Evaluating Search Result Diversity using Intent Hierarchies

Abstract

Search result diversification aims at returning diversified document lists to cover different user intents for ambiguous or broad queries. Existing diversity measures assume that user intents are independent or exclusive, and do not consider the relationships among the intents. In this paper, we introduce intent hierarchies to model the relationships among intents. Based on intent hierarchies, we propose several hierarchical measures that can consider the relationships among intents. We demonstrate the feasibility of hierarchical measures by using a new test collection based on TREC Web Track 2009-2013 diversity test collections. Our main experimental findings are: (1) Hierarchical measures are generally more discriminative and intuitive than existing measures using flat lists of intents; (2) When the queries have multilayer intent hierarchies, hierarchical measures are less correlated to existing measures, but can get more improvement in discriminative power; (3) Hierarchical measures are more intuitive in terms of diversity or relevance. The hierarchical measures using the whole intent hierarchies are more intuitive than only using the leaf nodes in terms of diversity and relevance.