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» Query quality: user ratings and system predictions
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ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...
CIKM
2006
Springer
14 years 19 days ago
Coupling feature selection and machine learning methods for navigational query identification
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Yumao Lu, Fuchun Peng, Xin Li, Nawaaz Ahmed
WISE
2009
Springer
14 years 6 months ago
Start Trusting Strangers? Bootstrapping and Prediction of Trust
Web-based environments typically span interactions between humans and software services. The management and automatic calculation of trust are among the key challenges of the futur...
Florian Skopik, Daniel Schall, Schahram Dustdar
WWW
2005
ACM
14 years 9 months ago
Clustering for probabilistic model estimation for CF
Based on the type of collaborative objects, a collaborative filtering (CF) system falls into one of two categories: item-based CF and user-based CF. Clustering is the basic idea i...
Qing Li, Byeong Man Kim, Sung-Hyon Myaeng
SIGIR
2003
ACM
14 years 2 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