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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 7 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 7 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
ADMA
2009
Springer
212views Data Mining» more  ADMA 2009»
14 years 2 months ago
Automating Gene Expression Annotation for Mouse Embryo
It is of high biomedical interest to identify gene interactions and networks that are associated with developmental and physiological functions in the mouse embryo. There are now v...
Liangxiu Han, Jano I. van Hemert, Richard A. Baldo...
BMCBI
2005
106views more  BMCBI 2005»
13 years 7 months ago
Thesaurus-based disambiguation of gene symbols
Background: Massive text mining of the biological literature holds great promise of relating disparate information and discovering new knowledge. However, disambiguation of gene s...
Bob J. A. Schijvenaars, Barend Mons, Marc Weeber, ...
ICDE
2001
IEEE
163views Database» more  ICDE 2001»
14 years 8 months ago
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
We present a new algorithm for mining maximal frequent itemsets from a transactional database. Our algorithm is especially efficient when the itemsets in the database are very lon...
Douglas Burdick, Manuel Calimlim, Johannes Gehrke