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WEBI
2009
Springer
13 years 12 months ago
Zero-Sum Reward and Punishment Collaborative Filtering Recommendation Algorithm
In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
Nan Li, Chunping Li
IIR
2010
13 years 6 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
BCI
2009
IEEE
14 years 5 days ago
On the Performance of SVD-Based Algorithms for Collaborative Filtering
—In this paper, we describe and compare three Collaborative Filtering (CF) algorithms aiming at the low-rank approximation of the user-item ratings matrix. The algorithm implemen...
Manolis G. Vozalis, Angelos I. Markos, Konstantino...
AAAI
2004
13 years 6 months ago
Exploring More Realistic Evaluation Measures for Collaborative Filtering
Collaborative filtering is a popular technique for recommending items to people. Several methods for collaborative filtering have been proposed in the literature and the quality o...
Giuseppe Carenini, Rita Sharma
ICDIM
2007
IEEE
13 years 5 months ago
Assessing the value of unrated items in collaborative filtering
In collaborative filtering systems, a common technique is default voting. Unknown ratings are filled with a default value to alleviate the sparsity of rating databases. We show ...
Jérôme Kunegis, Andreas Lommatzsch, M...