Journal of Software Engineering and Applications

Volume 6, Issue 7 (July 2013)

ISSN Print: 1945-3116   ISSN Online: 1945-3124

Google-based Impact Factor: 1.22  Citations  h5-index & Ranking

New Topological Approaches for Data Granulation

HTML  Download Download as PDF (Size: 169KB)  PP. 1-6  
DOI: 10.4236/jsea.2013.67B001    3,758 Downloads   5,365 Views  Citations


Data granulation is a good tool of decision making in various types of real life applications. The basic ideas of data granulation have appeared in many fields, such as interval analysis, quantization, rough set theory, Dempster-Shafer theory of belief functions, divide and conquer, cluster analysis, machine learning, databases, information retrieval, and many others. In this paper, we initiate some new topological tools for data granulation using rough set approximations. Moreover, we define some topological measures of data granulation in topological I formation systems. Topological generalizations using δβ-open sets and their applications of information granulation are developed.

Share and Cite:

A. S. Salama and O. G. Elbarbary, "New Topological Approaches for Data Granulation," Journal of Software Engineering and Applications, Vol. 6 No. 7B, 2013, pp. 1-6. doi: 10.4236/jsea.2013.67B001.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.