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SIGIR
2011
ACM
12 years 7 months ago
2011
ACM
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
SIGIR
2012
ACM
11 years 7 months ago
2012
ACM
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
SIGIR
2010
ACM
13 years 8 months ago
2010
ACM
Ranking search results is a fundamental problem in information retrieval. In this paper we explore whether the use of proximity and phrase information can improve web retrieval ac...