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

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, 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 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 and M. Geierhos, “Requirements Engineering in OTF-Computing,” in encyclopedia.pub, Basel, Switzerland: MDPI, 2019.

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.

N. Seemann and M.-L. Merten, “UPB-Annotate: Ein maßgeschneidertes Toolkit fur historische Texte,” in DHd 2019 Digital Humanities: multimedial &; multimodal. Konferenzabstracts, Mainz and Frankfurt am Main, Germany, 2019, pp. 352–353.

F. S. Bäumer, B. Buff, and M. Geierhos, “Potentielle Privatsphareverletzungen aufdecken und automatisiert sichtbar machen,” in DHd 2019 Digital Humanities: multimedial &; multimodal. Konferenzabstracts, Mainz and Frankfurt am Main, Germany, 2019, pp. 192–193.

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 and B. Buff, “How to Boost Customer Relationship Management via Web Mining Benefiting from the Glass Customer’s Openness,” in Proceedings of the 8th International Conference on Data Science, Technology and Applications, 2019.

E. Friesen, Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis. Universität Paderborn, 2019.

F. S. Bäumer and M. Geierhos, “How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges,” in Proceedings of the 23rd International Conference on Natural Language and Information Systems, vol. 10859, M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, and F. Meziane, Eds. Cham, Switzerland: Springer, 2018, pp. 509–513.