CN112836919A - Supplier association analysis method and device based on knowledge graph - Google Patents
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Abstract
The invention relates to the technical field of supplier management, and provides a supplier association analysis method and device based on a knowledge graph, which are used for solving the problem of fuzzy association relationship among suppliers. The invention provides a supplier association analysis method based on a knowledge graph, which comprises the following steps: acquiring supplier information, wherein the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information; extracting enterprise incidence relation information from enterprise related public information; constructing a knowledge base, wherein the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise association relation knowledge base; and associating a plurality of suppliers supplying a target with the purchasing target, and then associating enterprises associated with the suppliers to construct a knowledge graph based on the purchasing target supplier enterprises. The efficiency of tender purchasing can be improved, and the purchasing risk can also be reduced.
Description
Technical Field
The invention relates to the technical field of supplier management, in particular to a supplier association analysis method and device based on a knowledge graph.
Background
According to the overall requirements of 'notice on the analysis table of advanced bidding management reform tasks of the issuing company' of the file No. 2019 of the radio and television enterprise '8', intelligent recommendation, risk analysis and intelligent early warning are realized by utilizing the technologies of supplier data reconstruction and the like, the high compliance efficiency of the selected suppliers for bidding purchase is ensured, and the risks of performing and auditing caused by the self risks of the suppliers in the purchasing process are prevented.
The association relationship of the suppliers has great influence on the effect of bid inviting purchase, and the visualized association relationship of the suppliers can provide basis for decision in the bid inviting purchase process. But now lacks software to produce such visual associations.
Disclosure of Invention
The invention solves the technical problem of fuzzy association relationship between suppliers and provides a supplier association analysis method based on a knowledge graph.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
the supplier association analysis method based on the knowledge graph comprises the following steps:
acquiring supplier information, wherein the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information;
extracting enterprise incidence relation information from enterprise related public information;
constructing a knowledge base, wherein the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise association relation knowledge base;
and associating a plurality of suppliers supplying a target with the purchasing target, and then associating enterprises associated with the suppliers to construct a knowledge graph based on the purchasing target supplier enterprises.
The association relation of the suppliers is presented in a knowledge map mode, and particularly, the intuitive and convenient reference is provided for selecting the suppliers for bid inviting purchase on the basis of purchasing targets.
The efficiency of tender purchasing can be improved, and the purchasing risk can also be reduced.
Preferably, the acquisition channel of the enterprise-related public information comprises third-party enterprise inquiry tools, provider website acquisition and portal website acquisition.
Preferably, the method for acquiring the enterprise association relationship from the enterprise-related public information includes:
acquiring a text of related public information;
splitting the text of the related public information to obtain a clause set containing at least one clause;
determining clauses containing preset associated keywords from the clause set, determining sentence pattern types of the clauses, adjusting the sentence patterns of the clauses into preset sentence patterns, and extracting enterprise association relation information from the adjusted clauses. The incidence relation of some enterprises is difficult to find, indirect acquisition through network reports is needed, and some hidden incidence relations can be effectively extracted from the network reports through a natural language processing technology.
Preferably, if the sentence pattern of the clause including the preset associated keyword is an elliptical sentence, completing the subject or object of the elliptical sentence, and the completing method includes:
and obtaining the previous sentence and the next sentence of the clause containing the preset associated keywords, if the obtained sentences have subjects or objects, performing CRF syntactic analysis, obtaining a main body of the clause where the preset associated keywords are located, and if the main body is the same as the name of the supplier, storing the enterprise association relationship. Some sentences in the network reports are omitted sentences, and the association is difficult to judge, so that the omitted sentences need to be completed.
Preferably, the completion method further comprises:
acquiring a previous sentence and a next sentence of a clause containing preset associated keywords;
if the subject or the object does not exist in the obtained sentence, the sentence is obtained again along the obtaining direction of the sentence until a sentence containing the subject or the object is obtained.
