Resumen

GIRALDO, Fabián Andrés; LEON, Elizabeth  y  GOMEZ, Jonatan. Characterizing data stream using clustering algorithms. Tecnura [online]. 2013, vol.17, n.37, pp.153-166. ISSN 0123-921X.

Abstract This paper presents introductory materials to datastream mining processes using clustering techniques. The limitations of traditional techniques are observed and the various approaches found in the literature are explained. The major trends in the different algorithms indicate that most applications separate the process into two phases; namely an online phase, which makes a data stream summarization in addition to the application of decay functions regardless of the data, and an offine phase, which is the application of traditional clustering techniques in order to obtain the cluster requested by users. The net result of this paper is a selection of desirable characteristics of an algorithm, based on the theoretical underpinnings of each of the works analyzed.

Palabras clave : clustering methods; data stream; data mining.

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