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» Explaining collaborative filtering recommendations
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DEBU
2008
186views more  DEBU 2008»
13 years 8 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
SIGIR
2009
ACM
14 years 2 months ago
On social networks and collaborative recommendation
Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided an...
Ioannis Konstas, Vassilios Stathopoulos, Joemon M....
HICSS
2009
IEEE
129views Biometrics» more  HICSS 2009»
14 years 2 months ago
Using Collaborative Filtering Algorithms as eLearning Tools
Collaborative information filtering techniques play a key role in many Web 2.0 applications. While they are currently mainly used for business purposes such as product recommendat...
Frank Loll, Niels Pinkwart
SIGIR
2004
ACM
14 years 1 months ago
A study of methods for normalizing user ratings in collaborative filtering
The goal of collaborative filtering is to make recommendations for a test user by utilizing the rating information of users who share interests similar to the test user. Because r...
Rong Jin, Luo Si
ESWA
2002
134views more  ESWA 2002»
13 years 7 months ago
A personalized recommender system based on web usage mining and decision tree induction
A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been...
Yoon Ho Cho, Jae Kyeong Kim, Soung Hie Kim