Abstract: A novel query expansion algorithm of local feedback is proposed based on item-all-weighted association rule mining，which combines the association rules mining technique with the query expansion.At the same time，a new computing method for weights of expansion terms is given.It makes the weighted value of an expansion term more reasonable.Our algorithm can 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.Experimental results show that our method is better than traditional ones in average precision.

摘要： 针对现有查询扩展存在的缺陷，将完全加权关联规则挖掘技术应用于查询扩展，提出新的查询扩展模型和扩展词权重的计算方法；提出基于完全加权关联规则挖掘的局部反馈查询扩展算法。该算法能自动从初检的前列文档中挖掘与原查询相关的完全加权关联规则，从规则中提取与原查询相关的扩展词，实现查询扩展。实验结果表明，与现有查询扩展算法比较，该查询扩展算法的检索性能得到很好的改善和提高。