Abstract
Query Expansion (QE) often improves the retrieval performance of an Information Retrieval (IR) system. However, as enterprise intranets are often sparse in nature, with limited use of alternative lexical representations between authors, it can be advantageous to use Collection Enrichment (CE) to gather higher quality pseudo-feedback documents. In this paper, we propose the use of query performance predictors to selectively apply CE on a per-query basis. We thoroughly evaluate our approach on the CERC standard test collection and its corresponding topic sets from the TREC 2007 & 2008 Enterprise track document search tasks. We experiment with 3 different external resources and 3 different query performance predictors. Our experimental results demonstrate that our proposed approach leads to a significant improvement in retrieval performance.
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Peng, J., He, B., Ounis, I. (2009). Predicting the Usefulness of Collection Enrichment for Enterprise Search. In: Azzopardi, L., et al. Advances in Information Retrieval Theory. ICTIR 2009. Lecture Notes in Computer Science, vol 5766. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04417-5_41
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DOI: https://doi.org/10.1007/978-3-642-04417-5_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04416-8
Online ISBN: 978-3-642-04417-5
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