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On Query Result Diversification

Resource type
Authors/contributors
Title
On Query Result Diversification
Abstract
In this paper we describe a general framework for evaluation and optimization of methods for diversifying query results. In these methods, an initial ranking candidate set produced by a query is used to construct a result set, where elements are ranked with respect to relevance and diversity features, i.e., the retrieved elements should be as relevant as possible to the query, and, at the same time, the result set should be as diverse as possible. While addressing relevance is relatively simple and has been heavily studied, diversity is a harder problem to solve. One major contribution of this paper is that, using the above framework, we adapt, implement and evaluate several existing methods for diversifying query results. We also propose two new approaches, namely the Greedy with Marginal Contribution (GMC) and the Greedy Randomized with Neighborhood Expansion (GNE) methods. Another major contribution of this paper is that we present the first thorough experimental evaluation of the various diversification techniques implemented in a common framework. We examine the methods' performance with respect to precision, running time and quality of the result. Our experimental results show that while the proposed methods have higher running times, they achieve precision very close to the optimal, while also providing the best result quality. While GMC is deterministic, the randomized approach (GNE) can achieve better result quality if the user is willing to tradeoff running time.
Date
2011
Proceedings Title
Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Place
Washington, DC, USA
Publisher
IEEE Computer Society
Pages
1163–1174
Series
ICDE '11
Language
en
DOI
10.1109/ICDE.2011.5767846
ISBN
978-1-4244-8959-6
Accessed
2019-01-27T22:10:26Z
Library Catalog
ACM Digital Library
Citation
Vieira, M. R., Razente, H. L., Barioni, M. C. N., Hadjieleftheriou, M., Srivastava, D., Traina, C., & Tsotras, V. J. (2011). On Query Result Diversification. In Proceedings of the 2011 IEEE 27th International Conference on Data Engineering (pp. 1163–1174). Washington, DC, USA: IEEE Computer Society. https://doi.org/10.1109/ICDE.2011.5767846
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