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SOCIALCOM
2010
13 years 3 months ago
Learning to Predict Ad Clicks Based on Boosted Collaborative Filtering
This paper addresses the topic of social advertising, which refers to the allocation of ads based on individual user social information and behaviors. As social network services (e...
Teng-Kai Fan, Chia-Hui Chang
SIGIR
2004
ACM
13 years 10 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
CIKM
2008
Springer
13 years 7 months ago
Predicting individual disease risk based on medical history
The monumental cost of health care, especially for chronic disease treatment, is quickly becoming unmanageable. This crisis has motivated the drive towards preventative medicine, ...
Darcy A. Davis, Nitesh V. Chawla, Nicholas Blumm, ...
AAAI
2012
11 years 7 months ago
Transfer Learning in Collaborative Filtering with Uncertain Ratings
To solve the sparsity problem in collaborative filtering, researchers have introduced transfer learning as a viable approach to make use of auxiliary data. Most previous transfer...
Weike Pan, Evan Wei Xiang, Qiang Yang
ACMSE
2006
ACM
13 years 11 months ago
Support vector machines for collaborative filtering
Support Vector Machines (SVMs) have successfully shown efficiencies in many areas such as text categorization. Although recommendation systems share many similarities with text ca...
Zhonghang Xia, Yulin Dong, Guangming Xing