Daniel Schlör, M.Sc.

Chair of Data Science (Informatik X)
University of Würzburg
Am Hubland
97074 Würzburg
Germany
Email: daniel.schloer@informatik.uni-wuerzburg.de
Phone: (+49 931) 31 - 84564
Office: Room B109 (Computer Science Building M2)
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
- Winter term 20/21: Übung zu Grundlagen der Algorithmen und Datenstrukturen
- Winter term 19/20: Übung zu Grundlagen der Algorithmen und Datenstrukturen
- Winter term 18/19: Übung zu Grundlagen der Algorithmen und Datenstrukturen
- Winter term 17/18: Übung zu Grundlagen der Algorithmen und Datenstrukturen
- Winter term 16/17: Sprachverarbeitung und Text Mining
- Winter term 15/16: Sprachverarbeitung und Text Mining
Publications
-
Evaluation of Post-hoc XAI Approaches Through Synthetic Tabular Data. Tritscher, Julian; Ring, Markus; Schlör, Daniel; Hettinger, Lena; Hotho, Andreas in Lecture Notes in Computer Science, D. Helic, G. Leitner, M. Stettinger, A. Felfernig, Z. W. Ras (reds.) (2020). (Vol. 12117) 422–430.
-
Improving Sentiment Analysis with Biofeedback Data. Schlör, Daniel; Zehe, Albin; Kobs, Konstantin; Veseli, Blerta; Westermeier, Franziska; Brübach, Larissa; Roth, Daniel; Latoschik, Marc Erich; Hotho, Andreas (2020). 28–33.
-
iNALU: Improved Neural Arithmetic Logic Unit. Schlör, Daniel; Ring, Markus; Hotho, Andreas in Frontiers in Artificial Intelligence (2020). 3 71.
-
Financial Fraud Detection with Improved Neural Arithmetic Logic Units Schlör, Daniel; Ring, Markus; Krause, Anna; Hotho, Andreas (2020). (Vol. Fifth Workshop on MIning DAta for financial applicationS)
-
Flow-based network traffic generation using Generative Adversarial Networks. Ring, Markus; Schlör, Daniel; Landes, Dieter; Hotho, Andreas in Comput. Secur. (2019). 82 156–172.
-
A White-Box Model for Detecting Author Nationality by Linguistic Differences in Spanish Novels. Zehe, Albin; Schlör, Daniel; Henny-Krahmer, Ulrike; Becker, Martin; Hotho, Andreas (2018).
-
Burrows’ Zeta: Exploring and Evaluating Variants and Parameters. Schöch, Christof; Schlör, Daniel; Zehe, Albin; Gebhard, Henning; Becker, Martin; Hotho, Andreas (2018). 274–277.
-
Neutralising the Authorial Signal in Delta by Penalization: Stylometric Clustering of Genre in Spanish Novels. Tello, José Calvo; Schlör, Daniel; Henny-Krahmer, Ulrike; Schöch, Christof R. Lewis, C. Raynor, D. Forest, M. Sinatra, S. Sinclair (reds.) (2017).
-
Straight Talk! Automatic Recognition of Direct Speech in Nineteenth-Century French Novels. Schöch, Christof; Schlör, Daniel; Popp, Stefanie; Brunner, Annelen; Henny, Ulrike; Tello, José Calvo (2016). 346–353.
-
Extracting Semantics from Unconstrained Navigation on Wikipedia. Niebler, Thomas; Schlör, Daniel; Becker, Martin; Hotho, Andreas in KI -- Künstliche Intelligenz (2016). 30(2) 163–168.