Abstract：For the question that query expansion words extracted by query expansion method based on search log are seriously influenced by the popularity of the words,which leads to a period covered with limited knowledge,and cause the missing part of the search results to satisfy users′ information needs,this paper studies a combined query expansion method for balanced epidemic and similarity.On one hand,this method clusters search logs,matching search queries and generate log based query expansions.Meanwhile,this method generates user query expansion word classification set using ontologies.Based on the classification set,the semantic coverage of the log based expansion set is calculated,and for expansion sets with low semantic coverage,ontology based expansion results are merged into log based expansion set using theory of evidence.The experimental results show that the method improves the retrieval performance of search engine,and it can meet the needs of the users to search information,which is able to improve the satisfaction of users.
2016, Vol. 37 
