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Authors: Corrado Grappiolo 1 ; Eline Verwielen 2 and Nils Noorman 3

Affiliations: 1 ESI (TNO), Eindhoven and The Netherlands ; 2 Unaffiliated, Valkenswaard and The Netherlands ; 3 Philips Healthcare, Best and The Netherlands

ISBN: 978-989-758-351-3

Keyword(s): String Clustering, N-Grams, Operational Usage Modelling, System Verification Testing.

Abstract: Connected high-tech systems allow the gathering of operational data at unprecedented volumes. A direct benefit of this is the possibility to extract usage models, that is, a generic representations of how such systems are used in their field of application. Usage models are extremely important, as they can help in understanding the discrepancies between how a system was designed to be used and how it is used in practice. We interpret usage modelling as an unsupervised learning task and present a novel algorithm, hereafter called Growing N-Grams (GNG), which relies on n-grams — arguably the most popular modelling technique for natural language processing — to cluster and model, in a two-step rationale, a dataset of strings. We empirically compare its performance against some other common techniques for string processing and clustering. The gathered results suggest that the GNG algorithm is a viable approach to usage modelling.

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Paper citation in several formats:
Grappiolo, C.; Verwielen, E. and Noorman, N. (2019). The Growing N-Gram Algorithm: A Novel Approach to String Clustering.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 52-63. DOI: 10.5220/0007259200520063

@conference{icpram19,
author={Corrado Grappiolo. and Eline Verwielen. and Nils Noorman.},
title={The Growing N-Gram Algorithm: A Novel Approach to String Clustering},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={52-63},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007259200520063},
isbn={978-989-758-351-3},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - The Growing N-Gram Algorithm: A Novel Approach to String Clustering
SN - 978-989-758-351-3
AU - Grappiolo, C.
AU - Verwielen, E.
AU - Noorman, N.
PY - 2019
SP - 52
EP - 63
DO - 10.5220/0007259200520063

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