Item-all-weighted association rules mining and its applications in query expansion
完全加权关联规则挖掘及其在查询扩展中的应用

In order to combine the association rules mining technique with the query expansion, a new algorithm of item-all-weighted association rules mining for query expansion was presented based on multiplicate pruning. This method could tremendously enhance the mining efficiency. And a novel query expansion algorithm of local feedback was proposed based on item-all-weighted association rules mining. The algorithm could automatically mine those all-weighted association rules related to original query in the top-ranked retrieved documents, to construct an association rules-based database, and extract expansion terms related to original query from the database for query expansion. At the same time, a new computing method for weights of expansion terms was given. It makes the weighted value of an expansion term more reasonable. Experimental results show that our method is better than traditional ones in average precision.