MINING TIMED SEQUENCES WITH TOM4L FRAMEWORK

Nabil Benayadi, Marc Le Goc

2010

Abstract

We introduce the problem of mining sequential patterns in large database of sequences using a Stochastic Approach. An example of patterns we are interested in is : 50% of cases of engine stops in the car are happened between 0 and 2 minutes after observing a lack of the gas in the engine, produced between 0 and 1 minutes after the fuel tank is empty. We call this patterns “signatures”. Previous research have considered some equivalent patterns, but such work have three mains problems : (1) the sensibility of their algorithms with the value of their parameters, (2) too large number of discovered patterns, and (3) their discovered patterns consider only ”after“ relation (succession in time) and omit temporal constraints between elements in patterns. To address this issue, we present TOM4L process (Timed Observations Mining for Learning process) which uses a stochastic representation of a given set of sequences on which an inductive reasoning coupled with an abductive reasoning is applied to reduce the space search. The results obtained with an application on very complex real world system are also presented to show the operational character of the TOM4L process.

Paper Citation

in Harvard Style

Benayadi N. and Le Goc M. (2010). MINING TIMED SEQUENCES WITH TOM4L FRAMEWORK . In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8425-05-8, pages 111-120. DOI: 10.5220/0002958401110120

in Bibtex Style

@conference{iceis10,
author={Nabil Benayadi and Marc Le Goc},
title={MINING TIMED SEQUENCES WITH TOM4L FRAMEWORK},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2010},
pages={111-120},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002958401110120},
isbn={978-989-8425-05-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - MINING TIMED SEQUENCES WITH TOM4L FRAMEWORK
SN - 978-989-8425-05-8
AU - Benayadi N.
AU - Le Goc M.
PY - 2010
SP - 111
EP - 120
DO - 10.5220/0002958401110120