An efficient and scalable density-based clustering algorithm for datasets with complex structures

As a research branch of data mining, clustering, as an unsupervised learning scheme, focuses on assigning objects in the dataset into several groups, called clusters, without any prior knowledge. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is one of the most widely used clus...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 171; S. 9 - 22
Hauptverfasser:	Lv, Yinghua, Ma, Tinghuai, Tang, Meili, Cao, Jie, Tian, Yuan, Al-Dhelaan, Abdullah, Al-Rodhaan, Mznah
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.01.2016
Schlagworte:	Border objects detecting Density-based clustering Locality sensitive hashing The influence space Locality sensitive hashing Density-based clustering The influence space Border objects detecting
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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