method and device for realizing data processing, computer storage medium and terminal |
| CN110971674A (en) * | 2019-11-15 | 2020-04-07 | 北京明略软件系统有限公司 | Method, device, computer storage medium and terminal for realizing information processing |
| CN111027832A (en) * | 2019-11-28 | 2020-04-17 | 卓尔智联(武汉)研究院有限公司 | Tax risk determination method, apparatus and storage medium |
| CN110889556A (en) * | 2019-11-28 | 2020-03-17 | 福建亿榕信息技术有限公司 | Enterprise operation risk prediction method and system |
| CN111160841A (en) * | 2019-11-29 | 2020-05-15 | 广东轩辕网络科技股份有限公司 | Organization architecture construction method and device based on knowledge graph |
| CN111061814A (en) * | 2019-12-10 | 2020-04-24 | 北京明略软件系统有限公司 | Modeling analysis method and device, electronic equipment and storage medium |
| CN111105311A (en) * | 2019-12-19 | 2020-05-05 | 第一创业证券股份有限公司 | Dynamic credit rating method and device for bond body |
| CN111046192A (en) * | 2019-12-25 | 2020-04-21 | 中国建设银行股份有限公司 | Identification method and device for bank case-involved account |
| CN111191853A (en) * | 2020-01-06 | 2020-05-22 | 支付宝(杭州)信息技术有限公司 | Risk prediction method and device and risk query method and device |
| CN111191853B (en) * | 2020-01-06 | 2022-07-15 | 支付宝(杭州)信息技术有限公司 | Risk prediction method and device and risk query method and device |
| CN111241300A (en) * | 2020-01-09 | 2020-06-05 | 中信银行股份有限公司 | Public opinion early warning and risk propagation analysis method, system, equipment and storage medium |
| CN111400504B (en) * | 2020-03-12 | 2023-04-07 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying enterprise key people |
| CN111400504A (en) * | 2020-03-12 | 2020-07-10 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying enterprise key people |
| CN111414485A (en) * | 2020-03-17 | 2020-07-14 | 北京恒通慧源大数据技术有限公司 | Enterprise customer association relation map construction method and device, storage and computer |
| CN111325355A (en) * | 2020-03-19 | 2020-06-23 | 中国建设银行股份有限公司 | Method and device for determining actual control persons of enterprises, computer equipment and medium |
| CN111325355B (en) * | 2020-03-19 | 2023-12-19 | 中国建设银行股份有限公司 | Method and device for determining actual control person of enterprise, computer equipment and medium |
| CN111383102A (en) * | 2020-03-27 | 2020-07-07 | 北京明略软件系统有限公司 | Financial credit risk identification method, model construction method and device |
| CN111383102B (en) * | 2020-03-27 | 2023-10-24 | 北京明略软件系统有限公司 | Financial credit risk identification method, model construction method and device |
| CN111583033A (en) * | 2020-04-01 | 2020-08-25 | 北京智信度科技有限公司 | Association analysis method and device based on relation between listed company and stockholder |
| CN111582643A (en) * | 2020-04-08 | 2020-08-25 | 北京明略软件系统有限公司 | Method, device and equipment for collecting enterprise risk information |
| CN111598702A (en) * | 2020-04-14 | 2020-08-28 | 徐佳慧 | Knowledge graph-based method for searching investment risk semantics |
| 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 |
| CN111709235B (en) * | 2020-05-28 | 2023-10-20 | 上海发电设备成套设计研究院有限责任公司 | Text data statistical analysis system and method based on natural language processing |
| CN111709235A (en) * | 2020-05-28 | 2020-09-25 | 上海发电设备成套设计研究院有限责任公司 | Text data statistical analysis system and method based on natural language processing |
| CN113761212B (en) * | 2020-06-01 | 2024-03-08 | 中国石油化工股份有限公司 | Knowledge graph construction method and device based on pipeline integrity |
| CN113761212A (en) * | 2020-06-01 | 2021-12-07 | 中国石油化工股份有限公司 | Knowledge graph construction method and device based on pipeline integrity |
