Structuring Typical Evolutions Using Temporal-Driven Constrained Clustering

In this paper, we propose a new time-aware dissimilarity measure that takes into account the temporal dimension. Observations that are close in the description space, but distant in time are considered as dissimilar. We also propose a method to enforce the segmentation contiguity, by introducing, in...

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Bibliographische Detailangaben

Hauptverfasser:	Rizoiu, M., Velcin, J., Lallich, S.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Clustering algorithms contiguity penalty function Equations Laboratories Linear programming Partitioning algorithms semi-supervised clustering temporal clustering temporal-aware dissimilarity measure Vectors
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