A knowledge-graph-based supplier association analysis apparatus, comprising:
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module acquires supplier information, and the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information;
the incidence relation extraction module extracts enterprise incidence relation information from enterprise related public information;
the knowledge base module is used for constructing a knowledge base, and the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise incidence relation knowledge base;
the knowledge graph building module is used for associating a plurality of suppliers supplying a target with the purchasing target and then associating enterprises associated with the suppliers to build a knowledge graph of the supplier enterprises based on the purchasing target.
Preferably, the information acquisition module acquires enterprise-related public information from a third-party enterprise inquiry tool, a provider website and a portal website.
Preferably, the association relation extracting module includes:
the text acquisition module acquires a text of the relevant public information;
the splitting module splits the text of the related public information to obtain a clause set containing at least one clause;
and the extraction module is used for determining the clauses containing the preset associated keywords from the clause set, determining the sentence pattern type of the clauses, adjusting the sentence pattern of the clauses into the preset sentence pattern, and extracting the enterprise association relation information from the adjusted clauses.
Preferably, the association relation extracting module further includes:
an adjacent sentence acquisition module that acquires a previous sentence and a next sentence of a sentence including a preset associated keyword;
if the obtained sentence has a subject or an object, a first completion module completes the subject or the object of the omitted sentence, performs CRF syntactic analysis, obtains a subject of a clause where the preset associated keyword is located, and if the subject is the same as the name of the supplier, stores the enterprise association relationship.
Preferably, the association relation extracting module further includes:
if the obtained sentence does not have the subject or the object, the second completion module obtains the sentence again along the obtaining direction of the sentence until the sentence containing the subject or the object is obtained, and sends the obtained sentence containing the subject or the object to the first completion module.
Compared with the prior art, the invention has the beneficial effects that: the efficiency of tender purchasing can be improved, and the purchasing risk can also be reduced. The association relation of the suppliers is presented in a knowledge map mode, and particularly, the intuitive and convenient reference is provided for selecting the suppliers for bid inviting purchase on the basis of purchasing targets.
Drawings
FIG. 1 is a schematic diagram of a knowledge-graph based supplier association analysis method.
FIG. 2 is a schematic diagram of a knowledge-graph.
Fig. 3 is a schematic diagram of a knowledge-graph based supplier correlation analysis apparatus.
Detailed Description
The following examples are further illustrative of the present invention and are not intended to be limiting thereof.
The supplier association analysis method based on the knowledge graph comprises the following steps of:
acquiring supplier information, wherein the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information;
extracting enterprise incidence relation information from enterprise related public information;
constructing a knowledge base, wherein the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise association relation knowledge base;
and associating a plurality of suppliers supplying a target with the purchasing target, and then associating enterprises associated with the suppliers to construct a knowledge graph based on the purchasing target supplier enterprises.
The association relation of the suppliers is presented in a knowledge map mode, and particularly, the intuitive and convenient reference is provided for selecting the suppliers for bid inviting purchase on the basis of purchasing targets.
The efficiency of tender purchasing can be improved, and the purchasing risk can also be reduced.
In some embodiments of the present application, the structure of the knowledge-graph may be represented as: the procurement target is connected to a plurality of suppliers, and the suppliers are connected to the enterprises associated with the suppliers. For example, both supplier A and supplier B may provide or have provided the target of purchase T; supplier A is the stockholder of Enterprise C, which can provide the necessary accessories to purchase target T; vendor B is the full subsidy of Enterprise D. The corresponding map structure is that the purchasing target T is connected with a supplier A and a supplier B, the supplier A is connected with an enterprise C, and the relationship between the supplier A and the enterprise C is as follows: supplier A is the stockholder of C, supplier B is connected with enterprise D, and the relationship between supplier B and enterprise D is as follows: supplier B is a full subsidy sub-company for Enterprise D.
In some embodiments of the present application, the acquisition channel of the enterprise-related public information includes third-party enterprise query tool, provider website acquisition, and portal website acquisition.
