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» Active Learning in the Drug Discovery Process
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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 5 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
AIED
2005
Springer
14 years 29 days ago
Discovery of Patterns in Learner Actions
This paper describes an approach for analysis of computer-supported learning processes utilizing logfiles of learners’ actions. We provide help to researchers and teachers in ...
Andreas Harrer, Michael Vetter, Stefan Thür, ...
IDA
2008
Springer
13 years 7 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
PGLDB
2003
151views Database» more  PGLDB 2003»
13 years 8 months ago
Web-service-based, Dynamic and Collaborative E-learning
This paper describes an on-going effort to investigate problems and approaches for achieving Web-service-based, dynamic and collaborative e-learning. In this work, a Learning Cont...
Stanley Y. W. Su, Gilliean Lee
BMCBI
2011
13 years 2 months ago
Systematic error detection in experimental high-throughput screening
Background: High-throughput screening (HTS) is a key part of the drug discovery process during which thousands of chemical compounds are screened and their activity levels measure...
Plamen Dragiev, Robert Nadon, Vladimir Makarenkov