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

Bäumer, F. S., Chen, W.-F., Geierhos, M., Kersting, J., &; Wachsmuth, H. (2023). Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, &; H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 65–84). Heinz Nixdorf Institut, Universität Paderborn.https://doi.org/10.5281/zenodo.8068456 

Kersting, J., &; Geierhos, M. (2023). Towards Comparable Ratings: Quantifying Evaluative Phrases in Physician Reviews. In A. Cuzzocrea, O. Gusikhin, S. Hammoudi, &; C. Quix (Eds.), Data Management Technologies and Applications (Vol. 1860, pp. 45–65). Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-37890-4_3 

Kersting, J., Maoro, F., &; Geierhos, M. (2023). Towards comparable ratings: Exploring bias in German physician reviews. Data &; Knowledge Engineering, 148, Article 102235.https://doi.org/10.1016/j.datak.2023.102235 

Kersting, J., Ahmed, M., &; Geierhos, M. (2022). Chatbot-Enhanced Requirements Resolution for Automated Service Compositions. In C. Stephanidis, M. Antona, &; S. Ntoa (Eds.), HCI International 2022 Posters (Vol. 1580, pp. 419--426). Springer International Publishing.https://doi.org/10.1007/978-3-031-06417-3_56 

Kersting, J., &; Bäumer, F. S. (2022). Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis. In J. Kersting (Ed.), 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 (pp. 5–9). IARIA.

Bäumer, F. S., Kersting, J., Denisov, S., &; Geierhos, M. (2021). IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING. PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225.

Kersting, J., &; Geierhos, M. (2021). Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks. In R. Loukanova (Ed.), Natural Language Processing in Artificial Intelligence -- NLPinAI 2020 (Vol. 939, pp. 163--189). Cham: Springer.https://doi.org/10.1007/978-3-030-63787-3_6 

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., &; Bäumer, F. S. (2020). SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, 119--123.

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., 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 

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., 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., 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.