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DOI: 10.14569/IJACSA.2019.0100380
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Density based Clustering Algorithm for Distributed Datasets using Mutual k-Nearest Neighbors

Author 1: Ahmed Salim
Author 2:

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 3, 2019.

  • Abstract and Keywords
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Abstract: Privacy and security have always been a concern that prevents the sharing of data and impedes the success of many projects. Distributed knowledge computing, if done correctly, plays a key role in solving such a problem. The main goal is to obtain valid results while ensuring the non-disclosure of data. Density-based clustering is a powerful algorithm in analyzing uncertain data that naturally occur and affect the performance of many applications like location-based services. Nowadays, a huge number of datasets have been introduced for researchers which involve high-dimensional data points with varying densities. Such datasets contain data points with high-density regions surrounded by data points with sparse density. The existing clustering approaches handle these situations inefficiently, especially in the context of distributed data. In this paper, we design a new decomposable density-based clustering algorithm for distributed datasets (DDBC). DDBC utilizes the concept of mutual k-nearest neighbor relationship to cluster distributed datasets with different density. The proposed DDBC algorithm is capable of preserving the privacy and security of data on each site by requiring a minimal number of transmissions to other sites.

Keywords: Privacy; mutual k-nearest neighbor; Density-based; clustering; security; DDBC

Ahmed Salim and , “Density based Clustering Algorithm for Distributed Datasets using Mutual k-Nearest Neighbors” International Journal of Advanced Computer Science and Applications(IJACSA), 10(3), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100380

@article{Salim2019,
title = {Density based Clustering Algorithm for Distributed Datasets using Mutual k-Nearest Neighbors},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100380},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100380},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {3},
author = {Ahmed Salim and }
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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