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COOPIS
2004
IEEE
13 years 9 months ago
Trust-Aware Collaborative Filtering for Recommender Systems
Recommender Systems allow people to find the resources they need by making use of the experiences and opinions of their nearest neighbours. Costly annotations by experts are replac...
Paolo Massa, Paolo Avesani
IPM
2010
157views more  IPM 2010»
13 years 3 months ago
Personalization of tagging systems
Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relatio...
Jun Wang, Maarten Clements, Jie Yang, Arjen P. de ...
WWW
2009
ACM
14 years 6 months ago
Collaborative filtering for orkut communities: discovery of user latent behavior
Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over ...
WenYen Chen, Jon-Chyuan Chu, Junyi Luan, Hongjie B...
IIR
2010
13 years 7 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
KDD
2005
ACM
218views Data Mining» more  KDD 2005»
14 years 5 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher