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» Learning and adaptivity in interactive recommender systems
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IUI
2000
ACM
13 years 12 months ago
Learning to recommend from positive evidence
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that nee...
Ingo Schwab, Wolfgang Pohl, Ivan Koychev
MIR
2010
ACM
264views Multimedia» more  MIR 2010»
14 years 2 months ago
Quest for relevant tags using local interaction networks and visual content
Typical tag recommendation systems for photos shared on social networks such as Flickr, use visual content analysis, collaborative filtering or personalization strategies to prod...
Neela Sawant, Ritendra Datta, Jia Li, James Ze Wan...
GI
2009
Springer
13 years 5 months ago
An Adaptative Framework for Tracking Web-based Learning Environments
: Collecting and sharing attention information represents a main concern within the Technology Enhanced Learning community, as the number of works or projects related to this topic...
Valentin Butoianu, Philippe Vidal, Julien Broisin
SIGIR
2011
ACM
12 years 10 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
AH
2008
Springer
14 years 1 months ago
RSS-Based Interoperability for User Adaptive Systems
This paper presents an approach to exploit widely used tag annotations to address two important issues in user-adaptive systems: the cold-start problem and the integration of distr...
Yiwen Wang, Federica Cena, Francesca Carmagnola, O...