piwik-script

Deutsch Intern
    Data Science Chair

    Dr. Daniel Schlör

    Chair of Data Science (Informatik X)
    University of Würzburg
    Campus Hubland Nord
    Emil-Fischer-Straße 50
    97074 Würzburg
    Germany

    Email: daniel.schloer@informatik.uni-wuerzburg.de

    Phone: (+49 931)  31 - 84564

    Office: Room 50.03.017 (Institutsgebäude Künstliche Intelligenz)

    Projects and Research Interests

    My main research interests are machine learning, anomaly detection in the fields of cybersecurity and fraud detection and textmining and their application to digital humanities. Currently I'm working on deep learning models able to capture mathematical and other relationships within data.

    In addition to my affiliation with the DMIR research group I have been a member of the CLiGS – Computational Literary Genre Stylistics research group, working in the field of Digital Humanities.

    Teaching

    Publications

    2022[ to top ]
    • Schlör, D. and Hotho, A. (2022) Towards Responsible Medical Diagnostics Recommendation Systems, available: http://arxiv.org/abs/2209.03760.
    • Tritscher, J., Gwinner, F., Schlör, D., Krause, A., and Hotho, A. (2022) Open ERP System Data For Occupational Fraud Detection, available: http://arxiv.org/abs/2206.04460.
    • Schlör, D. (2022) Detecting Anomalies in Transaction Data, PhD dissertation, available: https://doi.org/10.25972/OPUS-29856.
    2021[ to top ]
    • Ring, M., Schlör, D., Wunderlich, S., Landes, D., and Hotho, A. (2021) Malware detection on windows audit logs using LSTMs, Computers & Security, 109, 102389, available: https://doi.org/https://doi.org/10.1016/j.cose.2021.102389.
    • Tritscher, J., Krause, A., Schlör, D., Gwinner, F., Von Mammen, S., and Hotho, A. (2021) A financial game with opportunities for fraud, in 2021 IEEE Conference on Games (CoG), 1–5, available: https://doi.org/10.1109/CoG52621.2021.9619070.
    2020[ to top ]
    • Improving Sentiment Analy...
      Schl{\"o}r, D., Zehe, A., Kobs, K., Veseli, B., Westermeier, F., Br{\"u}bach, L., Roth, D., Latoschik, M.E., and Hotho, A. (2020) Improving Sentiment Analysis with Biofeedback Data, in Proceedings of LREC2020 Workshop ``People in Language, Vision and the mind’’ (ONION2020), Marseille, France: European Language Resources Association (ELRA), 28–33, available: https://www.aclweb.org/anthology/2020.onion-1.5.
    • Evaluation of Post-hoc XA...
      Tritscher, J., Ring, M., Schlör, D., Hettinger, L., and Hotho, A. (2020) Evaluation of Post-hoc XAI Approaches Through Synthetic Tabular Data., in Helic, D., Leitner, G., Stettinger, M., Felfernig, A. and Ras, Z.W., eds., ISMIS, Lecture Notes in Computer Science, Springer, 422–430, available: http://dblp.uni-trier.de/db/conf/ismis/ismis2020.html#TritscherRSHH20.
    • iNALU: Improved Neural Ar...
      Schlör, D., Ring, M., and Hotho, A. (2020) iNALU: Improved Neural Arithmetic Logic Unit, Frontiers in Artificial Intelligence, 3, 71, available: https://doi.org/10.3389/frai.2020.00071.
    • Financial Fraud Detection...
      Schlör, D., Ring, M., Krause, A., and Hotho, A. (2020) Financial Fraud Detection With Improved Neural Arithmetic Logic Units.
    2019[ to top ]
    • Classification of text-ty...
      Schl{\"o}r, D., Sch{\"o}ch, C., and Hotho, A. (2019) Classification of text-types in german novels, in Digital Humanities 2019: Conference Abstracts, available: https://doi.org/https://doi.org/10.34894/OMLKRN.
    • Flow-based network traffi...
      Ring, M., Schlör, D., Landes, D., and Hotho, A. (2019) Flow-based network traffic generation using Generative Adversarial Networks., Comput. Secur., 82, 156–172, available: http://dblp.uni-trier.de/db/journals/compsec/compsec82.html#RingSLH19.
    2018[ to top ]
    • A White-Box Model for Det...
      Zehe, A., Schlör, D., Henny-Krahmer, U., Becker, M., and Hotho, A. (2018) A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels, in DH, ADHO.
    • Burrows’ Zeta: Explorin...
      Schöch, C., Schlör, D., Zehe, A., Gebhard, H., Becker, M., and Hotho, A. (2018) Burrows’ Zeta: Exploring and Evaluating Variants and Parameters, in DH, 274–277, available: http://dblp.uni-trier.de/db/conf/dihu/dh2018.html#SchochSZG0H18.
    2017[ to top ]
    • Neutralising the Authoria...
      Tello, J.C., Schlör, D., Henny-Krahmer, U., and Schöch, C. (2017) Neutralising the Authorial Signal in Delta by Penalization: Stylometric Clustering of Genre in Spanish Novels., in Lewis, R., Raynor, C., Forest, D., Sinatra, M. and Sinclair, S., eds., DH, Alliance of Digital Humanities Organizations (ADHO), available: http://dblp.uni-trier.de/db/conf/dihu/dh2017.html#TelloSHS17.
    2016[ to top ]
    • Straight Talk! Automatic ...
      Sch{\"o}ch, C., Schl{\"o}r, D., Popp, S., Brunner, A., Henny, U., and Tello, J.C. (2016) Straight Talk! Automatic Recognition of Direct Speech in Nineteenth-Century French Novels., in DH, 346–353.
    • Niebler, T., Schlör, D., Becker, M., and Hotho, A. (2016) Extracting Semantics from Unconstrained Navigation on Wikipedia, KI -- Künstliche Intelligenz, 30(2), 163–168.