Process-Specific Extensions for Enhanced Recommender Systems in Business Process Management
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-61003-5_24
Reference22 articles.
1. van der Aalst, W.M.P.: Process mining - data science in action, 2nd Edn. Springer, Cham (2016)
2. Aggarwal, C.C.: Recommender Systems - The Textbook. Springer, New York (2016). https://doi.org/10.1007/978-3-319-29659-3
3. Arias, M., Munoz-Gama, J., Sepúlveda, M.: A multi-criteria approach for team recommendation (2016)
4. Barba, I., Weber, B., Del Valle, C.: Supporting the optimized execution of business processes through recommendations. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) Business Process Management Workshops. BPM 2011, LNBIP, vol. 99, pp. 135–140. Springer, Berlin (2012). https://doi.org/10.1007/978-3-642-28108-2_12
5. Bidar, R., ter Hofstede, A., Sindhgatta, R., Ouyang, C.: Preference-based resource and task allocation in business process automation. In: Panetto, H., Debruyne, C., Hepp, M., Lewis, D., Ardagna, C., Meersman, R. (eds.) On the Move to Meaningful Internet Systems: OTM 2019 Conferences, OTM 2019, LNCS, vol. 11877, pp. 404–421. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33246-4_26
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