A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

working with amazons3 ,t2.micro Ubuntu instance, Amazon AutoScaling group, Map-Reduce and Parallelize the implementation of K-means and DBSCAN algorithm using Hadoop and Map reduce cluster ...

Comprehensive and reproducible comparison of Traditional DBSCAN versus an Improved DBSCAN algorithm for small-object detection in autonomous driving scenarios using LiDAR point cloud data. The ...

Abstract: DBSCAN is a well-known clustering algorithm which is based on density and is able to identify arbitrary shaped clusters and eliminate noise data. However, existing parallel implementation ...

Abstract: The study is conducted on shopping mall data and utilized DBSCAN clustering for customer segmentation for data analysis. Data is obtained from the Kaggle database. Segmentation was carried ...