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» Methods for boosting recommender systems
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RECSYS
2010
ACM
13 years 7 months ago
Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Fac...
Alexandros Karatzoglou, Xavier Amatriain, Linas Ba...
IFIP12
2009
13 years 5 months ago
User Recommendations based on Tensor Dimensionality Reduction
Social Tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, web links, products etc.). Social tagging...
Panagiotis Symeonidis
PPOPP
2009
ACM
14 years 10 days ago
Turbocharging boosted transactions or: how i learnt to stop worrying and love longer transactions
Boosted transactions offer an attractive method that enables programmers to create larger transactions that scale well and offer deadlock-free guarantees. However, as boosted tran...
Chinmay Eishan Kulkarni, Osman S. Unsal, Adri&aacu...
SIGIR
2011
ACM
12 years 10 months ago
Fast context-aware recommendations with factorization machines
The situation in which a choice is made is an important information for recommender systems. Context-aware recommenders take this information into account to make predictions. So ...
Steffen Rendle, Zeno Gantner, Christoph Freudentha...
TNN
2010
127views Management» more  TNN 2010»
13 years 2 months ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia