Publications

Zlabinger, M., Sabou, R., Hofstätter, S., Sertkan, M. (2020) DEXA: Supporting Non-Expert Annotators with Dynamic Examples from Experts, Association for Computing Machinery, New York, NY, United States, SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval.
Zlabinger, M., Hofstätter, S., Rekabsaz, N., Hanbury, A. (2020) DSR: A Collection for the Evaluation of Graded Disease-Symptom Relations, Springer Nature Switzerland AG 2021, Advances in Information Retrieval 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14-17, 2020, Proceedings, Part II.
Zlabinger, M., Sabou, R., Hofstätter, S., Hanbury, A. (2020) Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial Reports, The Association for Computational Linguistics, Findings of the Association for Computational Linguistics: EMNLP 2020.
Hofstätter, S., Lipani, A., Zlabinger, M., Hanbury, A. (2020) Learning to Re-Rank with Contextualized Stopwords, Proceedings of the 29th ACM International Conference on Information & Knowledge Management.
Hofstätter, S., Zlabinger, M., Hanbury, A. (2020) Interpretable & time-budget-constrained contextualization for re-ranking, IOS Press, ECAI 2020 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain - Including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020).
Hofstätter, S., Zlabinger, M., Hanbury, A. (2020) Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-ranking Results, Springer, Advances in Information Retrieval 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14-17, 2020, Proceedings, Part II.
Hofstätter, S., Zlabinger, M., Sertkan, M., Schröder, M. (2020) Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering, Association for Computing Machinery, Proceedings of the 29th ACM International Conference on Information & Knowledge Management, .
Sabou, R., Käsznar, K., Zlabinger, M., Biffl, S. (2020) Verifying Extended Entity Relationship Diagrams with Open Tasks, Proceedings of the 8th AAAI Conference on Human Computation and Crowdsourcing, HCOMP.
Zlabinger, M., Rekabsaz, N., Zlabinger, S., Hanbury, A. (2019) Efficient Answer-Annotation for Frequent Questions, Springer, Experimental IR Meets Multilinguality, Multimodality, and Interaction.10th International Conference of the CLEF Association, CLEF 2019 Lugano, Switzerland, September 9-12, 2019. Proceedings..
Zlabinger, M. (2019) Efficient and Effective Text-Annotation through Active Learning, Association for Computing Machinery, SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval.
Zlabinger, M. (2019) Improving the Annotation Efficiency and Effectiveness in the Text Domain, Springer, Cham, Advances in Information Retrieval 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14-18, 2019, Proceedings, Part I.
Zlabinger, M., Andersson, L., Hanbury, A., Andersson, M. (2018) Medical Entity Corpus with PICO elements and Sentiment Analysis, International Conference on Language Resources and Evaluation, LREC 2018, Eleventh International Conference on Language Resources and Evaluation.
Zlabinger, M., Hanbury, A. (2017) Finding duplicate images in biology papers, SAC '17 Proceedings of the Symposium on Applied Computing, 32nd ACM SIGAPP Symposium On Applied Computing, .
Zlabinger, M. (2017) Efficient and Effective Text-Annotation through Active Learning, ACM, SIGIR'19: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval.
Zlabinger, M. (2016) Finden von Duplikatbildern in Biologie-Publikationen, , Master thesis at Institut für Softwaretechnik und Interaktive Systeme.