摘要
提出面向查询扩展的Apriori改进算法,采用三种剪枝策略,极大提高挖掘效率;针对现有查询扩展存在的缺陷,提出基于Apriori改进算法的局部反馈查询扩展算法,该算法用Apriori改进算法对前列初检文档进行词间关联规则挖掘,提取含有原查询词的词间关联规则,构造规则库,从库中提取扩展词,实现查询扩展。实验结果表明该算法能够提高信息检索性能,与现有算法比较,在相同查全率水平级下其平均查准率有了明显提高。
An improved Apriori algorithm for query expansion is presented based on the thrice pruning strategy, This method can tremendously enhance the mining efficiency. After studying the limitations of existing query expansion, a novel query expansion algorithm of local feedback is proposed based on the improved Apriori algorithm, This algorithm can automatically mine those association rules related to original query in the top - rank retrieved documents using the improved Apriori algorithm, 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.
出处
《现代图书情报技术》
CSSCI
北大核心
2007年第9期84-87,共4页
New Technology of Library and Information Service
作者简介
E-mail：cyh8390@sina.com
