Towards Association Rules as a Predictive Tool for Geospatial Areas Evolution

Asma Gharbi, Cyril De Runz, Sami Faiz, Herman Akdag

2016

Abstract

Although it was basically presented as an exploratory tool rather than a predictive tool, numerous follow up researches have enhanced association rule mining, which contributes in making it a powerful predictive tool. In this context, this paper review the main advances in this datamining technique, then attempts to describe how they can, practically, be harnessed to deal with problems such as the prediction of geographical areas evolution.

Paper Citation

in Harvard Style

Gharbi A., De Runz C., Faiz S. and Akdag H. (2016). Towards Association Rules as a Predictive Tool for Geospatial Areas Evolution . In Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-188-5, pages 201-206. DOI: 10.5220/0005914202010206

in Bibtex Style

@conference{gistam16,
author={Asma Gharbi and Cyril De Runz and Sami Faiz and Herman Akdag},
title={Towards Association Rules as a Predictive Tool for Geospatial Areas Evolution},
booktitle={Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2016},
pages={201-206},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005914202010206},
isbn={978-989-758-188-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - Towards Association Rules as a Predictive Tool for Geospatial Areas Evolution
SN - 978-989-758-188-5
AU - Gharbi A.
AU - De Runz C.
AU - Faiz S.
AU - Akdag H.
PY - 2016
SP - 201
EP - 206
DO - 10.5220/0005914202010206