Chris Biemann is a Professor for Language Technology at the University of Hamburg, where he leads the Language Technology group. He is also the scientific Director of the Hub of Computing and Data Science, where he enables ad shapes the digital transformation of research in all scientific disciplines. He earned his doctoral degree and a diploma in computer science from the University of Leipzig. His doctoral research focused on unsupervised, knowledge-free methods in language processing, exploring the extent to which computers can autonomously detect structure in text data. Following his PhD, Biemann expanded his research to include lexical semantics and various natural language processing (NLP) applications, including a range of open source tools for supporting researchers in the Humanities and Social Sciences.
CB Prof. Dr. Chris Biemann ( Partner)
Keywords: Computer science, Computational linguistics, Natural language processing, Data science infrastructures
Bio
Selected Publications
Biemann, C., Heyer, G., Quasthoff, U. (2022): Wissensrohstoff Text. Eine Einführung in das Text Mining. Springer Vieweg
Biemann, C. Crane, G.R., Fellbaum, C.D., Mehler, A. (Eds) (2014): Report from Dagstuhl Seminar 14301: Computational Humanities – Bridging the Gap Between Computer Science and Digital Humanities. Dagstuhl Reports, Volume 4, Issue 7, pp.80-111, doi: 10.4230/DagRep.4.7.80
Hatzel, H,. Stiemer, H., Biemann, C. and Gius, E. (2023): Machine learning in computational literary studies. it – Information Technology. https://doi.org/10.1515/itit-2023-0041
Hatzel, H. and Biemann, C. (2024): Story Embeddings — Narrative-Focused Representations of Fictional Stories. EMNLP 2024, Miami, Florida, USA.
Fischer, T., Schneider, F., Haque, A., Koch, G., Biemann, C. (2024): Extending the Discourse Analysis Tool Suite with Whiteboards for Visual Qualitative Analysis. (LREC-COLING 2024), Torino, Italy.
Fischer, T., Schneider, F., Geislinger, R., Helfer, F., Koch, G., and Biemann, C. (2024): Concept Over Time Analysis: Unveiling Temporal Patterns for Qualitative Data Analysis. NAACL 2024, Mexico City, Mexico
Koch, G., Biemann, C., Eiser, I., Fischer, T., Schneider, F., Stumpf, T., García, A.T. (2022): D-WISE Tool Suite for the Sociology of Knowledge Approach to Discourse. In: Rauterberg, M. (eds.) Proc. Culture and Computing. HCII 2022. Lecture Notes in Computer Science, vol 13324. Springer, Cham.
Wiedemann G., Yimam, S.M., Biemann, C. (2018): A Multilingual Information Extraction Pipeline for Investigative Journalism, In Proceedings of 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018). Brussels, Belgium
Haase, C., Anwar, S. Yimam, S.M., Friedrich, A., Biemann, C. (2021): SCoT: Sense Clustering over Time: a tool for the analysis of lexical change. The 2021 Conference of the European Chapter of the Association for Computational Linguistics – System Demonstrations. Kyiv, Ukraine (Online)
Biemann, C., Heyer, G., Quasthoff U. and Richter, M. (2007): The Leipzig Corpora Collection – Monolingual corpora of standard size. In: Proceedings of Corpus Linguistics 2007, Birmingham, UK