A Review on Density based Clustering Algorithms for Very Large Datasets

Provided by: International Journal of Emerging Technology and Advanced Engineering (IJETAE)
Topic: Data Management
Format: PDF
Data mining is widely employed in business management and engineering. The major objective of data mining is to discover helpful and accurate information among a vast quantity of data, providing a orientation basis for decision makers. Data clustering is currently a very popular and frequently applied analytical method in data mining. DBSCAN is a traditional and widely-accepted density-based clustering method. It is used to find clusters of arbitrary shapes and sizes yet may have trouble with clusters of varying density. In this paper, the authors present a survey based on various density based clustering and various works proposed by numerous researchers.

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