关键词: 查询扩展, 本体, Lucene, 语义相似度, 语义检索

Abstract: Semantic similarity is the crucial factor affecting the precision rate and recall rate of semantic information retrieval system. This paper put forward an improved semantic similarity computation model, which was used to quantify the association between concepts , and then the scope of expanded concept set was adjusted by the similarity threshold. In this paper a domain-ontology-based semantic information retrieval system based on the open source full text search engine: Lucene was designed. It extended the original query terms before entering this query expansion terms into Lucene, and used semantic similarity as the key factor of sorting algorithm between searching results. The experimental results show that the semantic similarity of this model is closer to the empirical value of experts, and the precision rate of this system is greatly improved compared with the original Lucene system.

Key words: Query Expansion, Ontology, Lucene, Semantic Similarity, Semantic Search