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» Recommendation Systems: A Probabilistic Analysis
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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
SIGIR
2003
ACM
13 years 10 months ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
JTAER
2010
164views more  JTAER 2010»
13 years 1 days ago
Research and Design of a Grid Based Electronic Commerce Recommendation System
Current electronic commerce recommendation system is designed for single electronic commerce website and current recommendation technologies have obvious deficiencies Centralized ...
Yueling Liang, Guihua Nie
WISE
2005
Springer
13 years 10 months ago
A Web Recommendation Technique Based on Probabilistic Latent Semantic Analysis
Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of clickstream data will lead to capture usag...
Guandong Xu, Yanchun Zhang, Xiaofang Zhou
AIRS
2005
Springer
13 years 10 months ago
A Probabilistic Model for Music Recommendation Considering Audio Features
In order to make personalized recommendations, many collaborative music recommender systems (CMRS) focused on capturing precise similarities among users or items based on user hist...
Qing Li, Sung-Hyon Myaeng, Donghai Guan, Byeong Ma...