In some embodiments of the present application, a method for obtaining an enterprise association relationship from enterprise-related public information includes:
acquiring a text of related public information;
splitting the text of the related public information to obtain a clause set containing at least one clause;
determining clauses containing preset associated keywords from the clause set, determining sentence pattern types of the clauses, adjusting the sentence patterns of the clauses into preset sentence patterns, and extracting enterprise association relation information from the adjusted clauses.
The incidence relation of some enterprises is difficult to find, indirect acquisition through network reports is needed, and some hidden incidence relations can be effectively extracted from the network reports through a natural language processing technology.
In some embodiments of the present application, text of relevant public information is obtained by crawler technology;
splitting the text of the related public information to obtain a clause set containing at least one clause; the splitting rule can take punctuation marks as splitting points or preset keywords;
determining clauses containing preset associated keywords from the clause set, determining sentence pattern types of the clauses, adjusting the sentence patterns of the clauses into preset sentence patterns, and extracting enterprise association relation information from the adjusted clauses; in this embodiment, the preset sentence is a "related keyword" of a company that is a supplier. The associated keywords are the company of stock control, the company of full capital, the great stockholder, the actual person of control, the final beneficiary, etc.
In some embodiments of the present application, if the sentence pattern of the clause including the preset associated keyword is an elliptical sentence, completing the subject or object of the elliptical sentence, and the completing method includes:
and obtaining the previous sentence and the next sentence of the clause containing the preset associated keywords, if the obtained sentences have subjects or objects, performing CRF syntactic analysis, obtaining a main body of the clause where the preset associated keywords are located, and if the main body is the same as the name of the supplier, storing the enterprise association relationship.
Some sentences in the network reports are omitted sentences, and the association is difficult to judge, so that the omitted sentences need to be completed.
The conversion of the omitted sentence into the predetermined sentence pattern must be supplemented with the omitted subject or object, so that the subject is searched for in the adjacent sentence, in the present embodiment, the noun or the noun of "__ company" is searched for in the adjacent sentence as the subject or object of the omitted sentence.
In some embodiments of the present application, the sentence where the preset associated keyword is located is "the stockholder of enterprise E", the subject is omitted, and the last sentence "supplier F invests 100 ten thousand" and the next sentence "complement the production clipboard" of the clause containing the preset associated keyword are obtained. In the last sentence, a noun supplier F exists, and through the syntactic analysis of CRF, the main phrase "supplier F" can be obtained, and the final sentence is that "supplier F is the stock holder of enterprise E".
In some embodiments of the present application, the completion method further comprises:
acquiring a previous sentence and a next sentence of a clause containing preset associated keywords;
if the subject or the object does not exist in the obtained sentence, the sentence is obtained again along the obtaining direction of the sentence until a sentence containing the subject or the object is obtained.
The supplier association analysis device based on the knowledge graph comprises, in some embodiments of the application:
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module acquires supplier information, and the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information;
the incidence relation extraction module extracts enterprise incidence relation information from enterprise related public information;
the knowledge base module is used for constructing a knowledge base, and the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise incidence relation knowledge base;
the knowledge graph building module is used for associating a plurality of suppliers supplying a target with the purchasing target and then associating enterprises associated with the suppliers to build a knowledge graph of the supplier enterprises based on the purchasing target.
In some embodiments of the present application, the information obtaining module obtains the enterprise-related public information from a third-party enterprise query tool, a provider website, or a portal website.
In some embodiments of the present application, the association extraction module includes:
the text acquisition module acquires a text of the relevant public information;
the splitting module splits the text of the related public information to obtain a clause set containing at least one clause;
and the extraction module is used for determining the clauses containing the preset associated keywords from the clause set, determining the sentence pattern type of the clauses, adjusting the sentence pattern of the clauses into the preset sentence pattern, and extracting the enterprise association relation information from the adjusted clauses.
