J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.

F. S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, and H. Wachsmuth, “Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 65–84.

J. Kersting and M. Geierhos, “Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews,” in Data Management Technologies and Applications, vol. 1860, A. Cuzzocrea, O. Gusikhin, S. Hammoudi, and C. Quix, Eds. Cham: Springer Nature Switzerland, 2023, pp. 45–65.

J. Kersting, F. Maoro, and M. Geierhos, “Towards comparable ratings: Exploring bias in German physician reviews,”10.1016/j.datak.2023.102235__Data &; Knowledge Engineering, vol. 148, Art. no. 102235, 2023, doi:10.1016/j.datak.2023.102235 .

J. Kersting, M. Ahmed, and M. Geierhos, “Chatbot-Enhanced Requirements Resolution for Automated Service Compositions,” in HCI International 2022 Posters, vol. 1580, C. Stephanidis, M. Antona, and S. Ntoa, Eds. Cham, Switzerland: Springer International Publishing, 2022, pp. 419--426.

J. Kersting and F. S. Bäumer, “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis,” in Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, Barcelona, Spain, 2022, pp. 5–9.

F. S. Bäumer, J. Kersting, S. Denisov, and M. Geierhos, “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, Lisbon, Portugal, 2021, pp. 221--225.

J. Kersting and M. Geierhos, “Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks,” in Natural Language Processing in Artificial Intelligence -- NLPinAI 2020, vol. 939, R. Loukanova, Ed. Cham: Springer, 2021, pp. 163--189.

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

J. Kersting and M. Geierhos, “Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting,” in Natural Language Processing and Information Systems, vol. 12801, E. Kapetanios, H. Horacek, E. Métais, and F. Meziane, Eds. Saarbrücken, Germany: Springer, 2021, pp. 231--242.

F. S. Bäumer, J. Kersting, B. Buff, and M. Geierhos, “Tag Me If You Can: Insights into the Challenges of Supporting Unrestricted P News Tagging,” in Information and Software Technologies, vol. 1283, L. Audrius, B. Rita, G. Daina, and S. Vilma, Eds. Springer, 2020, pp. 368--382.

J. Kersting and F. S. Bäumer, “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, Lisbon, Portugal, 2020, pp. 119--123.

J. Kersting and M. Geierhos, “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), Valetta, Malta, 2020, pp. 391--400.

B. Buff, J. Kersting, and M. Geierhos, “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), Valetta, Malta, 2020, pp. 630--637.

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

J. Kersting and M. Geierhos, “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, Valetta, Malta, 2020, pp. 263--272.

F. S. Bäumer, J. Kersting, and M. Geierhos, “Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches,” Computers, vol. 8, no. 1, 2019.

J. Kersting, F. S. Bäumer, and M. Geierhos, “In Reviews We Trust: But Should We? Experiences with Physician Review Websites,” in Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, Heraklion, Greece, 2019, pp. 147–155.

F. S. Bäumer, J. Kersting, V. Kurselis, and M. Geierhos, “Rate Your Physician: Findings from a Lithuanian Physician Rating Website,” in Communications in Computer and Information Science, vol. 920, R. Damasevidius and G. Vasiljevien, Eds. Cham, Switzerland: Springer, 2018, pp. 43–58.

F. S. Bäumer, J. Kersting, M. Orlikowski, and M. Geierhos, “Towards a Multi-Stage Approach to Detect Privacy Breaches in Physician Reviews,” in 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), Vienna, Austria, 2018, vol. 2198.