基于關聯規則與聚類算法的查詢擴展算法:針對信息檢索中查詢關鍵詞與文檔用詞不匹配的問題，提出一種基于關聯規則與聚類算法的查詢擴展算法。該算法在第1 階段對
初始查詢結果的前N 篇文檔進行關聯規則挖掘，提取含有初始查詢項的關聯規則構建規則庫，并從中選取與查詢用詞關聯度最大的K 個詞
作為擴展詞，與初始查詢組成新查詢后再次查詢，在第2 階段將新查詢結果進行聚類分析并計算結果中每篇文檔的最終相關度，按最終相
關度大小重新排序。實驗結果表明，該算法比單獨使用關聯規則算法或是單獨使用聚類算法均有更優的檢索性能。
關鍵詞：信息檢索；查詢擴展；關聯規則；聚類算法

【Abstract】To solve the problem of word-mismatch between query key words and document words, this paper puts forward a query expansion
algorithm based on the combination of association rules and cluster algorithm. At the first stage it uses association rules on the front N documents in
the first query result, and gets the rules that have query item to build the rules base, and gets the K words that have the most similarity with the query
words to form a new query and query again to get a new result. At the second stage it uses cluster algorithm on the new result and compute every
document’s final similarity to get a document re-ranking. Experimental result shows this query expansion algorithm outperforms both the association
rules and the cluster algorithm.
【Key words】information retrieval; query expansion; association rules; cluster algorithm