In some embodiments of the present application, the association relation extracting module further includes:
an adjacent sentence acquisition module that acquires a previous sentence and a next sentence of a sentence including a preset associated keyword;
if the obtained sentence has a subject or an object, a first completion module completes the subject or the object of the omitted sentence, performs CRF syntactic analysis, obtains a subject of a clause where the preset associated keyword is located, and if the subject is the same as the name of the supplier, stores the enterprise association relationship.
In some embodiments of the present application, the association relation extracting module further includes:
if the obtained sentence does not have the subject or the object, the second completion module obtains the sentence again along the obtaining direction of the sentence until the sentence containing the subject or the object is obtained, and sends the obtained sentence containing the subject or the object to the first completion module.
The above detailed description is specific to possible embodiments of the present invention, and the above embodiments are not intended to limit the scope of the present invention, and all equivalent implementations or modifications that do not depart from the scope of the present invention should be included in the present claims.
Claims (10)
1. The supplier association analysis method based on the knowledge graph is characterized by comprising the following steps:
acquiring supplier information, wherein the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information;
extracting enterprise incidence relation information from enterprise related public information;
constructing a knowledge base, wherein the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise association relation knowledge base;
and associating a plurality of suppliers supplying a target with the purchasing target, and then associating enterprises associated with the suppliers to construct a knowledge graph based on the purchasing target supplier enterprises.
2. The method of claim 1, wherein the channels for obtaining enterprise-related public information comprise third-party enterprise query tools, provider website obtaining, and portal website obtaining.
3. The method of claim 2, wherein the method of obtaining business association relationships from business related public information comprises:
acquiring a text of related public information;
splitting the text of the related public information to obtain a clause set containing at least one clause;
determining clauses containing preset associated keywords from the clause set, determining sentence pattern types of the clauses, adjusting the sentence patterns of the clauses into preset sentence patterns, and extracting enterprise association relation information from the adjusted clauses.
4. The method of claim 3, wherein if the sentence pattern of the clause including the predetermined associated keyword is an elliptical sentence, completing the subject or object of the elliptical sentence, the completing method comprises:
and obtaining the previous sentence and the next sentence of the clause containing the preset associated keywords, if the obtained sentences have subjects or objects, performing CRF syntactic analysis, obtaining a main body of the clause where the preset associated keywords are located, and if the main body is the same as the name of the supplier, storing the enterprise association relationship.
5. The knowledgegraph-based vendor correlation analysis method of claim 4, wherein the completion method further comprises:
acquiring a previous sentence and a next sentence of a clause containing preset associated keywords;
if the subject or the object does not exist in the obtained sentence, the sentence is obtained again along the obtaining direction of the sentence until a sentence containing the subject or the object is obtained.
6. The supplier association analysis method device based on the knowledge graph is characterized by comprising the following steps:
the system comprises an information acquisition module, a data processing module and a data processing module, wherein the information acquisition module acquires supplier information, and the supplier information comprises enterprise basic information, purchasing target information and enterprise related public information;
the incidence relation extraction module extracts enterprise incidence relation information from enterprise related public information;
the knowledge base module is used for constructing a knowledge base, and the knowledge base comprises an enterprise basic information knowledge base, a purchasing target information knowledge base and an enterprise incidence relation knowledge base;
the knowledge graph building module is used for associating a plurality of suppliers supplying a target with the purchasing target and then associating enterprises associated with the suppliers to build a knowledge graph of the supplier enterprises based on the purchasing target.
7. The apparatus for vendor association analysis based on knowledge-graph as claimed in claim 6, wherein the information obtaining module obtains the enterprise-related public information from a third-party enterprise query tool, a vendor website, and a portal website.
8. The knowledgegraph-based vendor association analysis device of claim 6, wherein the association extraction module comprises:
the text acquisition module acquires a text of the relevant public information;
the splitting module splits the text of the related public information to obtain a clause set containing at least one clause;
and the extraction module is used for determining the clauses containing the preset associated keywords from the clause set, determining the sentence pattern type of the clauses, adjusting the sentence pattern of the clauses into the preset sentence pattern, and extracting the enterprise association relation information from the adjusted clauses.
