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\iteman{io-port 06069477}
\itemau{Duda, Piotr; Jaworski, Maciej; Pietruczuk, Lena}
\itemti{On pre-processing algorithms for data stream.}
\itemso{Rutkowski, Leszek (ed.) et al., Artificial intelligence and soft computing. 11th international conference, ICAISC 2012, Zakopane, Poland, April 29--May 3, 2012. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-29349-8/pbk). Lecture Notes in Computer Science 7268. Lecture Notes in Artificial Intelligence, 56-63 (2012).}
\itemab
Summary: Clustering is a one of the most important tasks of data mining. Algorithms like the Fuzzy C-Means and Possibilistic C-Means provide good result both for the static data and data streams. All clustering algorithms compute centers from chunk of data, what requires a lot of time. If the rate of incoming data is faster than speed of algorithm, part of data will be lost. To prevent such situation, some pre-processing algorithms should be used. The purpose of this paper is to propose a pre-processing method for clustering algorithms. Experimental results show that proposed method is appropriate to handle noisy data and can accelerate processing time.
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\itemcc{}
\itemut{data streams; fuzzy clustering; pre-processing}
\itemli{doi:10.1007/978-3-642-29350-4\_7}
\end