Assisted Declarative Process Creation from Natural Language Descriptions
- Hugo Andres Lopez,
- Morten Marquard,
- Lukas Muttenthaler,
- Rasmus Strømsted
- ,
- DCR Solutions,
- University of Copenhagen
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
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Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 96-99 (4 pages)Publication milestones
- Published - 21/11/2019
Publication status
Published - 21/11/2019
Publisher
IEEE, United StatesISBN (Electronic)
978-1-7281-4598-3Publication IDs
- Scopus: 85075978401
Host publication title
2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW)Abstract
In this paper, we report recent advances on user support for declarative process generation from natural language descriptions. The Process Highlighter is a hybrid modelling tool that facilitates the (manual) creation of Dynamic Response Condition (DCR) graphs directly from text documents, supporting non-technical users in the adoption of declarative process models. While some process descriptions
are a few paragraphs long, others, such as the ones coming from municipal governments and legal bodies might contain several pages. Some aspects that undermine the adoption of hybrid modelling techniques and their promised one-to-one correspondence between texts and process models are the length of the texts, the inconsistent use of terms, and the difficulty in identifying textual elements that correspond to elements in a declarative process model. To mitigate these
risks, we have implemented major additions in the Process Highlighter for industrial usage. The principal change is the inclusion of Natural Language Processing (NLP) techniques to support users in the identification of roles, activities and constraints. This, combined with the modelling, simulation and verification tools already existing in the framework, support the users in providing process models that are better aligned with their specifications, in a shorter time. These features are motivated from empirical observations of the use of the Process Highlighter in groups of caseworkers and students of process engineering in Danish universities.
are a few paragraphs long, others, such as the ones coming from municipal governments and legal bodies might contain several pages. Some aspects that undermine the adoption of hybrid modelling techniques and their promised one-to-one correspondence between texts and process models are the length of the texts, the inconsistent use of terms, and the difficulty in identifying textual elements that correspond to elements in a declarative process model. To mitigate these
risks, we have implemented major additions in the Process Highlighter for industrial usage. The principal change is the inclusion of Natural Language Processing (NLP) techniques to support users in the identification of roles, activities and constraints. This, combined with the modelling, simulation and verification tools already existing in the framework, support the users in providing process models that are better aligned with their specifications, in a shorter time. These features are motivated from empirical observations of the use of the Process Highlighter in groups of caseworkers and students of process engineering in Danish universities.
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Accepted author manuscript, 416.34 KB
