Application of Keyword Dynamic Query Software in Relational Database based on Big Data

In order to improve the precision and recall of keywords dynamic query in relational database, a dynamic keyword query algorithm in relational database based on association characteristics data mining and semantic retrieval is proposed, and the query software is designed. In order to improve the query efficiency, reduce the time overhead of graph traverse in query process, the method of path index is used to establish the keywords dynamic query model of reverse search from the keyword node and forward search from potential root node, and extract the related characteristics of the keywords in the relational database. Through the semantic retrieval, the words, nodes, weights and Voronoi path information of the keywords are extracted, and the data graph of the keyword dynamic query is constructed according to the matching degree between the text content and the keyword in the query result, and the database optimization query is realized. Standard Linux development tools are used for query software development and design. The simulation results show that the proposed method can improve the precision and recall of the dynamic keyword query in the relational database, and the matching performance of is better and the real-time performance and accuracy of the database query are enhanced.