| CN113297044B (en) * | 2020-06-11 | 2024-01-09 | 阿里巴巴集团控股有限公司 | Operation and maintenance risk early warning method and device |
| CN113297044A (en) * | 2020-06-11 | 2021-08-24 | 阿里巴巴集团控股有限公司 | Operation and maintenance risk early warning method and device |
| CN111858903A (en) * | 2020-06-11 | 2020-10-30 | 创新工场(北京)企业管理股份有限公司 | Method and device for negative news early warning |
| CN111767370A (en) * | 2020-06-24 | 2020-10-13 | 北京墨丘科技有限公司 | Associated entity mining method, system and computer readable medium |
| CN111899089A (en) * | 2020-07-01 | 2020-11-06 | 苏宁金融科技(南京)有限公司 | Enterprise risk early warning method and system based on knowledge graph |
| CN112131392A (en) * | 2020-08-01 | 2020-12-25 | 赛飞特工程技术集团有限公司 | Public health epidemic situation early warning method and system based on knowledge graph |
| CN111932131B (en) * | 2020-08-12 | 2024-03-15 | 上海冰鉴信息科技有限公司 | Service data processing method and device |
| CN111932131A (en) * | 2020-08-12 | 2020-11-13 | 上海冰鉴信息科技有限公司 | Service data processing method and device |
| CN111951079B (en) * | 2020-08-14 | 2024-04-02 | 国网数字科技控股有限公司 | Credit rating method and device based on knowledge graph and electronic equipment |
| CN111951079A (en) * | 2020-08-14 | 2020-11-17 | 国网电子商务有限公司 | Credit rating method and device based on knowledge graph and electronic equipment |
| CN111967976B (en) * | 2020-08-19 | 2024-04-16 | 中国银行股份有限公司 | Knowledge graph-based risk enterprise determination method and device |
| CN112015909B (en) * | 2020-08-19 | 2024-04-30 | 普洛斯科技(重庆)有限公司 | Knowledge graph construction method and device, electronic equipment and storage medium |
| CN112015909A (en) * | 2020-08-19 | 2020-12-01 | 普洛斯科技(重庆)有限公司 | Knowledge graph construction method and device, electronic equipment and storage medium |
| CN111967976A (en) * | 2020-08-19 | 2020-11-20 | 中国银行股份有限公司 | Risk enterprise determination method and device based on knowledge graph |
| CN111984797A (en) * | 2020-09-07 | 2020-11-24 | 中国银行股份有限公司 | Customer identity recognition device and method |
| CN112131275A (en) * | 2020-09-23 | 2020-12-25 | 中国科学技术大学智慧城市研究院(芜湖) | Enterprise portrait construction method of holographic city big data model and knowledge graph |
| US11948213B2 (en) * | 2020-09-28 | 2024-04-02 | Tata Consultancy Services Limited | Method and system for sequencing asset segments of privacy policy |
| CN112115278A (en) * | 2020-09-28 | 2020-12-22 | 中国建设银行股份有限公司 | Actual control person relation mining method and device based on knowledge graph |
| US20220101461A1 (en) * | 2020-09-28 | 2022-03-31 | Tata Consultancy Services Limited | Method and system for sequencing asset segments of privacy policy |
| CN112286986A (en) * | 2020-10-14 | 2021-01-29 | 北京乾唐伟业科技股份公司 | Property right analysis management system based on enterprise genealogy |
| CN112214614B (en) * | 2020-10-16 | 2024-02-09 | 民生科技有限责任公司 | Knowledge-graph-based risk propagation path mining method and system |
| CN112214614A (en) * | 2020-10-16 | 2021-01-12 | 民生科技有限责任公司 | Method and system for mining risk propagation path based on knowledge graph |
| CN112836919A (en) * | 2020-11-30 | 2021-05-25 | 广东电网有限责任公司 | Supplier association analysis method and device based on knowledge graph |
| CN112487108A (en) * | 2020-11-30 | 2021-03-12 | 中冶赛迪工程技术股份有限公司 | Enterprise competition analysis method based on knowledge graph |
| CN113051365A (en) * | 2020-12-10 | 2021-06-29 | 深圳证券信息有限公司 | Industrial chain map construction method and related equipment |
| CN112487208A (en) * | 2020-12-14 | 2021-03-12 | 杭州安恒信息技术股份有限公司 | Network security data association analysis method, device, equipment and storage medium |
