Topographic Connectionist Unsupervised Learning for RFID Behavior Data Mining

Guénaël Cabanes, Younès Bennani, Claire Chartagnat, Dominique Fresneau

2008

Abstract

Radio Frequency IDentification (RFID) is an advanced tracking technology that can be used to study the spatial organization of animal societies. The aim of this work is to build a new RFID-based autonomous system to follow individuals spatio-temporal activity, which is not currently available, and to develop new tools for automatic data mining. We study here how to transform these data to obtain knowledge about the division of labor and intra-colonial cooperation and conflict in an ant colony by developing a new unsupervised learning data mining method (DS2L-SOM : Density-based Simultaneous Two-Level - Self Organizing Map) to find homogeneous clusters (i.e., sets of individual witch share a distinctive behavior). This method is very fast and efficient and it also allows a very useful visualization of results.

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Paper Citation


in Harvard Style

Cabanes G., Bennani Y., Chartagnat C. and Fresneau D. (2008). Topographic Connectionist Unsupervised Learning for RFID Behavior Data Mining . In Proceedings of the 2nd International Workshop on RFID Technology - Concepts, Applications, Challenges - Volume 1: IWRT, (ICEIS 2008) ISBN 978-989-8111-46-3, pages 63-72. DOI: 10.5220/0001733400630072


in Bibtex Style

@conference{iwrt08,
author={Guénaël Cabanes and Younès Bennani and Claire Chartagnat and Dominique Fresneau},
title={Topographic Connectionist Unsupervised Learning for RFID Behavior Data Mining},
booktitle={Proceedings of the 2nd International Workshop on RFID Technology - Concepts, Applications, Challenges - Volume 1: IWRT, (ICEIS 2008)},
year={2008},
pages={63-72},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001733400630072},
isbn={978-989-8111-46-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Workshop on RFID Technology - Concepts, Applications, Challenges - Volume 1: IWRT, (ICEIS 2008)
TI - Topographic Connectionist Unsupervised Learning for RFID Behavior Data Mining
SN - 978-989-8111-46-3
AU - Cabanes G.
AU - Bennani Y.
AU - Chartagnat C.
AU - Fresneau D.
PY - 2008
SP - 63
EP - 72
DO - 10.5220/0001733400630072