Symbolic clustering using a new dissimilarity measure
Pattern Recognition
Clustering of interval data based on city-block distances
Pattern Recognition Letters
Interval Set Clustering of Web Users with Rough K-Means
Journal of Intelligent Information Systems
General fuzzy min-max neural network for clustering and classification
IEEE Transactions on Neural Networks
A Grey-Rough Set Approach for Interval Data Reduction of Attributes
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Rule induction based on an incremental rough set
Expert Systems with Applications: An International Journal
A reasonable rough approximation for clustering web users
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
RSMAT: Robust simultaneous modeling and tracking
Pattern Recognition Letters
A rough set based approach to patent development with the consideration of resource allocation
Expert Systems with Applications: An International Journal
Alternative rule induction methods based on incremental object using rough set theory
Applied Soft Computing
Interval clustering algorithm for fast event detection in stream monitoring applications
Pattern Recognition Letters
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This paper introduces a novel incremental approach to clustering interval data. The method employs rough set theory to capture the inherent uncertainty involved in cluster analysis. Our experimental results show that it produces meaningful cluster abstractions for interval data at a minimal computational expense.