att_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 answer 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. Both methods iteratively construct a result
set using a scoring function that ranks candidate elements using
not only relevance and diversity to the existing result set, but also
accounts for diversity against the remaining candidates. 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´┐Ż 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.}},
	att_authors={mh6516, ds8961},
	att_categories={C_CCF.1, C_IIS.10},
	author={Marios Hadjieleftheriou and Divesh Srivastava and Marcos Vieira and Humberto Razente and Maria Barioni and Caetano Traina Jr. and Vassilis J. Tsotras},
	institution={{IEEE ICDE 2011}},
	title={{On Query Result Diversification}},