Dr. ir. X. (Xixi) Lu

Buys Ballotgebouw
Princetonplein 5
Kamer 508
3584 CC Utrecht

Dr. ir. X. (Xixi) Lu

Universitair docent
Process Science
030 253 7540
x.lu@uu.nl

Publicaties

2023

Wetenschappelijke publicaties

Lee, S., Comuzzi, M., Lu, X., & Reijers, H. A. (2023). Measuring the Stability of Process Outcome Predictions in Online Settings. In J. Munoz-Gama, S. Rinderle-Ma, & A. Senderovich (Eds.), Proceedings - 2023 5th International Conference on Process Mining, ICPM 2023 (pp. 105-112). Article 10271960 (Proceedings - 2023 5th International Conference on Process Mining, ICPM 2023). IEEE. https://doi.org/10.1109/ICPM60904.2023.10271960
Beerepoot, I., Barenholz, D., Beekhuis, S., Gulden, J., Lee, S., Lu, X., Overbeek, S., Van De Weerd, I., Van Der Werf, J. M., & Reijers, H. A. (2023). A Window of Opportunity: Active Window Tracking for Mining Work Practices. In J. Munoz-Gama, S. Rinderle-Ma, & A. Senderovich (Eds.), 5th International Conference on Process Mining (ICPM), Rome, Italy, October 23-27, 2023 (pp. 57-64). IEEE Computer Society. https://doi.org/10.1109/ICPM60904.2023.10271961
Liu, Y., Stein Dani, V., Beerepoot, I., & Lu, X. (Accepted/In press). Turning Logs Into Lumber: Preprocessing Tasks in Process Mining. In 4th International Conference on Process Mining (ICPM 2023) Workshops - The Event Data & Behavioral Analytics (EdbA 2023)
Leemans, S. J. J., Zelst, S. J. V., & Lu, X. (2023). Partial-order-based process mining: a survey and outlook. Knowledge and Information Systems, 65(1), 1-29. https://doi.org/10.1007/s10115-022-01777-3
Zelst, S. J. V., Tai, J., Langenberg, M., & Lu, X. (2023). Context-Based Activity Label-Splitting. In C. D. Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management - 21st International Conference, BPM 2023, Proceedings: 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11–15, 2023, Proceedings (1 ed., pp. 232-248). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14159 LNCS). Springer. https://doi.org/10.1007/978-3-031-41620-0_14
Vazifehdoostirani, M., Genga, L., Lu, X., Verhoeven, R., Laarhoven, H. V., & Dijkman, R. M. (2023). Interactive Multi-interest Process Pattern Discovery. In C. D. Francescomarino, A. Burattin, C. Janiesch, & S. Sadiq (Eds.), Business Process Management - 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11-15, 2023, Proceedings (Vol. 14159, pp. 303-319). (Lecture Notes in Computer Science). Springer Verlag. https://doi.org/10.1007/978-3-031-41620-018
Hundogan, O., Lu, X., Du, Y., & Reijers, H. A. (2023). CREATED: Generating Viable Counterfactual Sequences for Predictive Process Analytics. In M. Indulska, I. Reinhartz-Berger, C. Cetina, & O. Pastor (Eds.), Advanced Information Systems Engineering - 35th International Conference, CAiSE 2023, Proceedings (Vol. 13901, pp. 541-557). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13901 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-031-34560-932
Jongeling, H. E., Lu, X., Beerepoot, I., Weerd, I. V. D., & Reijers, H. A. (2023). Getting Your RPA Priorities Straight with Process Mining: The PLOST Framework. In M. Aanestad, S. Klein, M. Tarafdar, S. Han, S. Laumer, & I. Ramos (Eds.), 31st European Conference on Information Systems - Co-creating Sustainable Digital Futures, ECIS 2023, Kristiansan, Norway, June 11-16, 2023 https://aisel.aisnet.org/ecis2023_rp/308/

