Text Information Retrieval Based on Concept Semantic Similarity

摘要：

In this paper, an improved method of calculating ontology semantic similarity is proposed to enhance the information retrieval recall and precision. To filter out the document which have smaller related degree with original query, the scores of search results document is re-calculated by use of ontology semantic similarity. A new definition of the iterative query expansion parameters is put forward which can reduce the number of expansion and further improve the efficiency of the query. The use of open source tools for text semantic retrieval test, i.e., Jena and Lucene, has verified the feasibility and effectiveness of the proposed method.

关键词： Information Retrieval Ontology Semantic Similarity Query Expansion Document Scores

作者: Gang Lv Cheng Zheng Li Zhang

作者单位: Key Laboratory of Network and Intelligent Information Processing, Hefei University, Hefei, China Educational Department Key Laboratory of Intelligent Computing & Signal Processing, Anhui University, Hefei, China

会议类型: 国际会议

会议名称: Fifth International Conference on Semantics,Knowledge and Grid(第五届语义、知识与网格国际会议 SKG 2009)

会议地点: 珠海

会议语种:英文

页码: 356-360

在线出版日期: 2009-10-12（万方平台首次上网日期，不代表论文的发表时间）