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107
Voted
CIKM
2008
Springer
15 years 2 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
103
Voted
SEMWEB
2009
Springer
15 years 7 months ago
Using Naming Authority to Rank Data and Ontologies for Web Search
Abstract. The focus of web search is moving away from returning relevant documents towards returning structured data as results to user queries. A vital part in the architecture of...
Andreas Harth, Sheila Kinsella, Stefan Decker
WWW
2010
ACM
15 years 7 months ago
Generalized distances between rankings
Spearman’s footrule and Kendall’s tau are two well established distances between rankings. They, however, fail to take into account concepts crucial to evaluating a result set...
Ravi Kumar, Sergei Vassilvitskii
122
Voted
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
13 years 8 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
TAL
2010
Springer
14 years 11 months ago
Concept Based Representations for Ranking in Geographic Information Retrieval
Abstract. Geographic Information Retrieval (GIR) is a specialized Information Retrieval (IR) branch that deals with information related to geographical locations. Traditional IR en...
Maya Carrillo, Esaú Villatoro-Tello, Aureli...