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Survey on DBSCAN Algorithm in Distributed Data Mining using Map Reduce


Chaitali Patel , Akhilesh Bansiya


Data Mining, Map-Reduce, Big Data


Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining, also called knowledge discovery in databases. Clustering is a grouping of objects into classes such as object in same cluster is similar and objects in different clusters are dissimilar. Clustering can also be used for anomaly detection. In the data mining we use DBSCAN algorithm for clustering method. DBSCAN is one the density based algorithm but most of the time lacking in the performance, run time complexity and not gives proper output in the multi density dataset. To overcome from this problem many algorithms are developed and here present literature survey on those algorithms. This paper also gives the details of different types of DBSCAN Algorithm.

Other Details

Paper ID: IJSRDV4I80137
Published in: Volume : 4, Issue : 8
Publication Date: 01/11/2016
Page(s): 193-194

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