TU Wien Informatics

20 Years

Role

  • Using Semi-automatic Annotation Platform to Create Corpus for Argumentative Zoning / El-Ebshihy, A., Ningtyas, A. M., Piroi, F., Rauber, A., Romadhony, A., Faraby, S. A., & Sabariah, M. K. (2023). Using Semi-automatic Annotation Platform to Create Corpus for Argumentative Zoning. In O. Alonso, H. Cousijn, G. Silvello, M. Marrero, C. Teixeira Lopes, & S. Marchesin (Eds.), Linking Theory and Practice of Digital Libraries: 27th International Conference on Theory and Practice of Digital Libraries, TPDL 2023, Zadar, Croatia, September 26–29, 2023, Proceedings (pp. 132–145). Springer. https://doi.org/10.1007/978-3-031-43849-3_12
    Project: AR-Science (2019–2022)
  • Towards a Toolbox for Automated Assessment of Machine-Actionable Data Management Plans / Miksa, T., Suchánek, M., Slifka, J., Knaisl, V., Ekaputra, F. J., Kovacevic, F., Ningtyas, A. M., El-Ebshihy, A. M., & Pergl, R. (2023). Towards a Toolbox for Automated Assessment of Machine-Actionable Data Management Plans. Data Science Journal, 22, Article 28. https://doi.org/10.5334/dsj-2023-028
  • A Platform for Argumentative Zoning Annotation and Scientific Summarization / El-Ebshihy, A., Ningtyas, A. M., Andersson, L., Piroi, F., & Rauber, A. (2022). A Platform for Argumentative Zoning Annotation and Scientific Summarization. In M. A. Hasan & L. Xiong (Eds.), CIKM ’22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 4843–4847). Association for Computing Machinery (ACM). https://doi.org/10.1145/3511808.3557193
    Project: AR-Science (2019–2022)
  • Leveraging Wikipedia Knowledge for Distant Supervision in Medical Concept Normalization / Ningtyas, A. M., El-Ebshihy, A., Herwanto, G. B., Piroi, F., & Hanbury, A. (2022). Leveraging Wikipedia Knowledge for Distant Supervision in Medical Concept Normalization. In Experimental IR Meets Multilinguality, Multimodality, and Interaction (pp. 33–47). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-13643-6_3
  • Medical Entity Linking in Laypersons’ Language / Ningtyas, A. M. (2022). Medical Entity Linking in Laypersons’ Language. In Advances in Information Retrieval (pp. 513–519). Springer-Verlag. https://doi.org/10.1007/978-3-030-99739-7_63
  • Data Augmentation for Layperson’s Medical Entity Linking Task / Ningtyas, A. M., Piroi, F., Andersson, L., & Hanbury, A. (2021). Data Augmentation for Layperson’s Medical Entity Linking Task. In FIRE ’21: Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation (pp. 99–106). https://doi.org/10.1145/3503162.3503172
  • TUW-IFS at TREC NEWS 2020 Wikification Task / Ningtyas, A. M., El-Ebshihy, A., Piroi, F., Andersson, L., & Hanbury, A. (2021). TUW-IFS at TREC NEWS 2020 Wikification Task. In The Twenty-Ninth Text REtrieval Conference (TREC 2020) Proceedings (pp. 1–10). NIST. http://hdl.handle.net/20.500.12708/58735
  • ARTU / TU Wien and Artificial Researcher@ LongSumm 20 / El-Ebshihy, A., Ningtyas, A. M., Andersson, L., Piroi, F., & Rauber, A. (2020). ARTU / TU Wien and Artificial Researcher@ LongSumm 20. In Proceedings of the First Workshop on Scholarly Document Processing. The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.sdp-1.36