GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language Texts

Nils Freyer, Dustin Thewes, Matthias Meinecke

2023

Abstract

Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better results than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low.

Paper Citation

in Harvard Style

Freyer N., Thewes D. and Meinecke M. (2023). GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language Texts. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 335-342. DOI: 10.5220/0012084400003541

in Bibtex Style

@conference{data23,
author={Nils Freyer and Dustin Thewes and Matthias Meinecke},
title={GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language Texts},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={335-342},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012084400003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language Texts
SN - 978-989-758-664-4
AU - Freyer N.
AU - Thewes D.
AU - Meinecke M.
PY - 2023
SP - 335
EP - 342
DO - 10.5220/0012084400003541
PB - SciTePress