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» Two-Stage Approach to Item Recommendation from User Sessions
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AAAI
2006
13 years 6 months ago
Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Matthew Garden, Gregory Dudek
WKDD
2010
CPS
204views Data Mining» more  WKDD 2010»
13 years 10 months ago
A Scalable, Accurate Hybrid Recommender System
—Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of...
Mustansar Ali Ghazanfar, Adam Prügel-Bennett
ICDE
2007
IEEE
114views Database» more  ICDE 2007»
13 years 9 months ago
Group Recommending: A methodological Approach based on Bayesian Networks
The problem of building Recommender Systems has attracted considerable attention in recent years, but most recommender systems are designed for recommending items for individuals....
Luis M. de Campos, Juan M. Fernández-Luna, ...
ICDE
2012
IEEE
257views Database» more  ICDE 2012»
11 years 7 months ago
LARS: A Location-Aware Recommender System
Abstract—This paper proposes LARS, a location-aware recommender system that uses location-based ratings to produce recommendations. Traditional recommender systems do not conside...
Justin J. Levandoski, Mohamed Sarwat, Ahmed Eldawy...
SIGKDD
2008
138views more  SIGKDD 2008»
13 years 5 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