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» Capturing interest through inference and visualization: onto...
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KCAP
2003
ACM
13 years 9 months ago
Capturing interest through inference and visualization: ontological user profiling in recommender systems
Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a diverse and dynamic environment. Recommender systems ...
Stuart E. Middleton, Nigel R. Shadbolt, David De R...
RECSYS
2009
ACM
13 years 9 months ago
A semantic framework for personalized ad recommendation based on advanced textual analysis
In this paper we present a hybrid recommendation system that combines ontological knowledge with content-extracted linguistic information, derived from pre-trained lexical graphs,...
Dorothea Tsatsou, Fotis Menemenis, Ioannis Kompats...
AAAI
2006
13 years 6 months ago
Inferring User's Preferences using Ontologies
We consider recommender systems that filter information and only show the most preferred items. Good recommendations can be provided only when an accurate model of the user's...
Vincent Schickel-Zuber, Boi Faltings
KI
2002
Springer
13 years 4 months ago
Adaptivity through Unobstrusive Learning
In this paper, we present an approach for learning interest profiles implicitly from positive user observations only. This approach eliminates the need to prompt users for ratings...
Ingo Schwab, Alfred Kobsa
WWW
2005
ACM
14 years 5 months ago
AVATAR: an approach based on semantic reasoning to recommend personalized TV programs
In this paper a TV recommender system called AVATAR (AdVAnce Telematic search of Audiovisual contents by semantic Reasoning) is presented. This tool uses the experience gained in ...
Yolanda Blanco-Fernández, José J. Pa...