Lucas Foulon
Former LIRIS member since: 2021-06-30
Quality | PhD student |
Team(s) | DM2L |
Institution | Autre |
Thesis | Anomaly detection in data streams using indexing and approximation. Application to continuous analysis of message streams within the SNCF information system (click to view details) |
Publications (IdHAL : lucas-foulon)
Publications LIRIS pour Lucas Foulon (5)
- 2022 (1)
- Book edition (books, chapters, seminars, congress, special numbers) (1)
- Lucas Foulon, Christophe Rigotti, Serge Fenet & Denis Jouvin (2022). "Anomaly Detection Based on Sequence Indexation and CFOF Score Approximation". Advances in Knowledge Discovery and Management, Springer International Publishing, pp. 47-61. doi : 10.1007/978-3-030-90287-2_3. HAL : hal-03881940.
- 2020 (1)
- HDR, thesis (1)
- Thesis (1)
- Lucas Foulon (2020). "Détection d'anomalies dans les flux de données par structure d'indexation et approximation. Application à l'analyse en continu des flux de messages du système d'information de la SNCF". HAL : tel-03089142. .
- 2019 (3)
- Conferences (2)
- International conferences with peer review (1)
- Lucas Foulon, Serge Fenet, Christophe Rigotti & Denis Jouvin (2019). "Scoring Message Stream Anomalies in Railway Communication Systems". LMID 2019 - IEEE Workshop on Learning and Mining with Industrial Data, 11 novembre 2019, Beijing (China), pp. 1-8. doi : 10.1109/ICDMW.2019.00114. HAL : hal-02357924. .
- National conferences with peer review (1)
- Lucas Foulon, Christophe Rigotti, Serge Fenet & Denis Jouvin (2019). "Approximation du score CFOF de détection d’anomalie dans un arbre d’indexation iSAX : Application au contexte SI de la SNCF". EGC 2019 - 19ème Conférence francophone sur l'Extraction et la Gestion des Connaissances, 25 janvier 2019, Metz (France), pp. 1-12. HAL : hal-02019035. .
- Others (1)
- Lucas Foulon, Serge Fenet, Christophe Rigotti & Denis Jouvin (2019). "Detecting Anomalies over Message Streams in Railway Communication Systems". AALTD@ECML/PKDD 2019 - 4th Workshop on Advanced Analytics and Learning on Temporal Data. Poster, 20 septembre 2019, Wurzburg (Germany). Poster. HAL : hal-02357927. .