关键词: 查询扩展, 伪相关反馈, 语义空间, 观察窗口, 加权, 平均倒数排名

Abstract: Query expansion is a method which adds new words into original query. The method aims at overcoming ambiguity problem and improving description of nature language. Query expansion in concept semantic space can greatly figure out the degree of association among query words and describe the sense of query on the whole. An algorithm proposed is that structures semantic trees for every query word making use of relationships of context and similarity in WordNet dictionary and finds a common root node upwards to structure concept semantic space, filters expansion words in source by co-occurrence information as parameter in order to prevent query drift. It imports dynamic observation windows weighting model into the algorithm, so that enhances the function of co-occurrence information in relevancy between every two words. The experimental results show that the expansion algorithm is much more effective than traditional pseudo-relevance feedback algorithm.

Key words: query expansion, pseudo-relevance feedback, semantic space, observation windows, weighting, Mean Reciprocal Rank（MRR）