A search log sparseness oriented query expansion method

Query expansion methods based on search logs could improve the quality of search results to some extends. But when the search logs are sparse, this kind of query expansion methods will have poor quality of search results and are unable to meet the user´s search request, etc. This paper presents the search log sparseness oriented query extension method. By introducing the determination rule of data sparseness, this method selects expansion terms with high performance from the expansion terms given by local context based methods to go over the disadvantages of search log based method with sparse data sets, providing expansion terms with higher quality for the user´s initial queries. The experimental results show that, this method improves the accuracy and recall of the search results, improving the quality of search results.