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RECSYS
2009
ACM
14 years 2 months ago
Ordering innovators and laggards for product categorization and recommendation
Different buyers exhibit different purchasing behaviors. Some rush to purchase new products while others tend to be more cautious, waiting for reviews from people they trust. In...
Sarah K. Tyler, Shenghuo Zhu, Yun Chi, Yi Zhang
CISS
2008
IEEE
14 years 2 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach
ICPPW
2002
IEEE
14 years 1 months ago
Hebbian Algorithms for a Digital Library Recommendation System
generally meta-data, so that documents on any specific subject can be transparently retrieved. While quality control can in principle still rely on the traditional methods of peer-...
Francis Heylighen, Johan Bollen
IUI
2000
ACM
14 years 16 days ago
Learning to recommend from positive evidence
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that nee...
Ingo Schwab, Wolfgang Pohl, Ivan Koychev
IIR
2010
13 years 9 months ago
An IR-Based Approach for Tag Recommendation
Thanks to the continuous growth of collaborative platforms like YouTube, Flickr and Delicious, we are recently witnessing to a rapid evolution of web dynamics towards a more `soci...
Cataldo Musto, Fedelucio Narducci, Marco de Gemmis...