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» Principles of Lifelong Learning for Predictive User Modeling
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CCECE
2006
IEEE
14 years 1 months ago
A Dynamic Associative E-Learning Model based on a Spreading Activation Network
Presenting information to an e-learning environment is a challenge, mostly, because ofthe hypertextlhypermedia nature and the richness ofthe context and information provides. This...
Phongchai Nilas, Nilamit Nilas, Somsak Mitatha
BMCBI
2010
229views more  BMCBI 2010»
13 years 7 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
UAI
2008
13 years 9 months ago
Toward Experiential Utility Elicitation for Interface Customization
User preferences for automated assistance often vary widely, depending on the situation, and quality or presentation of help. Developing effective models to learn individual prefe...
Bowen Hui, Craig Boutilier
NIPS
2008
13 years 9 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 8 months ago
Turning down the noise in the blogosphere
In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. The task of guidin...
Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos...