Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Intelligent agent for automated manufacturing rule generation
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Extending multicriteria decision making by mixing t-norms and OWA operators: Research Articles
International Journal of Intelligent Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
Intelligent Data Mining: Techniques and Applications (Studies in Computational Intelligence)
Intelligent Data Mining: Techniques and Applications (Studies in Computational Intelligence)
Similarity relations and fuzzy orderings
Information Sciences: an International Journal
Information Sciences: an International Journal
AMID: Approximation of MultI-measured Data using SVD
Information Sciences: an International Journal
A framework for use of imprecise categorization in developing intelligent systems
IEEE Transactions on Fuzzy Systems
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We consider the problem of summarizing a collection of data values. Here we use a mountain method like approach based on the similarities of the data. Fundamental to our work is the possibility of allowing for multiple summarizing values. We present an algorithm, in the spirit of the mountain method, that uses the similarity between the data points to find focus points which serve as the seed for finding summarizing centers. Central to this algorithm is a process of reducing the energy of the data points which we show can be implemented most generally using a t-norm. We provide an application of the algorithm to the problem of binning data which is used in data mining and the development of histograms. Here we allow the location of the bins to be determined by the data rather then fixed a priori.