Construction Of Knowledge Graph And Realization Of Visualization System For Winter Olympic Games Based On Knowledge Representation Learning

In recent years,with the development of big data and artificial intelligence technology,we have gradually entered the intelligent era from the digital and information age,and the Internet has become the largest platform for obtaining multi-source information.Knowledge graph breaks the limitations of traditional data storage media,integrates multi-source heterogeneous data on the Internet through entities and relationships in a structured way to form a unified semantic network structure,providing underlying data and technical support for intelligent question answering and intelligent search.As for the network data in the field of Winter Olympic Games,there are some problems,such as the serious fragmentation of knowledge and the simplification of knowledge display.Various sources of data are independent and have different structures,which can not realize the exchange and sharing of data,resulting in the lack of intelligent service means and other problems.Therefore,in the face of massive data of the Winter Olympic Games,an effective data management method is urgently needed to integrate data,so as to provide more intelligent service means.The emergence of knowledge graph provides a new way to solve this problem.Knowledge graph can effectively associate semantic network data and realize the integration and utilization of multi-source heterogeneous data.At present,there is a lack of research on Knowledge graph in the field of Winter Olympic Games.Therefore,based on the background of Winter Olympic Games,this thesis studies and constructs the knowledge graph of Winter Olympic Games and visualizes it.This thesis focuses on the construction technology and visualization technology of Winter Olympic domain knowledge graph,constructed the Winter Olympic knowledge map based on knowledge representation learning and makes visualization.In the process of implementation,the main work of this thesis includes the following aspects:(1)This thesis analyzed the characteristics of the Internet data related to the Winter Olympic Games,uses the distributed web crawler technology to crawl the data related to the Winter Olympics from the Internet,and extracts the knowledge from the structured triplet.(2)The representation learning algorithm based on relation path is studied.This thesis improves the representation learning model Trans D,proposes the PTrans DW model,uses Trans D to model the direct relationship,uses path modeling to obtain the implicit relationship between multi-step relationship paths,in addition,introduces the weight matrix of relation type is used to improve the representation ability of the model.Finally,the performance of the model is verified on the data set.(3)The construction of Winter Olympics knowledge graph and the realization of visualization system.Through knowledge extraction,knowledge fusion and knowledge storage,a knowledge graph based on Winter Olympics domain is constructed.It adopts Python language,Neo4 j graph database,Python based Web framework Flask and Node.js +Vue front-end technology finally realized the construction and visualization system of Winter Olympics knowledge graph based on knowledge representation learning.