Publications

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Filters: Keyword is Data mining  [Clear All Filters]
2022
A. Hmami, Sbaï, H., et Fredj, M., « Applying change tree method in configurable process mining », in 2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2022, 2022.
M. Z. Wadghiri, Idri, A., T. Idrissi, E., et Hakkoum, H., « Ensemble blood glucose prediction in diabetes mellitus: A review », Computers in Biology and Medicine, vol. 147, 2022.
S. Baina et Rihi, A., « NEW INSIGHT OF DATA MINING-BASED FRAUD DETECTION IN FINANCIAL IT-SYSTEMS », in Proceedings of the 15th IADIS International Conference Information Systems 2022, IS 2022, 2022, p. 73-80.
2021
H. Hakkoum, Idri, A., et Abnane, I., « Assessing and Comparing Interpretability Techniques for Artificial Neural Networks Breast Cancer Classification », Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 9, p. 587-599, 2021.
B. ElOuassif, Idri, A., Hosni, M., et Abran, A., « Classification techniques in breast cancer diagnosis: A systematic literature review », Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 9, p. 50-77, 2021.
Y. Sabri, Bahja, F., Siham, A., et Maizate, A., « Cloud Computing in Remote Sensing: Big Data Remote Sensing Knowledge Discovery and Information Analysis », International Journal of Advanced Computer Science and Applications, vol. 12, p. 888-895, 2021.
A. Khannat, Sbaï, H., et Kjiri, L., « Configurable Process Mining: Semantic Variability in Event Logs », in International Conference on Enterprise Information Systems, ICEIS - Proceedings, 2021, vol. 1, p. 768-775.
I. Choukri, Guermah, H., Daosabah, A., et Nassar, M., « Context aware Hidden Markov Model for Intention process mining », in 5th International Conference on Intelligent Computing in Data Sciences, ICDS 2021, 2021.
A. Hmami, Sbaï, H., et Fredj, M., « Enhancing change mining from a collection of event logs: Merging and Filtering approaches », in Journal of Physics: Conference Series, 2021, vol. 1743.
A. Hmami, Fredj, M., et Sbaï, H., « Handling Sudden and Recurrent Changes in Business Process Variability: Change Mining based Approach », International Journal of Advanced Computer Science and Applications, vol. 12, p. 632-640, 2021.
E. M. Akrouchi, Benbrahim, H., et Kassou, I., « Review on adopting concept extraction in weak signals detection in competitive intelligence », in ACM International Conference Proceeding Series, 2021.
2020
H. Hakkoum, Idri, A., et Abnane, I., « Artificial Neural Networks Interpretation Using LIME for Breast Cancer Diagnosis », Advances in Intelligent Systems and Computing, vol. 1161 AISC, p. 15-24, 2020.
B. Karbal et Romadi, R., « A Comparison of Different Machine Learning Algorithms for Intrusion Detection », Communications in Computer and Information Science, vol. 1264, p. 157-169, 2020.
H. Benhar, Idri, A., et Fernández-Alemán, J. L., « Data preprocessing for heart disease classification: A systematic literature review. », Computer Methods and Programs in Biomedicine, vol. 195, 2020.
I. Chlioui, Idri, A., et Abnane, I., « Data preprocessing in knowledge discovery in breast cancer: systematic mapping study », Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 8, p. 547-561, 2020.
A. Khannat, Sbaï, H., et Kjiri, L., « Event logs pre-processing for configurable process discovery: Ontology-based approach », in Colloquium in Information Science and Technology, CIST, 2020, vol. 2020-June, p. 139-144.
E. O. Aissaoui, Y. Madani, E. Alami El, Oughdir, L., Dakkak, A., et Y. Allioui, E., « Mining Learners’ Behaviors: An Approach Based on Educational Data Mining Techniques », Advances in Intelligent Systems and Computing, vol. 1076, p. 655-670, 2020.
E. O. Aissaoui, Y. Madani, E. Alami El, Oughdir, L., Dakkak, A., et Y. Allioui, E., « A Multiple Linear Regression-Based Approach to Predict Student Performance », Advances in Intelligent Systems and Computing, vol. 1102 AISC, p. 9-23, 2020.
A. Hmami, Sbaï, H., et Fredj, M., « A new Framework to improve Change Mining in Configurable Process », in ACM International Conference Proceeding Series, 2020.
M. EZZAT et Idri, A., « Reviewing Data Analytics Techniques in Breast Cancer Treatment », Advances in Intelligent Systems and Computing, vol. 1161 AISC, p. 65-75, 2020.
A. Khannat, Sbaï, H., et Kjiri, L., « Towards mining semantically enriched configurable process models », in ACM International Conference Proceeding Series, 2020, p. 20-24.

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