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» Letting Users Choose Recommender Algorithms: An Experimental...
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CCS
2010
ACM
13 years 8 months ago
Towards publishing recommendation data with predictive anonymization
Recommender systems are used to predict user preferences for products or services. In order to seek better prediction techniques, data owners of recommender systems such as Netfli...
Chih-Cheng Chang, Brian Thompson, Hui (Wendy) Wang...
SIGIR
2009
ACM
13 years 11 months ago
Predicting user interests from contextual information
Search and recommendation systems must include contextual information to effectively model users’ interests. In this paper, we present a systematic study of the effectiveness of...
Ryen W. White, Peter Bailey, Liwei Chen
SIGIR
2004
ACM
13 years 10 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
ICDM
2010
IEEE
267views Data Mining» more  ICDM 2010»
13 years 3 months ago
Personalizing Web Page Recommendation via Collaborative Filtering and Topic-Aware Markov Model
Web-page recommendation is to predict the next request of pages that Web users are potentially interested in when surfing the Web. This technique can guide Web users to find more u...
Qingyan Yang, Ju Fan, Jianyong Wang, Lizhu Zhou
RECSYS
2009
ACM
13 years 11 months ago
Collaborative prediction and ranking with non-random missing data
A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative ď¬...
Benjamin M. Marlin, Richard S. Zemel