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WSDM
2009
ACM

Diversifying search results

12 years 4 months ago
Diversifying search results
We study the problem of answering ambiguous web queries in a setting where there exists a taxonomy of information, and that both queries and documents may belong to more than one category according to this taxonomy. We present a systematic approach to diversifying results that aims to minimize the risk of dissatisfaction of the average user. We propose an algorithm that well approximates this objective in general, and is provably optimal for a natural special case. Furthermore, we generalize several classical IR metrics, including NDCG, MRR, and MAP, to explicitly account for the value of diversification. We demonstrate empirically that our algorithm scores higher in these generalized metrics compared to results produced by commercial search engines. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval—retrieval models General Terms Algorithm, Performance Keywords Result diversification, relevance, marginal utility
Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverso
Added 19 May 2010
Updated 19 May 2010
Type Conference
Year 2009
Where WSDM
Authors Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverson, Samuel Ieong
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