Enterprise Social Graph Query For Enterprise Knowledge Graph Application

Since the theoretical method of knowledge graph was introduced to our country,it has grown rapidly in the field of social sciences.Recently,the application of knowledge graphs has been widely used in the fields of education and big data.The construction of enterprise social graph is aimed at the effective organization and application of enterprise knowledge data resources in the big data environment,and realizes that data becomes productivity.The enterprise social graph query system of this paper has been realized by learning the basic theoretical knowledge related to the knowledge graph,viewing a large number of related technologies of the knowledge graph,and viewing the projects related to the knowledge graph of the predecessors.This paper is based on the companies that purchase the company's products,and provides a network diagram with the target product company as the core and spread to the outer layer in accordance with the needs of users,data types,application scenarios,etc.The enterprise social graph query visually displays the related data information between enterprises in a three-dimensional manner,which is used to measure the closeness of contacts between enterprises and help target enterprises to find potential customers.At the same time,according to customer needs,data types,data volume,application scenarios,etc.the target company's products are improved to achieve a win-win situation and bring greater benefits to the company.The enterprise social graph query system implemented in this paper contains four steps.The first step is to build the Schema.Determine which entities,relationships,constraints,and attributes on entities and relationships are based on our own business needs and business data.The second step is to select different knowledge acquisition methods based on the data and data sources currently owned by the enterprise and sort out and import knowledge.The third step is to develop more functions based on the basic data of the enterprise social graph and comprehensively use knowledge data fusion,knowledge logical reasoning,semantic retrieval and other technical theories to achieve a qualitative improvement.The fourth step is to design different knowledge representations and presentation methods according to the business scenarios of the enterprise?For example,data visualization: display enterprise-related data in the form of graphs,semantic search: users can input content and return the graph of corresponding content,logical reasoning: through existing knowledge logic to infer unknown knowledge through relationship analysis,etc.In the end,this paper uses data as the means of production for data detection,data analysis,data mining,and data empowerment.Combined with the knowledge characteristics of the enterprise social domain,the knowledge is abstracted and modeled,thereby constructing the enterprise social domain ontology.The neo4 j graph database was selected for knowledge preservation and graph formation.In the end,the enterprise social graph query system constructed in this paper contains 39,565 entities and 20,186 relationship information.The paper is innovative in the following aspects.The first is to apply knowledge graphs to enterprise management to improve the query display of corporate social relationships.The second is to use the enterprise's existing data to reason out potential customer information,and effectively improve the efficiency of the enterprise's work.The enterprise social graph query system helps enterprise management members to grasp the enterprise's product information,industry dynamic information,competitive product dynamic information,and precise positioning of potential customers.And realizing that data becomes productive in a big data environment.