Kersting, J., &; Geierhos, M. (2021). Well-being in Plastic Surgery: Deep Learning Reveals Patients’ Evaluations. Proceedings of the 10th International Conference on Data Science, Technology and Applications (DATA 2021), 275--284.

Kersting, J., &; Geierhos, M. (2021). Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting. In E. Kapetanios, H. Horacek, E. Métais, &; F. Meziane (Eds.), Natural Language Processing and Information Systems (Vol. 12801, pp. 231--242). Springer.

Bäumer, F. S., Kersting, J., Buff, B., &; Geierhos, M. (2020). Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P News Tagging. In L. Audrius, B. Rita, G. Daina, &; S. Vilma (Eds.), Information and Software Technologies (Vol. 1283, pp. 368--382). Kaunas, Litauen: Springer.https://doi.org/10.1007/978-3-030-59506-7_30 

Kersting, J., &; Geierhos, M. (2020). Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) (pp. 391--400). Setúbal, Portugal: SCITEPRESS.

Buff, B., Kersting, J., &; Geierhos, M. (2020). Detection of Privacy Disclosure in the Medical Domain: A Survey. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020) (pp. 630--637). Setúbal, Portugal: SCITEPRESS.

Kersting, J., &; Geierhos, M. (2020). Neural Learning for Aspect Phrase Extraction and Classification in Sentiment Analysis. In Proceedings of the 33rd International Florida Artificial Intelligence Research Symposium (FLAIRS) Conference (pp. 282--285). North Miami Beach, FL, USA: AAAI.

Kersting, J., &; Geierhos, M. (2020). What Reviews in Local Online Labour Markets Reveal about the Performance of Multi-Service Providers. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods (pp. 263--272). Setúbal, Portugal: SCITEPRESS.

Bäumer, F. S., &; Geierhos, M. (2019). Requirements Engineering in OTF-Computing. In encyclopedia.pub. Basel, Switzerland: MDPI.

Bäumer, F. S., Kersting, J., &; Geierhos, M. (2019). Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches. Computers, 8(1).https://doi.org/10.3390/computers8010022 

Bäumer, F. S., Buff, B., &; Geierhos, M. (2019). Potentielle Privatsphareverletzungen aufdecken und automatisiert sichtbar machen. In P. Sahle (Ed.), DHd 2019 Digital Humanities: multimedial &; multimodal. Konferenzabstracts (pp. 192–193). Frankfurt am Main, Germany: Zenodo.https://doi.org/10.5281/zenodo.2596095 

Kersting, J., Bäumer, F. S., &; Geierhos, M. (2019). In Reviews We Trust: But Should We? Experiences with Physician Review Websites. In M. Ramachandran, R. Walters, G. Wills, V. Mendez Munoz, &; V. Chang (Eds.), Proceedings of the 4th International Conference on Internet of Things, Big Data and Security (pp. 147–155). Setúbal, Portugal: SCITEPRESS.

Bäumer, F. S., &; Geierhos, M. (2018). How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges. In M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, &; F. Meziane (Eds.), Proceedings of the 23rd International Conference on Natural Language and Information Systems (Vol. 10859, pp. 509–513). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-91947-8_53 

Kim, Y., Lee, S., Dollmann, M., &; Geierhos, M. (2018). Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure. International Journal of Advanced Science and Technology, 112, 123–136.https://doi.org/10.14257/ijast.2018.112.12 

Geierhos, M. (2018). Freiraum zur individuellen Reflexion gemeinsamer Werte. In K. B. Schnebel &; A. Taubenböck (Eds.), Integration und Toleranz (1st ed., pp. 288–292). Ulm, Germany: Klemm+Oelschläger.

Bäumer, F. S., Kersting, J., Kurselis, V., &; Geierhos, M. (2018). Rate Your Physician: Findings from a Lithuanian Physician Rating Website. In R. Damasevidius &; G. Vasiljevien (Eds.), Communications in Computer and Information Science (Vol. 920, pp. 43–58). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-99972-2_4 

Bäumer, F. S., &; Geierhos, M. (2018). NLP in OTF Computing: Current Approaches and Open Challenges. In R. Damasevidius &; G. Vasiljevien (Eds.), Proceedings of the 24th International Conference on Information and Software Technologies (ICIST 2018) (Vol. 920, pp. 559–570). Cham, Switzerland: Springer.https://doi.org/10.1007/978-3-319-99972-2_46 

Bäumer, F. S., &; Geierhos, M. (2018). Text Broom: A ML-based Tool to Detect and Highlight Privacy Breaches in Physician Reviews: An Insight into Our Current Work. In European Conference on Data Analysis 2018: Multidisciplinary Facets of Data Science - Book of Abstracts. Paderborn, Germany.

Bäumer, F. S., Kersting, J., Orlikowski, M., &; Geierhos, M. (2018). Towards a Multi-Stage Approach to Detect Privacy Breaches in Physician Reviews. In A. Khalili &; M. Koutraki (Eds.), Proceedings of the Posters and Demos Track of the 14th International Conference on Semantic Systems co-located with the 14th International Conference on Semantic Systems (SEMANTiCS 2018) (Vol. 2198). Vienna, Austria: CEUR-WS.org.

Bäumer, F. S., &; Geierhos, M. (2018). Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-based Configuration of Text Analysis Pipelines. In Proceedings of the 51st Hawaii International Conference on System Sciences (pp. 5746–5755). Big Island, Waikoloa Village.https://doi.org/10125/50609 

Geierhos, M. (2018). Unschärfe bei der Interpretation natürlichsprachlicher Anforderungsbeschreibungen. In S. Freitag, M. Geierhos, R. Asmani, &; J. I. Haug (Eds.), Unschärfe - Der Umgang mit fehlender Eindeutigkeit (1st ed., pp. 111–128). Paderborn, Germany: Ferdinand Schöningh.