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Title: WCL2R : a benchmark collection for Learning to rank research with clickthrough data.
Authors: Alcântara, Otávio D. A.
Pereira Junior, Álvaro Rodrigues
Almeida, Humberto Mossri de
Gonçalves, Marcos André
Middleton, Christian
Yates, Ricardo Baeza
Keywords: Benchmark
Learning to rank
Issue Date: 2010
Citation: ALCÂNTARA, O. D. A. WCL2R : a benchmark collection for Learning to rank research with clickthrough data. Journal of Information and Data Management, v. 1, n. 3, p. 551-566, 2010. Disponível em: <>. Acesso em: 11 out. 2012.
Abstract: WCL2R: A benchmark collection for Learning to rank research with clickthrough data In this paper we present WCL2R, a benchmark collection for supporting research in learning to rank (L2R) algorithms which exploit clickthrough features. Differently from other L2R benchmark collections, such as LETOR and the recently released Yahoo!’s collection for a L2R competition, in WCL2R we focus on defining a significant (and new) set of features over clickthrough data extracted from the logs of a real-world search engine. In this paper, we describe the WCL2R collection by providing details about how the corpora, queries and relevance judgments were obtained, how the learning features were constructed and how the process of splitting the collection in folds for representative learning was performed. We also analyze the discriminative power of the WCL2R collection using traditional feature selection algorithms and show that the most discriminative features are, in fact, those based on clickthrough data. We then compare several L2R algorithms on WCL2R, showing that all of them obtain significant gains by exploiting clickthrough information over using traditional ranking approaches.
ISSN: 21666288
metadata.dc.rights.license: Permission to copy without fee all or part of the material printed in JIDM is granted provided that the copies are not made or distributed for commercial advantage, and that notice is given that copying is by permission of the Sociedade Brasileira de Computação. Fonte: o próprio artigo.
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