Abstract
Process Mining is a combination of business process management and machine learning, which automatically allows one to discover the process model, compare it with an existing process to verify its conformity, and improve it. With the frequent use of the web and social media, recommender systems are increasingly used to build customer fidelity and smartly simplify access to services. In this paper, we conduct a comparative study between the latest works focusing on how to improve recommender systems using process mining. This study is considered the first step toward developing a new framework based on configurable process mining.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Goossens, J., Demewez, T., Hassani. M.: Effective steering of customer journey via order-aware recommendation. In: International Conference on Data Mining Workshops 2018 (ICDMW), pp. 828–837. IEEE, Singapore (2018)
Epure, E.V., Ingvaldsen, J.E., Deneckere, R., Salinesi, C.: Process mining for recommender strategies support in news media. In: Tenth International Conference on Research Challenges in Information Science 2016 (RCIS), pp. 1–12. IEEE, France (2016)
Husin, H.S., Ismail, S.: Process mining approach to analyze user navigation behavior of a news website. In: The 4th International Conference on Information Science and Systems 2021, pp. 7–12. Association for Computing Machinery, Edinburgh United Kingdom (2021)
Poggi, N., Muthusamy, V., Carrera, D., Khalaf, R.: Business process mining from E-commerce web logs. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 65–80. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40176-3_7
Terragni, A., Hassani, M.: Analyzing customer journey with process mining: from discovery to recommendations. In: 6th International Conference on Future Internet of Things and Cloud 2018 (FiCloud), pp. 224–229. IEEE, Barcelona, Spain (2018)
Melville, P., Sindhwani, V.: Recommender systems. Encyclopedia of Machine Learning, pp. 829–838 (2011)
Hernandez, P., Garrigos, I., Mazon, J.-N.: Modeling Web logs to enhance the analysis of web usage data. In: Workshops on Database and Expert Systems Applications 2010, pp. 297‑301. IEEE, Bilbao, Spain (2010)
Bernard, G., Andritsos, P.: CJM-ab: abstracting customer journey maps using process mining. In: Mendling, J., Mouratidis, H. (eds.) CAiSE 2018. LNBIP, vol. 317, pp. 49–56. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-92901-9_5
Bernard, G., Andritsos, P.: A Process mining based model for customer journey mapping. In: Proceedings of the forum and doctoral consortium papers. In: 29th international conference on advanced information systems engineering 2017 vol. 1848. pp. 46–56. CEUR-WS (2017)
Wheelock, A., Miraldo, M., Parand, A., Vincent, C., Sevdalis, N.: Journey to vaccination: a protocol for a multinational qualitative study. BMJ Open 4(1), e004279 (2014)
Van Der Aalst, W.: Process mining: overview and opportunities. ACM Trans. Manag. Inf. Syst. (TMIS) 3(2), 1–17 (2012)
Sikal, R., Sbai, H., Kjiri, L.: Configurable process mining: variability discovery approach. In: 5th International Congress on Information Science and Technology 2018 (CiSt), pp. 137–142. IEEE, Marrakech, Morocco (2018)
Epure, E.V., Deneckere, R., Salinesi, C., Kille, B., Ingvaldsen, J.: Devising news recommendation strategies with process mining support. In: Interdisciplinary Workshop on Recommender Systems, pp. 1–7 (2017)
Terragni, A., Hassani, M.: Optimizing customer journey using process mining and sequence-aware recommendation. In: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, pp. 57–65. ACM, Limassol Cyprus (2019)
Filipowska, A., Kaluzny, P., Skrzypek, M.: Improving user experience in e-commerce by application of process mining techniques. Zeszyty Naukowe Politechniki Częstochowskiej Zarządzanie 33(1), 30–40 (2019). https://doi.org/10.17512/znpcz.2019.1.03
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
El Alama, I., Sbai, H. (2023). Applying Process Mining in Recommender System: A Comparative Study. In: Lazaar, M., En-Naimi, E.M., Zouhair, A., Al Achhab, M., Mahboub, O. (eds) Proceedings of the 6th International Conference on Big Data and Internet of Things. BDIoT 2022. Lecture Notes in Networks and Systems, vol 625. Springer, Cham. https://doi.org/10.1007/978-3-031-28387-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-28387-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-28386-4
Online ISBN: 978-3-031-28387-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)