JOURNAL ARTICLE

DS_CABOSFV clustering algorithm for high dimensional data stream

Abstract

Data stream clustering has become a hot research issue. The high-dimensional data stream clustering is a difficult problem for the data stream mining because the large volumes of data arriving in a stream make most traditional algorithms too inefficient. In this paper, DS_CABOSFV, a high-dimensional data stream clustering algorithm based on CABOSFV algorithm is presented. Our empirical tests show that DS_CABOSFV has low computational complexity and good efficiency for high-dimensional data stream clustering.

Keywords:
Data stream clustering Cluster analysis Computer science Data stream CURE data clustering algorithm Canopy clustering algorithm Data stream mining Data mining Clustering high-dimensional data Correlation clustering Algorithm Artificial intelligence

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
12
Refs
0.31
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Clustering Algorithms Research
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Stream Mining Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Anomaly Detection Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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