Uma Ferramenta para Modelagem de Processos de Negócios com base em Padrões de Recomendação
Resumo
A Notação de Modelagem de Processos de Negócios (BPMN) é a especificação desenvolvida pela OMG para representar processos de negócios no paradigma de modelagem imperativa. A criação de diagramas BPMN continua sendo uma atividade dependente do desempenho humano e do conhecimento do domínio da aplicação. Nesse contexto, este trabalho propõe uma ferramenta de apoio à modelagem de processos baseada no conceito de Padrão de Recomendação com o objetivo de gerar recomendações posicionais em um processo interativo integrado à atividade de modelagem. O estudo de caso mostra que cada recomendação sugerida é sensível ao estado atual do modelo. O modelo final é sintático e semanticamente correto.Referências
Andaloussi, A. A., Burattin, A., Slaats, T., Kindler, E., and Weber, B. (2020). On the declarative paradigm in hybrid business process representations: A conceptual framework and a systematic literature study. Information Systems, 91:101505.
Barba, I., Del Valle, C., Weber, B., and Jimenez, A. (2013). Automatic generation of optimized business process models from constraint-based specifications. International Journal of Cooperative Information Systems, 22(02):1350009.
Abdelhadi, A., Khawar, A. and Clancy, T.C. (2015) ‘Optimal downlink power allocation in cellular networks’, Physical Communication,Vol. 17, pp. 1–14,
Costa, M. B. and Tamzalit, D. (2017). Recommendation patterns for business process imperative modeling. In Proceedings of the Symposium on Applied Computing, pages 735–742. ACM.
Dijkman, R., Dumas, M., Van Dongen, B., Ka¨arik, R., and Mendling, J. (2011). Similarity of Business Process Models: Metrics and Evaluation. Information Systems, 36(2):498–516.
Fahland, D., Lubke, D., Mendling, J., Reijers, H., Weber, B., Weidlich, M., and Zugal, S. (2009). Declarative versus imperative process modeling languages: The issue of understandability. In Enterprise, Business-Process and Information Systems Modeling, pages 353–366. Springer
Fellmann, M., Metzger, D., Jannaber, S., Zarvic, N., and Thomas, O. (2018). Process modeling recommender systems. Business & Information Systems Engineering, 60(1):21–38.
Goedertier, S., Vanthienen, J., and Caron, F. (2015). Declarative business process modelling: principles and modelling languages. Enterprise Information Systems, 9(2):161–185.
Jannach, D. and Fischer, S. (2014). Recommendation-based modeling support for data mining processes. In Proceedings of the 8th ACM Conference on Recommender systems, pages 337–340.
Jannach, D., Jugovac, M., and Lerche, L. (2015). Adaptive recommendation-based modeling support for data analysis workflows. In Proceedings of the 20th International Conference on Intelligent User Interfaces, pages 252–262.
Koschmider, A., Hornung, T., and Oberweis, A. (2011). Recommendation-based Editor for Business Process Modeling. Data & Knowledge Engineering, 70(6):483–503.
Koschmider, A. and Oberweis, A. (2010). Designing business processes with a recommendation-based editor. In Handbook on Business Process Management 1, pages 299–312. Springer.
Leyh, C., Bley, K., and Seek, S. (2016). Elicitation of processes in business process management in the era of digitization – the same techniques as decades ago? In International Conference on Enterprise Resource Planning Systems, pages 42–56. Springer.
Li, Y., Cao, B., Xu, L., Yin, J., Deng, S., Yin, Y., and Wu, Z. (2014). An Efficient Recommendation Method for Improving Business Process Modeling. Industrial Informatics, IEEE Transactions on, 10(1):502–513.
Pereira, J. A., Matuszyk, P., Krieter, S., Spiliopoulou, M., and Saake, G. (2018). Personalized recommender systems for product-line configuration processes. Computer Languages, Systems & Structures, 54:451–471.
Schonenberg, H., Weber, B., van Dongen, B., and van der Aalst, W. (2008). Supporting Flexible Processes through Recommendations Based on History. In Business Process Management, pages 51–66. Springer.
van der Aalst, W. M. (2010). Business process simulation revisited. In Workshop on Enterprise and Organizational Modeling and Simulation, pages 1–14. Springer.
Wang, H. J. and Wu, H. (2011). Supporting Process Design for e-Business via an Integrated Process Repository. Information Technology and Management, 12(2):97–109.
Wang, J., Gui, S., and Cao, B. (2019). A process recommendation method using bag-offragments. International Journal of Intelligent Internet of Things Computing, 1(1):32–42.
