%0 Journal Article
%T Query Expansion of Local Feedback Based on Improved Apriori Algorithm<br>基于Apriori改进算法的局部反馈查询扩展
%A Chen Yanhong
%A Huang Mingxuan
%A <br>陈燕红
%A 黄名选
%J 现代图书情报技术
%D 2007
%I 
%X 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.
%K Query expansion Apriori algorithm Local feedback Information retrieval<br>查询扩展
%K Apriori算法
%K 局部反馈
%K 信息检索
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=E46382710BF131B2&jid=24AADBCD0D5373C73F37F78D10E2F717&aid=ECB8206CA6A2608DF7AC45D2F231BFAB&yid=A732AF04DDA03BB3&vid=0B39A22176CE99FB&iid=9CF7A0430CBB2DFD&sid=656F8C8401D91023&eid=117F81797AB182FC&journal_id=1003-3513&journal_name=现代图书情报技术&referenced_num=0&reference_num=7