A Nature-Inspired Tree Communication Clustering Algorithm for Clustering the Text Documents
Abstract
The Wood Wide Web is an emerging research area for the analysis of various fields like networking, machine learning, data science, etc. In this research, the nature-inspired novel approach is proposed for clustering the documents based on communication between the groups of trees. The experimental result shows that the proposed Tree Communication Clustering Algorithm (TCCA) performs better than benchmark K-Means and Rough K-Means Clustering Algorithms. In the future, the TCCA approach can be hybridized with soft computing techniques for clustering various data sets like image, medical, signal, etc.