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» Ranking judgments in Arrow's setting
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NIPS
2007
13 years 7 months ago
Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks
We propose a model that leverages the millions of clicks received by web search engines to predict document relevance. This allows the comparison of ranking functions when clicks ...
Ben Carterette, Rosie Jones
CHI
2009
ACM
14 years 18 days ago
Matchin: eliciting user preferences with an online game
Eliciting user preferences for large datasets and creating rankings based on these preferences has many practical applications in community-based sites. This paper gives a new met...
Severin Hacker, Luis von Ahn
EACL
2009
ACL Anthology
14 years 6 months ago
Sentiment Summarization: Evaluating and Learning User Preferences
We present the results of a large-scale, end-to-end human evaluation of various sentiment summarization models. The evaluation shows that users have a strong preference for summar...
Kevin Lerman, Sasha Blair-Goldensohn, Ryan T. McDo...
SIGIR
2011
ACM
12 years 8 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
CIKM
2009
Springer
14 years 11 days ago
Relying on topic subsets for system ranking estimation
Ranking a number of retrieval systems according to their retrieval effectiveness without relying on costly relevance judgments was first explored by Soboroff et al [6]. Over th...
Claudia Hauff, Djoerd Hiemstra, Franciska de Jong,...