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» Explaining collaborative filtering recommendations
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SIGKDD
2008
138views more  SIGKDD 2008»
13 years 7 months ago
Learning preferences of new users in recommender systems: an information theoretic approach
Recommender systems are a nice tool to help nd items of interest from an overwhelming number of available items. Collaborative Filtering (CF), the best known technology for recomme...
Al Mamunur Rashid, George Karypis, John Riedl
ATAL
2007
Springer
13 years 12 months ago
Strategy recommender agents (ALEX) - the methodology
Agents for Alignment into strategy Experience (ALEX agents), a type of recommender agent (RA), are proposed here as a means of helping employees to perform tasks in line with the ...
Ronald Uriel Ruiz Ordóñez, Josep Llu...
CORR
2008
Springer
104views Education» more  CORR 2008»
13 years 8 months ago
A Recommender System based on Idiotypic Artificial Immune Networks
Abstract-The immune system is a complex biological system with a highly distributed, adaptive and selforganising nature. This paper presents an Artificial Immune System (AIS) that ...
Steve Cayzer, Uwe Aickelin
CORR
2010
Springer
118views Education» more  CORR 2010»
13 years 4 months ago
Estimating Probabilities in Recommendation Systems
Modeling ranked data is an essential component in a number of important applications including recommendation systems and websearch. In many cases, judges omit preference among un...
Mingxuan Sun, Guy Lebanon, Paul Kidwell
KDD
2005
ACM
180views Data Mining» more  KDD 2005»
14 years 1 months ago
Information retrieval based on collaborative filtering with latent interest semantic map
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...
Noriaki Kawamae, Katsumi Takahashi