Zhang, J., Liu, Q., and Xu, K. (2009). Flowrecommender: a workflow recommendation technique for process provenance. In Proceedings of the Eighth Australasian Data Mining Conference-Volume 101, pages 55–61. Australian Computer Society, Inc.
Barba, I., Del Valle, C., Weber, B., and Jimenez, A. (2013). Automatic generation of optimized business process models from constraint-based specifications. International Journal of Cooperative Information Systems, 22(02):1350009.
Abdelhadi, A., Khawar, A. and Clancy, T.C. (2015) ‘Optimal downlink power allocation in cellular networks’, Physical Communication,Vol. 17, pp. 1–14,
Costa, M. B. and Tamzalit, D. (2017). Recommendation patterns for business process imperative modeling. In Proceedings of the Symposium on Applied Computing, pages 735–742. ACM.
Dijkman, R., Dumas, M., Van Dongen, B., Ka¨arik, R., and Mendling, J. (2011). Similarity of Business Process Models: Metrics and Evaluation. Information Systems, 36(2):498–516.
Fahland, D., Lubke, D., Mendling, J., Reijers, H., Weber, B., Weidlich, M., and Zugal, S. (2009). Declarative versus imperative process modeling languages: The issue of understandability. In Enterprise, Business-Process and Information Systems Modeling, pages 353–366. Springer
Fellmann, M., Metzger, D., Jannaber, S., Zarvic, N., and Thomas, O. (2018). Process modeling recommender systems. Business & Information Systems Engineering, 60(1):21–38.
Goedertier, S., Vanthienen, J., and Caron, F. (2015). Declarative business process modelling: principles and modelling languages. Enterprise Information Systems, 9(2):161–185.
Jannach, D. and Fischer, S. (2014). Recommendation-based modeling support for data mining processes. In Proceedings of the 8th ACM Conference on Recommender systems, pages 337–340.
Jannach, D., Jugovac, M., and Lerche, L. (2015). Adaptive recommendation-based modeling support for data analysis workflows. In Proceedings of the 20th International Conference on Intelligent User Interfaces, pages 252–262.
Koschmider, A., Hornung, T., and Oberweis, A. (2011). Recommendation-based Editor for Business Process Modeling. Data & Knowledge Engineering, 70(6):483–503.
Koschmider, A. and Oberweis, A. (2010). Designing business processes with a recommendation-based editor. In Handbook on Business Process Management 1, pages 299–312. Springer.
Leyh, C., Bley, K., and Seek, S. (2016). Elicitation of processes in business process management in the era of digitization – the same techniques as decades ago? In International Conference on Enterprise Resource Planning Systems, pages 42–56. Springer.
Li, Y., Cao, B., Xu, L., Yin, J., Deng, S., Yin, Y., and Wu, Z. (2014). An Efficient Recommendation Method for Improving Business Process Modeling. Industrial Informatics, IEEE Transactions on, 10(1):502–513.
Pereira, J. A., Matuszyk, P., Krieter, S., Spiliopoulou, M., and Saake, G. (2018). Personalized recommender systems for product-line configuration processes. Computer Languages, Systems & Structures, 54:451–471.
Schonenberg, H., Weber, B., van Dongen, B., and van der Aalst, W. (2008). Supporting Flexible Processes through Recommendations Based on History. In Business Process Management, pages 51–66. Springer.
van der Aalst, W. M. (2010). Business process simulation revisited. In Workshop on Enterprise and Organizational Modeling and Simulation, pages 1–14. Springer.
Wang, H. J. and Wu, H. (2011). Supporting Process Design for e-Business via an Integrated Process Repository. Information Technology and Management, 12(2):97–109.
Wang, J., Gui, S., and Cao, B. (2019). A process recommendation method using bag-offragments. International Journal of Intelligent Internet of Things Computing, 1(1):32–42.
Zhang, J., Liu, Q., and Xu, K. (2009). Flowrecommender: a workflow recommendation technique for process provenance. In Proceedings of the Eighth Australasian Data Mining Conference-Volume 101, pages 55–61. Australian Computer Society, Inc.
Publicado
25/10/2021
Como Citar
LUCAS, Arthur Chisté; KOMATI, Karin S.; COSTA, Mateus Conrad Barcellos da.
Uma Ferramenta para Modelagem de Processos de Negócios com base em Padrões de Recomendação. In: ESCOLA REGIONAL DE INFORMÁTICA DE GOIÁS (ERI-GO), 9. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 82-95.
DOI: https://doi.org/10.5753/erigo.2021.18435.
