nach oben

Erschienen in:

2021 | OriginalPaper | Buchkapitel

A Rule-Based Recommendation Approach for Business Process Modeling

verfasst von : Diana Sola, Christian Meilicke, Han van der Aa, Heiner Stuckenschmidt

Erschienen in: Advanced Information Systems Engineering

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Business process modeling is a crucial, yet time-consuming and knowledge-intensive task. This is particularly the case when modeling a domain-specific process, which often requires the use of highly specialized terminology in a consistent manner. To alleviate these issues, the process modeling task can be supported by techniques that suggest how a model under development can be expanded. In this work, we provide such suggestions through a rule-based activity recommendation approach, which suggests suitable activities to be included at a user-defined position in a process model. A benefit of our rule-based work over other approaches is that it accompanies recommendations with explanations, providing additional transparency and trustworthiness to users. Furthermore, through comprehensive evaluation experiments on a large set of real-world process models, we show that our rule-based approach outperforms other methods, including an embedding-based one.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Digging for Gold in RPA Projects – A Quantifiable Method to Identify and Prioritize Suitable RPA Process Candidates

Nächstes Kapitel Sketch2BPMN: Automatic Recognition of Hand-Drawn BPMN Models

For proprietary reasons, requests for the source code of the employed implementation should be submitted to diana.sola@sap.com.

Note that with the decision to keep these different revisions, we follow the setup used to evaluate RLRecommender.

For brevity, we use template and template group interchangeably in this section.

Agrawal, R., Imieliński, T., Swami, A.: Mining association rules between sets of items in large databases. In: SIGMOD, pp. 207–216. ACM (1993)

Blockeel, H., De Raedt, L.: Top-down induction of first-order logical decision trees. Artif. Intell. 101(1–2), 285–297 (1998)MathSciNetCrossRef

Cao, B., Yin, J., Deng, S., Wang, D., Wu, Z.: Graph-based workflow recommendation: on improving business process modeling. In: CIKM, pp. 1527–1531. ACM (2012)

De Raedt, L.: Logical and Relational Learning. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68856-3

Dehaspe, L., De Raedt, L.: Mining association rules in multiple relations. In: Lavrač, N., Džeroski, S. (eds.) ILP 1997. LNCS, vol. 1297, pp. 125–132. Springer, Heidelberg (1997). https://doi.org/10.1007/3540635149_40CrossRef

Deng, S., et al.: A recommendation system to facilitate business process modeling. IEEE Trans. Cybern. 47(6), 1380–1394 (2017)CrossRef

Dijkman, R., Dumas, M., García-Bañuelos, L.: Graph matching algorithms for business process model similarity search. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 48–63. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03848-8_5CrossRef

Dijkman, R.M., Dumas, M., Ouyang, C.: Semantics and analysis of business process models in BPMN. Inf. Softw. Technol. 50(12), 1281–1294 (2008)CrossRef

Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management. Springer, Berlin (2013). https://doi.org/10.1007/978-3-642-33143-5

10.

Fellmann, M., Zarvic, N., Metzger, D., Koschmider, A.: Requirements catalog for business process modeling recommender systems. In: WI, pp. 393–407 (2015)

11.

Frederiks, P.J., Van der Weide, T.P.: Information modeling: the process and the required competencies of its participants. Data Knowl. Eng. 58(1), 4–20 (2006)CrossRef

12.

Friedrich, F., Mendling, J., Puhlmann, F.: Process model generation from natural language text. In: Mouratidis, H., Rolland, C. (eds.) CAiSE 2011. LNCS, vol. 6741, pp. 482–496. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21640-4_36CrossRef

13.

Galárraga, L.A., Teflioudi, C., Hose, K., Suchanek, F.: AMIE: association rule mining under incomplete evidence in ontological knowledge bases. In: WWW, pp. 413–422 (2013)

14.

Jannach, D., Fischer, S.: Recommendation-based modeling support for data mining processes. In: RecSys, pp. 337–340 (2014)

15.

Jannach, D., Jugovac, M., Lerche, L.: Supporting the design of machine learning workflows with a recommendation system. ACM Trans. Interact. Intell. Syst. 6(1), 1–35 (2016)CrossRef

16.

Li, Y., et al.: An efficient recommendation method for improving business process modeling. IEEE Trans. Ind. Inf. 10(1), 502–513 (2014)CrossRef

17.

Meilicke, C., Chekol, M.W., Ruffinelli, D., Stuckenschmidt, H.: Anytime bottom-up rule learning for knowledge graph completion. In: IJCAI, pp. 3137–3143. AAAI Press (2019)

18.

Model collection of the Business Process Management Academic Initiative. http://bpmai.org/

19.

Quinlan, J.R.: Learning logical definitions from relations. Mach. Learn. 5(3), 239–266 (1990)

20.

Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 3 edn. Prentice Hall (2010)

21.

Sola, D.: Towards a rule-based recommendation approach for business process modeling. In: Hacid, H., et al. (eds.) Service-Oriented Computing – ICSOC 2020 Workshops, ICSOC 2020. Lecture Notes in Computer Science, vol. 12632. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-76352-7_4

22.

Wang, H., Wen, L., Lin, L., Wang, J.: RLRecommender: a representation-learning-based recommendation method for business process modeling. In: Pahl, C., Vukovic, M., Yin, J., Yu, Q. (eds.) ICSOC 2018. LNCS, vol. 11236, pp. 478–486. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03596-9_34CrossRef

23.

Zhang, Y., Chen, X.: Explainable recommendation: a survey and new perspectives. arXiv preprint arXiv:1804.11192 (2018)

Titel: A Rule-Based Recommendation Approach for Business Process Modeling
verfasst von: Diana Sola
Christian Meilicke
Han van der Aa
Heiner Stuckenschmidt
Verlag: Springer International Publishing
Buch: Advanced Information Systems Engineering
Print ISBN: 978-3-030-79381-4

Electronic ISBN: 978-3-030-79382-1

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-79382-1_20

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner