Data Stream Clustering With Affinity Propagation

Data stream clustering provides insights into the underlying patterns of data flows. This paper focuses on selecting the best representatives from clusters of streaming data. There are two main challenges: how to cluster with the best representatives and how to handle the evolving patterns that are...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2014-07, Vol.26 (7), p.1644-1656
Hauptverfasser:	Xiangliang Zhang, Furtlehner, Cyril, Germain-Renaud, Cecile, Sebag, Michele
Format:	Artikel
Sprache:	eng
Schlagworte:	Affinity Propagation Algorithms Artificial Intelligence Change detection algorithms Clustering algorithms Computational modeling Computer Science Data models Data Stream Clustering Machine Learning Monitoring Optimization Reservoirs
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