| CN112487209A (en) * | 2020-12-15 | 2021-03-12 | 厦门市美亚柏科信息股份有限公司 | String mark behavior analysis method based on knowledge graph, terminal equipment and storage medium |
| CN112598302B (en) * | 2020-12-25 | 2024-03-26 | 北京知因智慧科技有限公司 | Enterprise data evaluation method, device and server |
| CN112598302A (en) * | 2020-12-25 | 2021-04-02 | 北京知因智慧科技有限公司 | Enterprise data evaluation method and device and server |
| CN112598507A (en) * | 2020-12-25 | 2021-04-02 | 北京知因智慧科技有限公司 | Excessive credit granting risk prediction system and method based on knowledge graph |
| CN112750028A (en) * | 2020-12-30 | 2021-05-04 | 北京知因智慧科技有限公司 | Risk early warning method and device of event text based on entity extraction |
| CN112800896A (en) * | 2021-01-18 | 2021-05-14 | 北京明略软件系统有限公司 | Security emergency measure self-response method and system based on knowledge graph |
| CN112734270B (en) * | 2021-01-19 | 2024-01-23 | 中国科学院地理科学与资源研究所 | Energy risk conduction measurement method, system and data platform |
| CN112734270A (en) * | 2021-01-19 | 2021-04-30 | 中国科学院地理科学与资源研究所 | Measuring method, system and data platform for energy risk conduction |
| CN112465411A (en) * | 2021-01-27 | 2021-03-09 | 支付宝(杭州)信息技术有限公司 | Risk prediction method, device and equipment |
| CN113159796A (en) * | 2021-03-12 | 2021-07-23 | 国网英大国际控股集团有限公司 | Trade contract verification method and device |
| CN113342904A (en) * | 2021-04-01 | 2021-09-03 | 山东省人工智能研究院 | Enterprise service recommendation method based on enterprise feature propagation |
| CN113362125A (en) * | 2021-04-19 | 2021-09-07 | 浙江锐驰网络科技有限公司 | Information screening system of electric business enterprise incubator |
| CN113361962A (en) * | 2021-06-30 | 2021-09-07 | 支付宝(杭州)信息技术有限公司 | Method and device for identifying enterprise risk based on block chain network |
| CN113344460A (en) * | 2021-07-07 | 2021-09-03 | 上海软中信息技术有限公司 | Intelligent risk prediction and identification system, equipment and device based on big data map calculation |
| CN113392228A (en) * | 2021-08-03 | 2021-09-14 | 广域铭岛数字科技有限公司 | Abnormity prediction and tracing method, system, equipment and medium based on automobile production |
| CN114118779A (en) * | 2021-11-24 | 2022-03-01 | 武汉大学 | KGANN-based enterprise risk identification method facing Internet public sentiment events |
| CN114118779B (en) * | 2021-11-24 | 2024-05-10 | 武汉大学 | KGANN-based enterprise risk identification method for Internet public opinion event |
| CN115964504B (en) * | 2021-12-28 | 2023-06-30 | 北方工业大学 | Food safety risk prediction method and system |
| CN115964504A (en) * | 2021-12-28 | 2023-04-14 | 北方工业大学 | Food safety risk prediction method and system |
| CN114022058A (en) * | 2022-01-06 | 2022-02-08 | 成都晓多科技有限公司 | Small and medium-sized enterprise confidence loss risk prediction method based on time sequence knowledge graph |
| CN114168757A (en) * | 2022-02-11 | 2022-03-11 | 子长科技(北京)有限公司 | Company event risk prediction method, device, storage medium and electronic equipment |
| CN114168757B (en) * | 2022-02-11 | 2022-04-29 | 子长科技(北京)有限公司 | Company event risk prediction method, device, storage medium and electronic equipment |
| CN114328765B (en) * | 2022-03-04 | 2022-05-31 | 四川大学 | News propagation prediction method and device |
| CN114328765A (en) * | 2022-03-04 | 2022-04-12 | 四川大学 | News propagation prediction method and device |
| CN114884727A (en) * | 2022-05-06 | 2022-08-09 | 天津大学 | Internet of things risk positioning method based on dynamic hierarchical knowledge graph |
| CN114884727B (en) * | 2022-05-06 | 2023-02-24 | 天津大学 | Internet of things risk positioning method based on dynamic hierarchical knowledge graph |
| CN115018214B (en) * | 2022-08-09 | 2022-11-25 | 北京融信数联科技有限公司 | Enterprise risk analysis and prediction method, system and medium based on cognitive map |
