KNN-BLOCK DBSCAN: Fast Clustering for Large-Scale Data

Large-scale data clustering is an essential key for big data problem. However, no current existing approach is "optimal" for big data due to high complexity, which remains it a great challenge. In this article, a simple but fast approximate DBSCAN, namely, KNN-BLOCK DBSCAN, is proposed bas...

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Veröffentlicht in:	IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2021-06, Vol.51 (6), p.3939-3953
Hauptverfasser:	Chen, Yewang, Zhou, Lida, Pei, Songwen, Yu, Zhiwen, Chen, Yi, Liu, Xin, Du, Jixiang, Xiong, Naixue
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximation algorithms Big Data Clustering Clustering algorithms Complexity theory Computer science DBSCAN Density distribution FLANN kNN KNN-BLOCK DBSCAN Partitioning algorithms Vegetation
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