The Research And Implementation Of Domain Knowledge Graph Construction Platform Based On Web

The domain knowledge graph is a semantic network constructed by extracting the relationship between entities and entities from resources in a specific domain which has strong domain specificity and professionalism.The domain knowledge graph construction platform is a semi-automated tool for experts to build a highly targeted and accurate domain knowledge graph based on massive data.It should have the following three characteristics:The construction process is complete which covers the processes of data acquisition,information extraction,knowledge fusion,graph construction,knowledge update,etc.Processing massive data is inseparable from the support of big data platform,so the platform needs to have big data processing capability;Because the domain knowledge graph has strong domain specificity and professionalism,Excessive using thresholds are not conducive to the supervision and intervention of domain experts during the construction process.However,in the current public domain graph construction platfonn,there are many challenges in the definition of knowledge graph construction process,lack of support for big data related technologies and poor operability for domain experts.Most of the current domain knowledge graph construction platforms are incompletely defined for the construction process,and emphasize some aspects of the knowledge graph construction process in isolation,such as data collection,knowledge representation,graph visualization,which is unable to support the full life cycle knowledge graph construction;Most of the current domain knowledge graph construction platforms rarely mention the support of big data related technologies in the process of knowledge graph construction,which lack of guiding value in the actual construction process of knowledge graph.In the process of constructing the domain knowledge graph based on the platform,in order to ensure the accuracy,the supervision and intervention of the domain experts are often required,but the natural language processing technology and the big data processing flow are difficult for the domain experts to understand,the technical implementation threshold is high which imposes certain restrictions on the popularity and application of the domain knowledge graph.In view of the above problems and challenges,this paper focuses on the research and analysis of the domain knowledge graph construction technology and process,and completes the design and implementation of the Web-based domain knowledge graph construction platform.The main research contents are as follows:1)Design and implement a Web-based domain knowledge graph construction platform which provides domain experts with a knowledge graph construction service with complete definition process,big data processing capability and easy to use.In the development process,in order to realize the custom orchestration of the knowledge graph construction process,a visual Web service composition orchestration technology is proposed and implemented.In addition,the DSACC(Dynamic Scheduling Algorithm for Concurrent Connections)algorithm is proposed and implemented to solve the problem of front-end performance optimization of big data rendering in the process of knowledge graph visualization.2)A method based on big data driven domain knowledge graph is proposed and implemented.After completing the first part,this paper further summarizes the knowledge graph construction process,aiming to study the big data related technologies in the process of knowledge graph construction.The support of related technologies provides a certain reference value for the actual construction process of the knowledge graph.3)Using the Web-based domain knowledge graph construction platform as a tool,and based on a big data-driven domain knowledge graph construction method,complete the artificial intelligence industry knowledge graph construction.The graph covers 3,458 artificial intelligence enterprises,1,087 technology labels in the field of artificial intelligence,16,324 patent data,and 69,866 related news,which fully demonstrates the development status of the artificial intelligence industry and further proves the effectiveness and integrity of the platform and method.