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» Top-k learning to rank: labeling, ranking and evaluation
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ACL
2009
14 years 7 months ago
A Graph-based Semi-Supervised Learning for Question-Answering
We present a graph-based semi-supervised learning for the question-answering (QA) task for ranking candidate sentences. Using textual entailment analysis, we obtain entailment sco...
Asli Çelikyilmaz, Marcus Thint, Zhiheng Hua...
SIGIR
2004
ACM
15 years 3 months ago
A joint framework for collaborative and content filtering
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...
Justin Basilico, Thomas Hofmann
108
Voted
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
13 years 5 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
63
Voted
FUNGAMES
2008
14 years 10 months ago
Developing an Adaptive Memory Game for Seniors
This paper describes the development of a game application for seniors to train their memory and learning abilities. From an initial co-discovery evaluation participants were found...
Elly Zwartkruis-Pelgrim, Boris E. R. de Ruyter
111
Voted
ICML
2000
IEEE
15 years 10 months ago
Eligibility Traces for Off-Policy Policy Evaluation
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh