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An algorithm to compute data diversity index in spatial networks.

Authors :
Agryzkov, Taras
Tortosa, Leandro
Vicent, Jose F.
Source :
Applied Mathematics & Computation. Nov2018, Vol. 337, p63-75. 13p.
Publication Year :
2018

Abstract

Diversity is an important measure that according to the context, can describe different concepts of general interest: competition, evolutionary process, immigration, emigration and production among others. It has been extensively studied in different areas, as ecology, political science, economy, sociology and others. The quality of spatial context of the city can be gauged through this measure. The spatial context with its corresponding dataset can be modelled using spatial networks. Consequently, this allows us to study the diversity of data present in this specific type of networks. In this paper we propose an algorithm to measure diversity in spatial networks based on the topology and the data associated to the network. In the experiments developed with networks of different sizes, it is observed that the proposed index is independent of the size of the network, but depends on its topology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00963003
Volume :
337
Database :
Academic Search Index
Journal :
Applied Mathematics & Computation
Publication Type :
Academic Journal
Accession number :
130690474
Full Text :
https://doi.org/10.1016/j.amc.2018.04.068