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SIGKDD
2008
138views more  SIGKDD 2008»
14 years 10 months ago
Learning preferences of new users in recommender systems: an information theoretic approach
Recommender systems are a nice tool to help nd items of interest from an overwhelming number of available items. Collaborative Filtering (CF), the best known technology for recomme...
Al Mamunur Rashid, George Karypis, John Riedl
100
Voted
TMC
2008
123views more  TMC 2008»
14 years 10 months ago
Learning Adaptive Temporal Radio Maps for Signal-Strength-Based Location Estimation
In wireless networks, a client's locations can be estimated using signal strength received from signal transmitters. Static fingerprint-based techniques are commonly used for ...
Jie Yin, Qiang Yang, Lionel M. Ni
SOCIALCOM
2010
14 years 8 months ago
Learning to Predict Ad Clicks Based on Boosted Collaborative Filtering
This paper addresses the topic of social advertising, which refers to the allocation of ads based on individual user social information and behaviors. As social network services (e...
Teng-Kai Fan, Chia-Hui Chang
ICML
2007
IEEE
15 years 11 months ago
Direct convex relaxations of sparse SVM
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 4 months ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...