BPM2Text: A language independent framework for Business Process Models to Natural Language Text

Authors

  • Raphael De Almeida Rodrigues UNIRIO - Universidade Federal do Estado do Rio de Janeiro
  • Leonardo Guerreiro Azevedo UNIRIO (Universidade Federal do Estado do Rio de Janeiro)
  • Kate Cerqueira Revoredo UNIRIO (Universidade Federal do Estado do Rio de Janeiro)

DOI:

https://doi.org/10.5753/isys.2016.320

Abstract

The proper representation of a Business process is important for its execution and understanding. BPMN has been used as the standard notation for business process models, however domain specialists, which are experts in the business, do not have necessarily the modeling skills to easily read a business process model. It is easier for them to read in natural language. In this work, we propose a language-independent framework, instantiated using Java standard technology, for generating automatically natural language texts from business process models. A case study was conducted to evaluate the quality of the generated text. We found empirical support that the textual work instructions can be considered equivalent, in terms of knowledge representation, to process models represented in BPMN. Regarding the framework output quality (textual descriptions) 86% of the subjects claims that it vary from excellent to good.

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Author Biographies

Raphael De Almeida Rodrigues, UNIRIO - Universidade Federal do Estado do Rio de Janeiro

Formado pela UNIRIO, realizando mestrado na linha de pesquisa de Distribuição e Redes na mesma instituição.

Leonardo Guerreiro Azevedo, UNIRIO (Universidade Federal do Estado do Rio de Janeiro)

Leonardo is Professor at Applied Informatics Department (DIA) at Federal University of State of Rio de Janeiro (UNIRIO) and researcher of Graduate Program in Informatics (PPGI/UNIRIO). He received D.Sc and M.Sc. degree from the Graduate School of Engineering (PESC/COPPE) - Federal University of Rio de Janeiro (UFRJ) and Bachelor in Informatics degree from Federal University of Rio de Janeiro (UFRJ). Nowadays, he is Professor at Federal University of State of Rio de Janeiro (UNIRIO) where he researches, teaches and supervise master and bachelor students in different subjects, such as Software Engineering, Database, SOA, BPM, MDA, Business Rules, Spatial Database etc. Since 2007, he works for NP2Tec (Research and Practice Group in Information Technology) as consultant working as Senior Researcher and Project Manager for Petrobras in Business Rules, Security in Database, SOA, BPM and Ontology. From 2000 to 2004 and 2005 to 2007, he worked for COPPETEC foundation as consultant for Brazilian Defense Ministry, Brazilian Navy and Embratel as Project Manager and System Analyst supervising software development projects.

Kate Cerqueira Revoredo, UNIRIO (Universidade Federal do Estado do Rio de Janeiro)

Bacharel em Matemática pela Universidade Federal do Rio de Janeiro (1999), mestre em Engenharia de Sistemas e Computação pela Universidade Federal do Rio de Janeiro (2002), doutora em Engenharia de Sistemas e Computação na COPPE pela Universidade Federal do Rio de Janeiro (2009), tendo feito doutorado sanduiche por 6 meses (2006) no Albert-Ludwigs Universität Freiburg (RFA), Alemanha. Atualmente é professora do Departamento de Informática Aplicada da Universidade Federal do Estado do Rio de Janeiro, e atua no Programa de Pós-Graduação em Informática. Atua na área de Ciência da Computação, com ênfase em Inteligência Artificial principalmente nos seguintes temas: representação de conhecimento e raciocínio, alinhamento de ontologias, analise de redes sociais, aprendizado de maquina, aprendizado relacional (programação em lógica indutiva - ILP), aprendizado estatístico relacional (SRL), revisão de teoria, invenção de predicados, redes Bayesianas.

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Additional Files

Published

2016-12-29

How to Cite

Rodrigues, R. D. A., Azevedo, L. G., & Revoredo, K. C. (2016). BPM2Text: A language independent framework for Business Process Models to Natural Language Text. ISys - Brazilian Journal of Information Systems, 9(4), 38–56. https://doi.org/10.5753/isys.2016.320

Issue

Vol. 9 No. 4 (2016)

Section

Special issues articles