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SIGIR
2010
ACM
15 years 10 months ago
Learning more powerful test statistics for click-based retrieval evaluation
Interleaving experiments are an attractive methodology for evaluating retrieval functions through implicit feedback. Designed as a blind and unbiased test for eliciting a preferen...
Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, T...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 7 months ago
Predicting customer shopping lists from point-of-sale purchase data
This paper describes a prototype that predicts the shopping lists for customers in a retail store. The shopping list prediction is one aspect of a larger system we have developed ...
Chad M. Cumby, Andrew E. Fano, Rayid Ghani, Marko ...
ECMDAFA
2007
Springer
122views Hardware» more  ECMDAFA 2007»
16 years 1 months ago
Model Transformation from OWL-S to BPEL Via SiTra
Although there are a large number of academic and industrial model transformation frameworks available, allowing specification, implementation, maintenance and documentation of mod...
Behzad Bordbar, Gareth Howells, Michael Evans, Ath...
ICRA
2010
IEEE
128views Robotics» more  ICRA 2010»
15 years 5 months ago
A game-theoretic procedure for learning hierarchically structured strategies
— This paper addresses the problem of acquiring a hierarchically structured robotic skill in a nonstationary environment. This is achieved through a combination of learning primi...
Benjamin Rosman, Subramanian Ramamoorthy
CIKM
2011
Springer
14 years 6 months ago
A probabilistic method for inferring preferences from clicks
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke