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Authors: Renato César Borges Ferreira 1 ; Lucinéia Heloisa Thom 1 and Marcelo Fantinato 2

Affiliations: 1 Federal University of Rio Grande do Sul, Brazil ; 2 University of São Paulo, Brazil

ISBN: 978-989-758-249-3

Keyword(s): Process Models, Natural Language Processing, Process Element, Business Process Management, Business Process Model and Notation, Process Modeling.

Abstract: In organizations, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this paper proposes a semi-automatic approach to identify process elements in natural language texts, which may include process descriptions. Therefore, based on the study of natural language processing, we defined a set of mapping rules to identify process elements in texts. In addition, we developed a prototype which is able to semi-automatically identify process elements in texts. Our evaluation shows promising results. The analyses of 56 texts revealed 91.92% accuracy and a case study showed that 93.33% of the participants agree with the mapping rules.

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Paper citation in several formats:
Ferreira R., Thom L. and Fantinato M. (2017). A Semi-automatic Approach to Identify Business Process Elements in Natural Language Texts.In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 978-989-758-249-3, pages 250-261. DOI: 10.5220/0006305902500261

@conference{iceis17,
author={Renato César Borges Ferreira and Lucinéia Heloisa Thom and Marcelo Fantinato},
title={A Semi-automatic Approach to Identify Business Process Elements in Natural Language Texts},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2017},
pages={250-261},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006305902500261},
isbn={978-989-758-249-3},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - A Semi-automatic Approach to Identify Business Process Elements in Natural Language Texts
SN - 978-989-758-249-3
AU - Ferreira R.
AU - Thom L.
AU - Fantinato M.
PY - 2017
SP - 250
EP - 261
DO - 10.5220/0006305902500261

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