2022

Wetenschappelijke publicaties

Munoz-Gama, J., & Lu, X. (Eds.) (2022). Process Mining Workshops - ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 - November 4, 2021, Revised Selected Papers. (Lecture Notes in Business Information Processing). Springer Verlag. https://doi.org/10.1007/978-3-030-98581-3
Koorn, J. J., Lu, X., Leopold, H., Martin, N., Verboven, S., & Reijers, H. A. (2022). Mining Statistical Relations for Better Decision Making in Healthcare Processes. In A. Burattin, A. Polyvyanyy, & B. Weber (Eds.), 4th International Conference on Process Mining, ICPM 2022, Bolzano, Italy, October 23-28, 2022 (pp. 32-39). IEEE. https://doi.org/10.1109/ICPM57379.2022.9980719
https://dspace.library.uu.nl/bitstream/handle/1874/431831/Mining_Statistical_Relations_for_Better_Decision_Making_in_Healthcare_Processes.pdf?sequence=1
Post, R., Beerepoot, I., Lu, X., Kas, S., Wiewel, S., Koopman, A., & Reijers, H. (2022). Active Anomaly Detection for Key Item Selection in Process Auditing. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops: ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers (1 ed., pp. 167-179). (Lecture Notes in Business Information Processing; Vol. 433 ). Springer Cham. https://doi.org/10.1007/978-3-030-98581-3_13
Lee, S., Lu, X., & Reijers, H. (2022). The Analysis of Online Event Streams: Predicting the Next Activity for Anomaly Detection. In R. Guizzardi, J. Ralyté, & X. Franch (Eds.), Research Challenges in Information Science: 16th International Conference, RCIS 2022, Barcelona, Spain, May 17–20, 2022, Proceedings (pp. 248-264). (Lecture Notes in Business Information Processing; Vol. 446 LNBIP). Springer. https://doi.org/10.1007/978-3-031-05760-1_15
Munoz-Gama, J., Martin, N., Fernandez-Llatas, C., Johnson, O. A., Sepúlveda, M., Helm, E., Galvez-Yanjari, V., Rojas, E., Martinez-Millana, A., Aloini, D., Amantea, I. A., Andrews, R., Arias, M., Beerepoot, I., Benevento, E., Burattin, A., Capurro, D., Carmona, J., Comuzzi, M., ... Zerbato, F. (2022). Process Mining for Healthcare: Characteristics and Challenges. Journal of Biomedical Informatics, 127, 1-15. Article 103994. https://doi.org/10.1016/j.jbi.2022.103994
Stein Dani, V., Leopold, H., van der Werf, J. M., Lu, X., Beerepoot, I., Koorn, J., & Reijers, H. (2022). Towards Understanding the Role of the Human in Event Log Extraction. In A. Marrella, & B. Weber (Eds.), Business Process Management Workshops: BPM 2021 International Workshops, Rome, Italy, September 6–10, 2021, Revised Selected Papers (pp. 86-98). (Lecture Notes in Business Information Processing; Vol. 436 LNBIP). Springer. https://doi.org/10.1007/978-3-030-94343-1_7
Koorn, J. J., Lu, X., Leopold, H., & Reijers, H. A. (2022). Mining Statistical Relations for Better Decision Making in Healthcare Processes.
Koorn, J. J., Lu, X., Mannhardt, F., Leopold, H., & Reijers, H. A. (2022). Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions. In Proceedings of the 55th Hawaii International Conference on System Sciences (pp. 1-10) https://doi.org/http://hdl.handle.net/10125/79839

