Comparing and Combining Methods for Automatic Query Expansion

Abstract. Query expansion is a well known method to improve the performance of information retrieval systems. In this work we have tested different approaches to extract the candidate query terms from the top ranked documents returned by the first-pass retrieval. One of them is the cooccurrence approach, based on measures of cooccurrence of the candidate and the query terms in the retrieved documents. The other one, the probabilistic approach, is based on the probability distribution of terms in the collection and in the top ranked set. We compare the retrieval improvement achieved by expanding the query with terms obtained with different methods belonging to both approaches. Besides, we have developed a na

• Type: Journal
• Year: 2008
• Where: CORR
• Authors: José R. Pérez-Agüera, Lourdes Araujo
• Keywords: CORR 2008, Education, First-pass Retrieval, Information Retrieval Systems, Query Expansion