9. The knowledge-graph-based supplier association analysis apparatus of claim 8, wherein the association relation extraction module further comprises:
an adjacent sentence acquisition module that acquires a previous sentence and a next sentence of a sentence including a preset associated keyword;
if the obtained sentence has a subject or an object, a first completion module completes the subject or the object of the omitted sentence, performs CRF syntactic analysis, obtains a subject of a clause where the preset associated keyword is located, and if the subject is the same as the name of the supplier, stores the enterprise association relationship.
10. The knowledge-graph-based vendor association analysis device of claim 9, wherein the association relation extraction module further comprises:
if the obtained sentence does not have the subject or the object, the second completion module obtains the sentence again along the obtaining direction of the sentence until the sentence containing the subject or the object is obtained, and sends the obtained sentence containing the subject or the object to the first completion module.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114862350A (en) * | 2022-05-05 | 2022-08-05 | 阿里巴巴（中国）有限公司 | Data processing method and device in task distribution process and electronic equipment |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107247707A (en) * | 2017-06-27 | 2017-10-13 | 北京神州泰岳软件股份有限公司 | Enterprise's incidence relation information extracting method and device based on completion strategy |
| CN107392436A (en) * | 2017-06-27 | 2017-11-24 | 北京神州泰岳软件股份有限公司 | A kind of method and apparatus for extracting enterprise's incidence relation information |
| CN107392433A (en) * | 2017-06-27 | 2017-11-24 | 北京神州泰岳软件股份有限公司 | A kind of method and apparatus for extracting enterprise's incidence relation information |
| CN108596439A (en) * | 2018-03-29 | 2018-09-28 | 北京中兴通网络科技股份有限公司 | A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates |
| CN108959575A (en) * | 2018-07-06 | 2018-12-07 | 北京神州泰岳软件股份有限公司 | A kind of enterprise's incidence relation information mining method and device |
| 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 |
| CN110347894A (en) * | 2019-05-31 | 2019-10-18 | 平安科技（深圳）有限公司 | Knowledge mapping processing method, device, computer equipment and storage medium based on crawler |
| WO2020007224A1 (en) * | 2018-07-06 | 2020-01-09 | 中兴通讯股份有限公司 | Knowledge graph construction and smart response method and apparatus, device, and storage medium |
-
2020
- 2020-11-30 CN CN202011371779.XA patent/CN112836919A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107247707A (en) * | 2017-06-27 | 2017-10-13 | 北京神州泰岳软件股份有限公司 | Enterprise's incidence relation information extracting method and device based on completion strategy |
| CN107392436A (en) * | 2017-06-27 | 2017-11-24 | 北京神州泰岳软件股份有限公司 | A kind of method and apparatus for extracting enterprise's incidence relation information |
| CN107392433A (en) * | 2017-06-27 | 2017-11-24 | 北京神州泰岳软件股份有限公司 | A kind of method and apparatus for extracting enterprise's incidence relation information |
| CN108596439A (en) * | 2018-03-29 | 2018-09-28 | 北京中兴通网络科技股份有限公司 | A kind of the business risk prediction technique and system of knowledge based collection of illustrative plates |
| CN108959575A (en) * | 2018-07-06 | 2018-12-07 | 北京神州泰岳软件股份有限公司 | A kind of enterprise's incidence relation information mining method and device |
| WO2020007224A1 (en) * | 2018-07-06 | 2020-01-09 | 中兴通讯股份有限公司 | Knowledge graph construction and smart response method and apparatus, device, and storage medium |
| 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 |
| CN110347894A (en) * | 2019-05-31 | 2019-10-18 | 平安科技（深圳）有限公司 | Knowledge mapping processing method, device, computer equipment and storage medium based on crawler |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114862350A (en) * | 2022-05-05 | 2022-08-05 | 阿里巴巴（中国）有限公司 | Data processing method and device in task distribution process and electronic equipment |
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Application publication date: 20210525 |