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ICDE
2011
IEEE
225views Database» more  ICDE 2011»
12 years 11 months ago
Methods for boosting recommender systems
—Online shopping has grown rapidly over the past few years. Besides the convenience of shopping directly from ones home, an important advantage of e-commerce is the great variety...
Rubi Boim, Tova Milo
RECSYS
2009
ACM
14 years 1 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
WWW
2005
ACM
14 years 8 months ago
Finding group shilling in recommendation system
In the age of information explosion, recommendation system has been proved effective to cope with information overload in ecommerce area. However, unscrupulous producers shill the...
Xue-Feng Su, Hua-Jun Zeng, Zheng Chen
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...
KDD
2009
ACM
162views Data Mining» more  KDD 2009»
14 years 8 months ago
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot make recommendations ...
Mohsen Jamali, Martin Ester