IMPROVED DENSITY BASED ALGORITHM FOR DATA STREAM CLUSTERING
DOI:
https://doi.org/10.11113/jt.v77.6492Keywords:
Data streams, density-based clusteringAbstract
In recent years, clustering methods have attracted more attention in analysing and monitoring data streams. Density-based techniques are the remarkable category of clustering techniques that are able to detect the clusters with arbitrary shapes and noises. However, finding the clusters with local density varieties is a difficult task. For handling this problem, in this paper, a new density-based clustering algorithm for data streams is proposed. This algorithm can improve the offline phase of density-based algorithm based on MinPts parameter. The experimental results show that the proposed technique can improve the clustering quality in data streams with different densities.
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