| CN115018214A (en) * | 2022-08-09 | 2022-09-06 | 北京融信数联科技有限公司 | Enterprise risk analysis and prediction method, system and medium based on cognitive map |
| CN116149885A (en) * | 2023-04-20 | 2023-05-23 | 北京神州邦邦技术服务有限公司 | Method and system for predicting risk of flood IT service |
| CN116663751A (en) * | 2023-07-31 | 2023-08-29 | 北京市科学技术研究院 | Three-network industry map construction method and system based on future industry enterprises |
| CN116757709A (en) * | 2023-08-22 | 2023-09-15 | 南京海关工业产品检测中心 | Knowledge graph-based copper concentrate import risk analysis method and system |
| CN116757709B (en) * | 2023-08-22 | 2023-11-14 | 南京海关工业产品检测中心 | Knowledge graph-based copper concentrate import risk analysis method and system |
| CN117236521A (en) * | 2023-11-10 | 2023-12-15 | 中国联合网络通信集团有限公司 | Industry risk level prediction method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108596439A (en) | A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates | |
| CN109583738A (en) | A kind of device and method for bond risk control | |
| Xiao et al. | Research on risk assessment of Blockchain-driven Supply Chain finance: A systematic review | |
| Zhou | Opportunities and challenges of artificial intelligence in the application of taxation system | |
| Li et al. | Theory and application of artificial intelligence in financial industry | |
| Ke et al. | Public construction project delivery process in Singapore, Beijing, Hong Kong and Sydney | |
| Öztürk et al. | Detection of accounting frauds using the rule-based expert systems within the scope of forensic accounting | |
| Yang | FinTech in Promoting the Development of Green Finance in China against the Background of Big Data and Artificial Intelligence | |
| Xie et al. | A Big Data Technique for Internet Financial Risk Control | |
| Shen et al. | Research on Application of Blockchain in Internationalization of China's Medical Tourism Industry | |
| TW201327453A (en) | Small enterprise financing risk assessment method | |
| Ye et al. | Research on the Application of Blockchain in Agricultural Logistics Park | |
| Zhao | Analysis and strategies of Internet+ taxation risk management of listed companies in the big data era from the organizational psychology perspective | |
| Yang et al. | Analysis of Platform Economic Supervision Mode from the Perspective of Blockchain | |
| Shen | Assessment of financial risk pre-alarm mechanism based on financial ecosystem using BPNN and genetic algorithm | |
| Ozgulbas et al. | Developing road maps for financial decision making by CHAID decision tree: CHAID decision tree application | |
| Wu¹ et al. | Study of the Impact of Chinese Policies and Regulations on Bitcoin | |
| Peng et al. | Intelligent early-warning analysis of operational risks based on grey Kalman filter | |
| Audrine et al. | Environmental Stewardship In Merck Pharmaceutical Industry | |
| Qi et al. | Analysis of the financial risk early warning mechanism of high-tech enterprises under the data analysis technology | |
| Li | Corporate social responsibility in China | |
| Hou | New Financial Regulatory Mode and Regulatory Technology in China | |
| Wang et al. | Quantitative model of financial risk management of forestry enterprises based on nonlinear differential equation | |
| Liu | Risks and Prevention Strategies of Internet Finance in China | |
| Zhang et al. | Performance Evaluation of the Listed Real Estate Companies in China Based on Fuzzy Neural Networks: The Perspective of Stakeholders |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180928 |
|
| RJ01 | Rejection of invention patent application after publication |