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2009•Journal of Quanzhou Normal UniversityRequires access

Research of Clustering Algorithm Based on Density

Wang Gui-hong

Open publisher page 2 citations

Abstract

Clustering is an important task in the data mining and the clustering based on density has been proved to be a very efficient method.Then,compared with DBSCAN algorithm,we propose a clustering algorithm called CUCD(Clustering Using Centers and Density).It works based on the centers and the density.The virtual core objects are generated from the distributed data and the quality is better if the algorithm runs more times.

About this research paper

What this paper is about

Clustering is an important task in the data mining and the clustering based on density has been proved to be a very efficient method.Then,compared with DBSCAN algorithm,we propose a clustering algorithm called CUCD(Clustering Using Centers and Density).It works based on the centers and the density.The virtual core objects are generated from the distributed data and the quality is better if the algorithm runs more times.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Clustering is an important task in the data mining and the clustering based on density has been proved to be a very efficient method.Then,compared with DBSCAN algorithm,we propose a clustering algorithm called CUCD(Clustering Using Centers and Density).It works based on the centers and the density.The virtual core objects are generated from the distributed data and the quality is better if the algorithm runs more times.

Key concepts: DBSCAN, Cluster analysis, CURE data clustering algorithm, Canopy clustering algorithm, Correlation clustering, Computer science, Data stream clustering, Data mining

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