In the field of information retrieval, the match between resources and query words determines retrieval quality. The search results using current query methods exist too much irrelevant information and cannot satisfy customer needs. Considering the defects of traditional information retrieval and current feature of semantic query expansion, an improved ontology-based semantic query expansion method based on the analysis of various query expansion algorithms and related research has been proposed. The method constructs and expands the user search tree according to the query message basing on the ontology model and concept similarity computation. The experiment results show that the method can get better query results comparing to other query expansion method.