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Dynamic data assigning assessment clustering of streaming data
2008
Applied Soft Computing
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
doi:10.1016/j.asoc.2007.11.006
fatcat:u4xeuxnckjfodj2v2zmm7rcds4