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» Principles of Lifelong Learning for Predictive User Modeling
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UAI
2003
13 years 9 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
WSDM
2010
ACM
214views Data Mining» more  WSDM 2010»
14 years 5 months ago
Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation
Tagging plays an important role in many recent websites. Recommender systems can help to suggest a user the tags he might want to use for tagging a specific item. Factorization mo...
Steffen Rendle, Lars Schmidt-Thieme
CHI
2003
ACM
14 years 8 months ago
Combined model for text entry rate development
We combine the power law of learning and theoretical upper limit predictions to describe the development of text entry rates from users' first contact to asymptotic expert us...
Poika Isokoski, I. Scott MacKenzie
ICMI
2003
Springer
96views Biometrics» more  ICMI 2003»
14 years 26 days ago
Learning and reasoning about interruption
We present methods for inferring the cost of interrupting users based on multiple streams of events including information generated by interactions with computing devices, visual ...
Eric Horvitz, Johnson Apacible
AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
14 years 1 months ago
Preference Networks: Probabilistic Models for Recommendation Systems
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh