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» Accuracy in Rating and Recommending Item Features
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SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 8 months ago
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
ErHeng Zhong, Wei Fan, Qiang Yang
CCIA
2008
Springer
13 years 7 months ago
On the Dimensions of Data Complexity through Synthetic Data Sets
Abstract. This paper deals with the characterization of data complexity and the relationship with the classification accuracy. We study three dimensions of data complexity: the len...
Núria Macià, Ester Bernadó-Ma...
ADC
2006
Springer
123views Database» more  ADC 2006»
13 years 11 months ago
Recency-based collaborative filtering
Collaborative filtering is regarded as one of the most promising recommendation algorithms. Traditional approaches for collaborative filtering do not take concept drift into acc...
Yi Ding, Xue Li, Maria E. Orlowska
IR
2002
13 years 5 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...
SIGIR
2005
ACM
13 years 11 months ago
Scalable collaborative filtering using cluster-based smoothing
Memory-based approaches for collaborative filtering identify the similarity between two users by comparing their ratings on a set of items. In the past, the memory-based approache...
Gui-Rong Xue, Chenxi Lin, Qiang Yang, Wensi Xi, Hu...