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UM
2007
Springer
14 years 1 months ago
Feature-Weighted User Model for Recommender Systems
Recommender systems are gaining widespread acceptance in e-commerce applications to confront the “information overload” problem. Collaborative Filtering (CF) is a successful re...
Panagiotis Symeonidis, Alexandros Nanopoulos, Yann...
UAI
2003
13 years 8 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
ICDE
2012
IEEE
257views Database» more  ICDE 2012»
11 years 10 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...
JCDL
2004
ACM
146views Education» more  JCDL 2004»
14 years 27 days ago
Enhancing digital libraries with TechLens+
The number of research papers available is growing at a staggering rate. Researchers need tools to help them find the papers they should read among all the papers published each y...
Roberto Torres, Sean M. McNee, Mara Abel, Joseph A...
TKDE
2012
236views Formal Methods» more  TKDE 2012»
11 years 10 months ago
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques
— Recommender systems are becoming increasingly important to individual users and businesses for providing personalized recommendations. However, while the majority of algorithms...
Gediminas Adomavicius, YoungOk Kwon