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» Hybrid Learning Scheme for Data Mining Applications
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IUI
2006
ACM
14 years 1 months ago
A hybrid learning system for recognizing user tasks from desktop activities and email messages
The TaskTracer system seeks to help multi-tasking users manage the resources that they create and access while carrying out their work activities. It does this by associating with...
Jianqiang Shen, Lida Li, Thomas G. Dietterich, Jon...
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
KDD
2003
ACM
149views Data Mining» more  KDD 2003»
14 years 8 months ago
Knowledge-based data mining
We describe techniques for combining two types of knowledge systems: expert and machine learning. Both the expert system and the learning system represent information by logical d...
Søren Damgaard, Sholom M. Weiss, Shubir Kap...
SC
2003
ACM
14 years 1 months ago
Optimizing Reduction Computations In a Distributed Environment
We investigate runtime strategies for data-intensive applications that involve generalized reductions on large, distributed datasets. Our set of strategies includes replicated fi...
Tahsin M. Kurç, Feng Lee, Gagan Agrawal, &U...
INFORMATICALT
2008
196views more  INFORMATICALT 2008»
13 years 7 months ago
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang