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Applying Process Mining in Recommender System: A Comparative Study

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Proceedings of the 6th International Conference on Big Data and Internet of Things (BDIoT 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 625))

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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.

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Author information

Authors and Affiliations

  1. Mathematics, Computer Science, and Application Laboratory (LMCSA), University Hassan II of Casablanca, Mohammedia, Morocco

    Imane El Alama & Hanae Sbai

Authors
  1. Imane El Alama
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  2. Hanae Sbai
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Corresponding author

Correspondence to Imane El Alama .

Editor information

Editors and Affiliations

  1. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  2. FST, Abdelmalek Essaâdi University, Tangier, Morocco

    El Mokhtar En-Naimi

  3. FST, Abdelmalek Essaâdi University, Tangier, Morocco

    Abdelhamid Zouhair

  4. ENSA, Abdelmalek Essaâdi University, Tetuan, Morocco

    Mohammed Al Achhab

  5. ENSA, Abdelmalek Essaadi University, Tetouan, Morocco

    Oussama Mahboub

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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

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