2021

Wetenschappelijke publicaties

Lee, S., Lu, X., & Comuzzi, M. (2021). Continuous Performance Evaluation for Business Process Outcome Monitoring. In J. Munoz-Gama, & X. Lu (Eds.), Process Mining Workshops: ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31 – November 4, 2021, Revised Selected Papers (Vol. 433, pp. 237-249). (Lecture Notes in Business Information Processing; Vol. 433). Springer. https://doi.org/10.1007/978-3-030-98581-3_18
Andel, V. V., Beerepoot, I., Lu, X., Weerd, I. V. D., & Reijers, H. A. (2021). DEUCE - A Methodology for Detecting Unauthorized Access of Electronic Health Records Using Process Mining.. Paper presented at 29th European Conference on Information Systems, ECIS 2021, Marrakech, Morocco. https://aisel.aisnet.org/ecis2021_rp/66
Koorn, J. J., Lu, X., Leopold, H., & Reijers, H. A. (2021). From Action to Response to Effect: Mining Statistical Relations in Work Processes. Information Systems.
Koorn, J. J., Beerepoot, I., Dani, V. S., Lu, X., Weerd, I. V. D., Leopold, H., & Reijers, H. A. (2021). Bringing Rigor to the Qualitative Evaluation of Process Mining Findings: An Analysis and a Proposal. In C. Di Ciccio, C. Di Francescomarino, & P. Soffer (Eds.), Proceedings - 2021 3rd International Conference on Process Mining, ICPM 2021 (pp. 120-127). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icpm53251.2021.9576877
Beerepoot, I., Lu, X., Van De Weerd, I., & Alexander Reijers, H. (2021). Seeing the Signs of Workarounds: A Mixed-Methods Approach to the Detection of Nurses’ Process Deviations. 3763-3772. https://doi.org/10.24251/hicss.2021.456
Neubauer, T. R., Peres, S. M., Fantinato, M., Lu, X., & Reijers, H. A. (2021). Interactive clustering: a scoping review. Artificial Intelligence Review, 54, 2765–2826. https://doi.org/10.1007/s10462-020-09913-7

2020

Wetenschappelijke publicaties

Lu, X., Gal, A., & Reijers, H. A. (2020). Discovering hierarchical processes using flexible activity trees for event abstraction. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), 2020 2nd International Conference on Process Mining (ICPM) (pp. 145-152). Article 9230087 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPM49681.2020.00030

2019

Wetenschappelijke publicaties

Tabatabaei, S. A., Lu, X., Hoogendoorn, M., & Reijers, H. A. (Accepted/In press). Identifying Patient Groups based on Frequent Patterns of Patient Samples. In IEEE Healthcom (Vol. abs/1904.01863). (CoRR). http://arxiv.org/abs/1904.01863
Gao, J., Zelst, S. J. V., Lu, X., & Aalst, W. M. P. V. D. (2019). Automated robotic process automation: a self-learning approach. In H. Panetto (Ed.), On the Move to Meaningful Internet Systems: OTM 2019 Conferences: Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21-25, 2019, Proceedings (pp. 95-112). (Lecture notes in computer science; Vol. 11877), (LNCS sublibrary. SL 2, Programming and software engineering). Springer. https://doi.org/10.1007/978-3-030-33246-4_6
Lu, X., Tabatabaei, S. A., Hoogendoorn, M., & Reijers, H. A. (2019). Trace Clustering on Very Large Event Data in Healthcare Using Frequent Sequence Patterns. In T. Hildebrandt (Ed.), Business Process Management: 17th International Conference, BPM 2019, Vienna, Austria, September 1–6, 2019, Proceedings (pp. 198-215). (Lecture Notes in Computer Science; Vol. 11675). Springer. https://doi.org/10.1007/978-3-030-26619-6_14
Koorn, J. J., Lu, X., Leopold, H., & Reijers, H. A. (2019). Towards Understanding Aggressive Behavior in Residential Care Facilities Using Process Mining. In G. Guizzardi, & F. Gailly (Eds.), International Conference on Conceptual Modeling (pp. 135-145). (Lecture Notes in Computer Science; Vol. 11787). Springer Cham. https://doi.org/10.1007/978-3-030-34146-6_12