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2008

Dynamic data assigning assessment clustering of streaming data

8 years 10 months ago
Dynamic data assigning assessment clustering of streaming data
: Discovering interesting patterns or substructures in data streams is an important challenge in data mining. Clustering algorithms are very often applied to identify single substructures although they are designed to partition a data set. Another problem of clustering algorithms is that most of them are not designed for data streams. This paper discusses a recently introduced procedure that deals with both problems. The procedure explores ideas from cluster analysis, but was designed to identify single clusters without the necessity to partition the whole data set into clusters. The new extended version of the algorithm is an incremental clustering approach applicable to stream data. It identifies new clusters formed by the incoming data and updates the data space partition. Clustering of artificial and real data sets illustrates the abilities of the proposed method.
Olga Georgieva, Frank Klawonn
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2008
Where ASC
Authors Olga Georgieva, Frank Klawonn
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