Exploring accumulative query expansion for relevance feedback

Authors:
Debasis Ganguly;Johannes Leveling;Gareth J. F. Jones
Affiliations:
CNGL, School of Computing, Dublin City University, Dublin 9, Ireland;CNGL, School of Computing, Dublin City University, Dublin 9, Ireland;CNGL, School of Computing, Dublin City University, Dublin 9, Ireland
Venue:
INEX'10 Proceedings of the 9th international conference on Initiative for the evaluation of XML retrieval: comparative evaluation of focused retrieval
Year:
2010

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Abstract

For the participation of Dublin City University (DCU) in the Relevance Feedback (RF) track of INEX 2010, we investigated the relation between the length of relevant text passages and the number of RF terms. In our experiments, relevant passages are segmented into non-overlapping windows of fixed length which are sorted by similarity with the query. In each retrieval iteration, we extend the current query with the most frequent terms extracted from these word windows. The number of feedback terms corresponds to a constant number, a number proportional to the length of relevant passages, and a number inversely proportional to the length of relevant passages, respectively. Retrieval experiments show a significant increase in MAP for INEX 2008 training data and improved precisions at early recall levels for the 2010 topics as compared to the baseline Rocchio feedback.