Tracking Context Changes through Meta-Learning
Machine Learning - Special issue on multistrategy learning
Machine Learning - Special issue on context sensitivity and concept drift
A Learning Agent that Assists the Browsing of Software Libraries
IEEE Transactions on Software Engineering
Discovering Robust Knowledge from Databases that Change
Data Mining and Knowledge Discovery
An initial framework of contexts for designing usable intelligent tutoring systems
Information Services and Use
Using multiple windows to track concept drift
Intelligent Data Analysis
Dynamic integration of classifiers for handling concept drift
Information Fusion
An active learning system for mining time-changing data streams
Intelligent Data Analysis
Efficient instance-based learning on data streams
Intelligent Data Analysis
The Cost of Learning Directed Cuts
ECML '07 Proceedings of the 18th European conference on Machine Learning
Self-tuning query mesh for adaptive multi-route query processing
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
A case-based technique for tracking concept drift in spam filtering
Knowledge-Based Systems
Quick adaptation to changing concepts by sensitive detection
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
An efficient algorithm for instance-based learning on data streams
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Dynamic financial distress prediction using instance selection for the disposal of concept drift
Expert Systems with Applications: An International Journal
On classifying drifting concepts in P2P networks
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
What is concept drift and how to measure it?
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
Classifier ensembles for virtual concept drift - the DEnBoost algorithm
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Concept drift and how to identify it
Web Semantics: Science, Services and Agents on the World Wide Web
Beating the baseline prediction in food sales: How intelligent an intelligent predictor is?
Expert Systems with Applications: An International Journal
WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
ACE: adaptive classifiers-ensemble system for concept-drifting environments
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Detecting change via competence model
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Time variance and defect prediction in software projects
Empirical Software Engineering
A survey on concept drift adaptation
ACM Computing Surveys (CSUR)
Concept drift detection via competence models
Artificial Intelligence
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