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C-DenStream: Using Domain Knowledge on a Data Stream

, , and . Discovery Science, volume 5808 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2009)

Abstract

Stream clustering algorithms are traditionally designed to process streams efficiently and to adapt to the evolution of the underlying population. This is done without assuming any prior knowledge about the data. However, in many cases, a certain amount of domain or background knowledge is available, and instead of simply using it for the external validation of the clustering results, this knowledge can be used to guide the clustering process. In non-stream data, domain knowledge is exploited in the context of

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DOI:
10.1007/978-3-642-04747-3_23
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