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KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 10 months ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...
KDD
2010
ACM
190views Data Mining» more  KDD 2010»
14 years 2 months ago
User browsing models: relevance versus examination
There has been considerable work on user browsing models for search engine results, both organic and sponsored. The click-through rate (CTR) of a result is the product of the prob...
Ramakrishnan Srikant, Sugato Basu, Ni Wang, Daryl ...
AUSDM
2008
Springer
274views Data Mining» more  AUSDM 2008»
14 years 3 days ago
Identifying Stock Similarity Based on Multi-event Episodes
Predicting stock market movements is always difficult. Investors try to guess a stock's behavior, but it often backfires. Thumb rules and intuition seems to be the major indi...
Abhi Dattasharma, Praveen Kumar Tripathi, Sridhar ...
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
12 years 5 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
12 years 16 days ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich