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ECAI
2008
Springer
13 years 9 months ago
Probabilistic Reinforcement Rules for Item-Based Recommender Systems
The Internet is constantly growing, proposing more and more services and sources of information. Modeling personal preferences enables recommender systems to identify relevant subs...
Sylvain Castagnos, Armelle Brun, Anne Boyer
JCP
2007
105views more  JCP 2007»
13 years 7 months ago
Intuitive Network Applications: Learning for Personalized Converged Services Involving Social Networks
Abstract— The convergence of the wireline telecom, wireless telecom, and internet networks and the services they provide offers tremendous opportunities in services personalizati...
Robert Dinoff, Tin Kam Ho, Richard Hull, Bharat Ku...
HT
2009
ACM
14 years 2 months ago
Improving recommender systems with adaptive conversational strategies
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...
Tariq Mahmood, Francesco Ricci
SIGIR
1999
ACM
13 years 12 months ago
Information Retrieval as Statistical Translation
We propose a new probabilistic approach to information retrieval based upon the ideas and methods of statistical machine translation. The central ingredient in this approach is a ...
Adam L. Berger, John D. Lafferty
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