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We developed Relational Data Mining approach which allows to overcome essential limitations of the Data Mining and Knowledge Discovery techniques. In the paper the approach was im...
I. V. Khomicheva, Eugenii E. Vityaev, Elena A. Ana...
Estimating the depth of anesthesia (DOA) is still a challenging area in anesthesia research. The objective of this study was to design a fuzzy rule based system which integrates el...
V. Esmaeili, Amin Assareh, M. B. Shamsollahi, Moha...
A principally new approach to the classifications of nucleotide sequences based on the "natural" classification concept is proposed. As a result of "natural" c...
Eugenii E. Vityaev, K. A. Lapardin, I. V. Khomiche...
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Data mining (DM) research has successfully developed advanced DM techniques and algorithms over the last few decades, and many organisations have great expectations to take more be...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
Meta-heuristics such as simulated annealing, genetic algorithms and tabu search have been successfully applied to many difficult optimization problems for which no satisfactory pro...
Abstract. We address the problem of matching imperfectly documented schemas of data streams and large databases. Instancelevel schema matching algorithms identify likely correspond...
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its ...