Automatic query expansion may be used in document retrieval to improve search effectiveness. Traditional query expansion methods are based on the document collection itself. For example, pseudorelevance feedback (PRF) assumes that the top retrieved documents are relevant, and uses the terms extracted from those documents for query expansion. However, there are other sources of evidence that can be used for expansion, some of which may give better search results with greater efficiency at query time. In this paper, we use the external evidence, especially the hints obtained from external web search engines to expand the original query. We explore 6 different methods using search engine query log, snippets and search result documents. We conduct extensive experiments, with state of the art PRF baselines and careful parameter tuning, on three TREC collections: AP,WT10g, GOV2. Log-based methods do not show consistent significant gains, despite being very efficient at query-time. Snippet-based expansion, using the summaries provided by an external search engine, provides significant effectiveness gains with good efficiency at query-time. © Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Yin, Z., Shokouhi, M., & Craswell, N. (2009). Query expansion using external evidence. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5478 LNCS, pp. 388–399). Springer Verlag. https://doi.org/10.1007/978-3-642-00958-7_33
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