Mining web documents to find additional query terms using fuzzy association rules

In this paper, we present an application of association rules to query refinement. Starting from an initial set of documents retrieved from the web, text transactions are constructed and association rules are extracted. A fuzzy extension of text transactions and association rules is employed, where the presence of the terms (items) in the documents (transactions) is determined with a value between 0 and 1. The obtained rules offer the user additional terms to be added to the query with the purpose of guiding the search and improving the retrieval.