2015 | OriginalPaper | Buchkapitel
Towards Query Level Resource Weighting for Diversified Query Expansion
verfasst von : Arbi Bouchoucha, Xiaohua Liu, Jian-Yun Nie
Erschienen in: Advances in Information Retrieval
Verlag: Springer International Publishing
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Diversifying query expansion that leverages multiple resources has demonstrated promising results in the task of search result diversification (SRD) on several benchmark datasets. In existing studies, however, the weight of a resource, or the degree of the contribution of that resource to SRD, is largely ignored. In this work, we present a query level resource weighting method based on a set of features which are integrated into a regression model. Accordingly, we develop an SRD system which generates for a resource a number of expansion candidates that is proportional to the weight of that resource. We thoroughly evaluate our approach on TREC 2009, 2010 and 2011 Web tracks, and show that: 1) our system outperforms the existing methods without resource weighting; and 2) query level resource weighting is superior to the non-query level resource weighting.