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Assisted Declarative Process Creation from Natural Language Descriptions

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Standard

Assisted Declarative Process Creation from Natural Language Descriptions. / Lopez, Hugo Andres; Marquard, Morten; Muttenthaler, Lukas; Strømsted, Rasmus.

2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW). IEEE Computer Society Press, 2019. p. 96-99.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Lopez, HA, Marquard, M, Muttenthaler, L & Strømsted, R 2019, Assisted Declarative Process Creation from Natural Language Descriptions. in 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW). IEEE Computer Society Press, pp. 96-99. https://doi.org/10.1109/EDOCW.2019.00027

APA

Lopez, H. A., Marquard, M., Muttenthaler, L., & Strømsted, R. (2019). Assisted Declarative Process Creation from Natural Language Descriptions. In 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW) (pp. 96-99). IEEE Computer Society Press. https://doi.org/10.1109/EDOCW.2019.00027

Vancouver

Lopez HA, Marquard M, Muttenthaler L, Strømsted R. Assisted Declarative Process Creation from Natural Language Descriptions. In 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW). IEEE Computer Society Press. 2019. p. 96-99 https://doi.org/10.1109/EDOCW.2019.00027

Author

Lopez, Hugo Andres ; Marquard, Morten ; Muttenthaler, Lukas ; Strømsted, Rasmus. / Assisted Declarative Process Creation from Natural Language Descriptions. 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW). IEEE Computer Society Press, 2019. pp. 96-99

Bibtex

@inproceedings{25ed74636bbf4dcb9db4b9370ab19473,
title = "Assisted Declarative Process Creation from Natural Language Descriptions",
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 descriptionsare 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 theserisks, 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.",
keywords = "Declarative Business Processes, DCR Graphs, NLP, Natural Language Processing, Dual Coding, Business Process Management",
author = "Lopez, {Hugo Andres} and Morten Marquard and Lukas Muttenthaler and Rasmus Str{\o}msted",
year = "2019",
month = nov
day = "21",
doi = "10.1109/EDOCW.2019.00027",
language = "English",
pages = "96--99",
booktitle = "2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW)",
publisher = "IEEE Computer Society Press",
address = "United States",

}

RIS

TY - GEN

T1 - Assisted Declarative Process Creation from Natural Language Descriptions

AU - Lopez, Hugo Andres

AU - Marquard, Morten

AU - Muttenthaler, Lukas

AU - Strømsted, Rasmus

PY - 2019/11/21

Y1 - 2019/11/21

N2 - 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 descriptionsare 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 theserisks, 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.

AB - 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 descriptionsare 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 theserisks, 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.

KW - Declarative Business Processes

KW - DCR Graphs

KW - NLP

KW - Natural Language Processing

KW - Dual Coding

KW - Business Process Management

UR - http://lopezacosta.net/Publications_files/EDOC19.pdf

U2 - 10.1109/EDOCW.2019.00027

DO - 10.1109/EDOCW.2019.00027

M3 - Article in proceedings

SP - 96

EP - 99

BT - 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW)

PB - IEEE Computer Society Press

ER -

ID: 84554768