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DL
2000
Springer
173views Digital Library» more  DL 2000»
13 years 12 months ago
Content-based book recommending using learning for text categorization
Recommender systems improve access to relevant products and information by making personalized suggestions based on previous examples of a user's likes and dislikes. Most exi...
Raymond J. Mooney, Loriene Roy
AI
2009
Springer
14 years 2 months ago
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Abstract. We use a hierarchical Bayesian approach to model user preferences in different contexts or settings. Unlike many previous recommenders, our approach is content-based. We...
Daniel Pomerantz, Gregory Dudek
ACMICEC
2007
ACM
154views ECommerce» more  ACMICEC 2007»
13 years 11 months ago
Learning and adaptivity in interactive recommender systems
Recommender systems are intelligent E-commerce applications that assist users in a decision-making process by offering personalized product recommendations during an interaction s...
Tariq Mahmood, Francesco Ricci
SAMT
2007
Springer
136views Multimedia» more  SAMT 2007»
14 years 1 months ago
Automatic Recommendations for Machine-Assisted Multimedia Annotation: A Knowledge-Mining Approach
Recommender systems apply knowledge discovery techniques to help in finding associated information. In this paper, we investigate the use of association rule mining as an underlyi...
Mónica Díez, Paulo Villegas
CIKM
2005
Springer
14 years 1 months ago
Feature-based recommendation system
The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems—a personalized information filtering technology use...
Eui-Hong Han, George Karypis