Selectively diversifying web search results

Search result diversification is a natural approach for tackling ambiguous queries. Nevertheless, not all queries are equally ambiguous, and hence different queries could benefit from different diversification strategies. A more lenient or more aggressive diversification strategy is typically encoded by existing approaches as a trade-off between promoting relevance or diversity in the search results. In this paper, we propose to learn such a trade-off on a per-query basis. In particular, we examine how the need for diversification can be learnt for each query—given a diversification approach and an unseen query, we predict an effective tradeoff between relevance and diversity based on similar previously seen queries. Thorough experiments using the TREC ClueWeb09 collection show that our selective approach can significantly outperform a uniform diversification for both classical and state-of-the-art diversification approaches. Categories and Subject Descriptors H.3.3 [...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis
• Keywords: Aggressive Diversification Strategy, Ambiguous Queries, CIKM 2010, Different Diversification Strategies, Information Technology