A context-dependent approach to query expansion in information retrieval

In practical applications of information retrieval, as the search engine, the query user submitted contains only several keywords usually. This will cause unmatched issue between words of relevant documents and user's query and have more serious negative effects on the performance of information retrieval. On the basis of analyzing of process of producing query, this paper puts forward a new method of query expansion on the basis of context and global information. The approach extracts related terms between documents and query through context and global information. The expansion terms are selected according to their relation to the whole query. At the same time, the position information between terms are considered. The experiment result on TREC data collection shows the method proposed by the paper, has 11-29% of the improvement all the time more than the language modeling method without expanding. Compared to the popular approach of query expansion, pseudo feedback, the method proposed in this paper has the competed average precision. 1553-9105/