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The Semantic Query System On Population Information Based On Knowledge Graph

Posted on:2020-02-03Degree:MasterType:Thesis
Country:ChinaCandidate:X WangFull Text:PDF
GTID:2428330596982425Subject:Software engineering
Abstract/Summary:PDF Full Text Request
Population is an essential part of social development.The storage and retrieval of population information has become a key issue due to population management.In the process of storing and retrieving population data,the disadvantages of the traditional query mode begin to emerge because users have higher requirements for the accuracy of the query.They hope to query the required data more conveniently.The research and development of new information management system is of great significance.The new semantic query technology can start from the semantics of user query statement to understand the real meaning of user query.While the knowledge graph uses the visualization technology to describe different parts and their relations to form an extensible knowledge network that can present both query results and relevant information to users.The combination of knowledge graph and semantic query can increase the depth and width of query,improve user query experience and query accuracy.The System in this paper combines semantic query and knowledge graph technology to solve the problem of the accuracy of population information query and the diversity of information display.According to the above problems,this paper develops the Semantic Query System on Population Information based on Knowledge Graph.The system combines Neo4 j graph database technology and the Baidu Echarts visualization tool to complete the data graph display,combines Ajax dynamic data loading technology,the LTP word segmentation system and Json data format technology to complete the data semantic query.The system complets click data processing and selective data processing,as well as the data graph display,dynamic data visualization,node click to expand,nodes on map format and other functions.The system combines the dependency parsing technology to analyze the data of common user query statements,extracts the unique pattern matching rules of the system to extract the entity relationship,and summarizes and classifies the synonyms of the extracted results,and finally complets the data semantic query function.The Semantic Query System on Population Information based on Knowledge Graph has finally realized the system demand and runs well after testing.
Keywords/Search Tags:Knowledge Map, Semantic Search, Entity Relationship Extraction, Neo4j
PDF Full Text Request
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