Algorithms for clustering data
Algorithms for clustering data
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
An evolutionary approach to combinatorial optimization problems
CSC '94 Proceedings of the 22nd annual ACM computer science conference on Scaling up : meeting the challenge of complexity in real-world computing applications: meeting the challenge of complexity in real-world computing applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Database techniques for the World-Wide Web: a survey
ACM SIGMOD Record
Controlling asymmetric errors in neuro-fuzzy classification
SAC '00 Proceedings of the 2000 ACM symposium on Applied computing - Volume 1
A clustering strategy based on a formalism of the reproductive process in natural systems
SIGIR '79 Proceedings of the 2nd annual international ACM SIGIR conference on Information storage and retrieval: information implications into the eighties
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Machine Learning
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
Foundations of Fuzzy Systems
A Bayesian Framework for Semantic Content Characterization
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
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In response to an explosive growth of collected, stored, and transferred data, Data Mining has emerged as a new research area. However, the approaches studied in this area are mostly specialized to analyze precise and highly structured data. Other sources of information-- for instance images--have often been neglected. The term Information Mining wants to emphasize the need for methods suited for more heterogeneous and imprecise information sources. We also claim the importance of fuzzy set methods to meet the prominent aim of to producing comprehensible results. Two case studies of applying information mining techniques to remotely sensed image data are presented.