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WECWIS
2005
IEEE
137views ECommerce» more  WECWIS 2005»
13 years 10 months ago
Using Singular Value Decomposition Approximation for Collaborative Filtering
Singular Value Decomposition (SVD), together with the Expectation-Maximization (EM) procedure, can be used to find a low-dimension model that maximizes the loglikelihood of obser...
Sheng Zhang, Weihong Wang, James Ford, Fillia Make...
SIGIR
2006
ACM
13 years 10 months ago
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large ...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
IR
2002
13 years 4 months ago
An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms
Collaborative filtering systems predict a user's interest in new items based on the recommendations of other people with similar interests. Instead of performing content index...
Jonathan L. Herlocker, Joseph A. Konstan, John Rie...
IRI
2007
IEEE
13 years 11 months ago
Adapting Ratings in Memory-Based Collaborative Filtering using Linear Regression
We show that the standard memory-based collaborative filtering rating prediction algorithm using the Pearson correlation can be improved by adapting user ratings using linear reg...
Jérôme Kunegis, Sahin Albayrak
IRAL
2003
ACM
13 years 10 months ago
An approach for combining content-based and collaborative filters
In this work, we apply a clustering technique to integrate the contents of items into the item-based collaborative filtering framework. The group rating information that is obtain...
Qing Li, Byeong Man Kim