Novel Query Expansion Technique using Apriori Algorithm

One problem in query reformulation process is to nd an optimal set of terms to add to the old query. In our TREC experiments this year, we propose to use the association rule discovery (especially apriori algorithm) to nd good candidate terms to enhance the query. These candidate terms are automatically derived from collection, added to the original query to build a new one. Experiments conducted on a subset of TREC collections gives quite promising results. We achieve a 19% improvement with old TREC7 adhoc queries.