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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
SIGIR
2009
ACM
14 years 2 months ago
Learning to recommend with social trust ensemble
As an indispensable technique in the field of Information Filtering, Recommender System has been well studied and developed both in academia and in industry recently. However, mo...
Hao Ma, Irwin King, Michael R. Lyu
HIS
2004
13 years 9 months ago
A Case-Based Recommender for Task Assignment in Heterogeneous Computing Systems
Case-based reasoning (CBR) is a knowledge-based problem-solving technique, which is based on reuse of previous experiences. In this paper we propose a new model for static task as...
S. Ghanbari, Mohammad Reza Meybodi, Kambiz Badie
WWW
2004
ACM
14 years 8 months ago
Shilling recommender systems for fun and profit
Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have bec...
Shyong K. Lam, John Riedl
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