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» Methods for boosting recommender systems
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COOPIS
2004
IEEE
13 years 11 months ago
Trust-Aware Collaborative Filtering for Recommender Systems
Recommender Systems allow people to find the resources they need by making use of the experiences and opinions of their nearest neighbours. Costly annotations by experts are replac...
Paolo Massa, Paolo Avesani
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...
GFKL
2007
Springer
196views Data Mining» more  GFKL 2007»
14 years 1 months ago
Comparison of Recommender System Algorithms Focusing on the New-item and User-bias Problem
Recommender systems are used by an increasing number of e-commerce websites to help the customers to find suitable products from a large database. One of the most popular techniqu...
Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thiem...
AVI
2004
13 years 9 months ago
More than the sum of its members: challenges for group recommender systems
Systems that recommend items to a group of two or more users raise a number of challenging issues that are so far only partly understood. This paper identifies four of these issue...
Anthony Jameson
RECSYS
2009
ACM
14 years 2 months ago
Harnessing the power of "favorites" lists for recommendation systems
We propose a novel collaborative recommendation approach to take advantage of the information available in user-created lists. Our approach assumes associations among any two item...
Maryam Khezrzadeh, Alex Thomo, William W. Wadge