Efficient hybrid algorithms for density based subspace clustering to deal with density divergence for improved quality and conciseness
Author:
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12530-019-09308-2.pdf
Reference31 articles.
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3. Assent I, Krieger R, Müller E, Seidl T (2007) DUSC: dimensionality unbiased subspace clustering. In: Proceedings international conference on data mining, pp 409–414
4. Böhm C, Kailing K, Kriegel H-P, Kröger P (2004) Density connected clustering with local subspace preferences. In: Proceedings of the fourth IEEE international conference on data mining (ICDM’04), pp 27–34
5. Chen G, Ma X, Yang D, Tang S (2011) Efficientapproachesforsummarizingsubspaceclusters into k representatives. Soft Comput 15(5):845–853
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