Mark Hoogendoorn

dr.

19942019
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  • 6 Similar Profiles
Learning systems Engineering & Materials Science
Electronic medical equipment Engineering & Materials Science
Reinforcement learning Engineering & Materials Science
Health Engineering & Materials Science
Intelligent agents Engineering & Materials Science
Reinforcement Learning Mathematics
Electronic Health Records Medicine & Life Sciences
Personalization Mathematics

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Research Output 1994 2019

Detecting fraudulent bookings of online travel agencies with unsupervised machine learning

Mensah, C., Klein, J., Bhulai, S., Hoogendoorn, M. & van der Mei, R., 1 Jan 2019, Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings. Friedrich, G., Ali, M., Wotawa, F., Pill, I. & Koitz-Hristov, R. (eds.). Springer Verlag, p. 334-346 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11606 LNAI).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Unsupervised Learning
Learning systems
Anomaly Detection
Machine Learning
Transportation charges

Detecting Network Intrusion beyond 1999: Applying Machine Learning Techniques to a Partially Labeled Cybersecurity Dataset

Klein, J., Bhulai, S., Hoogendoorn, M., Van Der Mei, R. & Hinfelaar, R., 10 Jan 2019, Proceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018. IEEE, p. 784-787 4 p. 8609692

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Intrusion detection
Learning systems

End-to-End Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning: A comparative study in digital health interventions for behavior change

El Hassouni, A., Hoogendoorn, M., Eiben, A. E., van Otterlo, M. & Muhonen, V., 14 Oct 2019, IEEE/WIC/ACM International Conference on Web Intelligence: WI '19. New York, NY, USA: ACM, p. 258-264 7 p.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Reinforcement learning
Health
Sensors
Mobile phones
Accelerometers

Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing

Grua, E. M. & Hoogendoorn, M., 28 Jan 2019, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Sundaram, S. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 813-820 8 p. 8628621

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Personalization
Reinforcement learning
Reinforcement Learning
Health
Clustering

Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns

Lu, X., Tabatabaei, S. A., Hoogendoorn, M. & Reijers, H. A., 2019, Business Process Management: 17th International Conference, BPM 2019, Proceedings. Hildebrandt, T., van Dongen, B. F., Röglinger, M. & Mendling, J. (eds.). Springer Verlag, p. 198-215 18 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11675 LNCS).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Healthcare
Trace
Clustering
Pathway
Medical problems

Activities 2015 2015

  • 1 Editorial work

Applied Artificial Intelligence (Journal)

T. Bosse (Member of editorial board), M. Hoogendoorn (Member of editorial board)
2015

Activity: Peer review and Editorial workEditorial workAcademic