Dr. Ioana Hulpus

Post-doctoral researcher

Universität Mannheim

B6, 28, Room C1,12

Email: ioana at informatik dot uni-mannheim dot de 

Office hours:  by appointment by email

Research

  • Knowledge Graph Mining
  • Entity Linking and Word-Sense Disambiguation
  • Knowledge Representation
  • Linked Data
  • Financial Network Analysis

Biography

Dr. Ioana Hulpus is a postdoctoral researcher in the Data and Web Science Group at the University of Mannheim, working with Prof. Dr. Heiner Stuckenschmidt and Prof. Dr. Simone Paolo Ponzetto on various topics at the border between text mining and structured knowledge representation. Before joining the Data and Web Science Group at Uni Mannheim, she worked as a post-doctoral researcher at Insight Centre, NUI-Galway, where she contributed to research projects involving partners like Elsevier, RTE and Irish Times. She received her Ph.D in 2014 from the National Insight Centre under the supervision of Dr. Conor Hayes, with a thesis on unsupervised word-sense disambiguation and topic labelling with knowledge graphs.

Recent Publications

  • Hulpus, I., Kobbe, J., Stuckenschmidt, H. und Hirst, G. (2020). Knowledge graphs meet moral values. In , Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics : