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Slim-Tree Clustering Large Application based on Randomized Search (STCLARANS) Algorithm Simulator


Ricardo Q. Camungao
Abstract

The Slim-Tree Clustering Large Application dependent on Randomized Search (STCLARANS) Algorithm is a k-medoids based calculation which was created through incorporating the Slim-Tree methods in its bunching procedure. It beats the grouping execution of the Clustering Large Application dependent on Randomized Search (CLARANS) Algorithm and the STCLARANS produce better nature of the bunched yield. This paper addresses the tasks of development of the program interface of the STCLARANS Algorithms using the different software and hardware development methods and tools and named as STCLARANS Simulator. Testing the functionalities of the simulator for dataset loader, Slim-Tree computation, clustering output and visual presentation of the clustered objects was made possible using a real dataset. Moreover, output of the simulator can use as basis to aide top management in decision making.

Volume 11 | 12-Special Issue

Pages: 1253-1258

DOI: 10.5373/JARDCS/V11SP12/20193333