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» Accuracy in Rating and Recommending Item Features
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SDM
2010
SIAM
217views Data Mining» more  SDM 2010»
13 years 6 months ago
Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...
Quanquan Gu, Jie Zhou, Chris H. Q. Ding
CSREAEEE
2006
174views Business» more  CSREAEEE 2006»
13 years 9 months ago
Using Temporal Information in Collaborative Filtering: An Empirical Study
- Collaborative filtering is a widely used and proven method of building recommender systems that provide personalized recommendations on products or services based on explicit rat...
Young Park, Tong-Queue Lee
TSMC
2008
109views more  TSMC 2008»
13 years 7 months ago
Providing Justifications in Recommender Systems
Abstract--Recommender systems are gaining widespread acceptance in e-commerce applications to confront the "information overload" problem. Providing justification to a re...
Panagiotis Symeonidis, Alexandros Nanopoulos, Yann...
SIGIR
2004
ACM
14 years 1 months ago
A music recommender based on audio features
Many collaborative music recommender systems (CMRS) have succeeded in capturing the similarity among users or items based on ratings, however they have rarely considered about the...
Qing Li, Byeong Man Kim, Donghai Guan, Duk whan Oh
ICMLA
2008
13 years 9 months ago
Data Integration for Recommendation Systems
The quality of large-scale recommendation systems has been insufficient in terms of the accuracy of prediction. One of the major reasons is caused by the sparsity of the samples, ...
Zhonghang Xia, Houduo Qi, Manghui Tu, Wenke Zhang