@inproceedings{a26be69e4f2541e6868c9b86cd8710cd,
title = "Study of the US road network based on social network analysis",
abstract = "The complexity of big data structures and networks demands more research in terms of analysing and representing data for a better comprehension and usage. In this regard, there are several types of model to represent a structure. The aim of this article is to use a social network topology to analyse road network for the following States in the United States (US): California, Pennsylvania and Texas. Our approach mainly focuses on clustering of road network data in order to create 'communities'.",
keywords = "Community structure, GraphX, MLib, Road network, Social network analysis (SNA), Spark, Tableau",
author = "Mambou, {Elie Ngomseu} and Samuel Nlend and Harold Liu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; IEEE AFRICON 2017 ; Conference date: 18-09-2017 Through 20-09-2017",
year = "2017",
month = nov,
day = "3",
doi = "10.1109/AFRCON.2017.8095614",
language = "English",
series = "2017 IEEE AFRICON: Science, Technology and Innovation for Africa, AFRICON 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "974--978",
editor = "Cornish, {Darryn R.}",
booktitle = "2017 IEEE AFRICON",
address = "United States",
}