| Efficient process discovery from event streams using sequential pattern mining M Hassani, S Siccha, F Richter, T Seidl 2015 IEEE symposium series on computational intelligence, 1366-1373, 2015 | 59 | 2015 |
| Looking into the TESSERACT: Time-drifts in event streams using series of evolving rolling averages of completion times F Richter, T Seidl Information Systems 84, 265-282, 2019 | 16 | 2019 |
| TESSERACT: time-drifts in event streams using series of evolving rolling averages of completion times F Richter, T Seidl Business Process Management: 15th International Conference, BPM 2017 …, 2017 | 15 | 2017 |
| Concept drift detection on streaming data with dynamic outlier aggregation L Zellner, F Richter, J Sontheim, A Maldonado, T Seidl Process Mining Workshops: ICPM 2020 International Workshops, Padua, Italy …, 2021 | 14 | 2021 |
| Efficient infrequent pattern mining using negative itemset tree Y Lu, F Richter, T Seidl Complex pattern mining: New challenges, methods and applications, 1-16, 2020 | 10 | 2020 |
| Efficient infrequent itemset mining using depth-first and top-down lattice traversal Y Lu, F Richter, T Seidl Database Systems for Advanced Applications: 23rd International Conference …, 2018 | 7 | 2018 |
| Multilevel visual motion opponency in Drosophila G Ammer, E Serbe-Kamp, AS Mauss, FG Richter, S Fendl, A Borst Nature neuroscience 26 (11), 1894-1905, 2023 | 6 | 2023 |
| OTOSO: online trace ordering for structural overviews F Richter, A Maldonado, L Zellner, T Seidl Process Mining Workshops: ICPM 2020 International Workshops, Padua, Italy …, 2021 | 6 | 2021 |
| TOAD: trace ordering for anomaly detection F Richter, Y Lu, L Zellner, J Sontheim, T Seidl 2020 2nd International Conference on Process Mining (ICPM), 169-176, 2020 | 5 | 2020 |
| LIProMa: Label-independent process matching F Richter, L Zellner, I Azaiz, D Winkel, T Seidl Business Process Management Workshops: BPM 2019 International Workshops …, 2019 | 4 | 2019 |
| Model-aware clustering of non-conforming traces F Richter, L Zellner, J Sontheim, T Seidl On the Move to Meaningful Internet Systems: OTM 2019 Conferences …, 2019 | 4 | 2019 |
| K-nearest neighbor based clustering with shape alternation adaptivity Y Lu, Y Zhang, F Richter, T Seidl 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 3 | 2020 |
| TADE: Stochastic conformance checking using temporal activity density estimation F Richter, J Sontheim, L Zellner, T Seidl Business Process Management: 18th International Conference, BPM 2020 …, 2020 | 3 | 2020 |
| Interdisciplinary knowledge cohesion through distributed information management systems D Kaltenthaler, JY Lohrer, F Richter, P Kröger Journal of Information, Communication and Ethics in Society 16 (4), 413-426, 2018 | 3 | 2018 |
| Perrcas: Process error cascade mining in trace streams A Wimbauer, F Richter, T Seidl International Conference on Process Mining, 224-236, 2021 | 2 | 2021 |
| “Show Me the Crowds!” Revealing Cluster Structures Through AMTICS F Richter, Y Lu, D Kazempour, T Seidl Data Science and Engineering 5 (4), 360-374, 2020 | 2 | 2020 |
| Temporal Deviations on Event Sequences. J Sontheim, F Richter, T Seidl LWDA, 173-177, 2019 | 2 | 2019 |
| k-process: Model-Conformance-based Clustering of Process Instances. F Richter, F Wahl, A Sydorova, T Seidl LWDA, 161-172, 2019 | 2 | 2019 |
| Scorer-gap: sequentially correlated rules for event recommendation considering gap size L Zellner, J Sontheim, F Richter, G Lindner, T Seidl 2021 International Conference on Data Mining Workshops (ICDMW), 925-934, 2021 | 1 | 2021 |
| Lscminer: Efficient low support closed itemsets mining Y Lu, F Richter, T Seidl Web Information Systems Engineering–WISE 2019: 20th International Conference …, 2019 | 1 | 2019 |
Ludwig ZellnerLMU MunichVerified email at dbs.ifi.lmu.de
