Classification algorithms
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Original Contribution: Stacked generalization
Neural Networks
Automated learning of decision rules for text categorization
ACM Transactions on Information Systems (TOIS)
Towards language independent automated learning of text categorization models
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Machine Learning
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Predicting equity returns from securities data
Advances in knowledge discovery and data mining
Active learning using adaptive resampling
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Solving regression problems with rule-based ensemble classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Segmentation-based modeling for advanced targeted marketing
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
R-MINI: An Iterative Approach for Generating Minimal Rules from Examples
IEEE Transactions on Knowledge and Data Engineering
Use of Contextual Information for Feature Ranking and Discretization
IEEE Transactions on Knowledge and Data Engineering
Maximizing Text-Mining Performance
IEEE Intelligent Systems
Probabilistic Estimation-Based Data Mining for Discovering Insurance Risks
IEEE Intelligent Systems
Lightweight Document Matching for Help-Desk Applications
IEEE Intelligent Systems
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A probabilistic estimation framework for predictive modeling analytics
IBM Systems Journal
Mathematical sciences in the nineties
IBM Journal of Research and Development
WSEAS Transactions on Information Science and Applications
Supporting smart interactions with predictive analytics
The smart internet
Supporting smart interactions with predictive analytics
The smart internet
Efficient multifaceted screening of job applicants
Proceedings of the 16th International Conference on Extending Database Technology
Business leadership through analytics
IBM Journal of Research and Development
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The Data Abstraction Research Group was formed in the early 1990s, to bring focus to the work of the Mathematical Sciences Department in the emerging area of knowledge discovery and data mining (KD & DM). Most activities in this group have been performed in the technical area of predictive modeling, roughly at the intersection of machine learning, statistical modeling, and database technology. There has been a major emphasis on using business and industrial problems to motivate the research agenda. Major accomplishments include advances in methods for feature analysis, rule-based pattern discovery, and probabilistic modeling, and novel solutions for insurance risk management, targeted marketing, and text mining. This paper presents an overview of the group's major technical accomplishments.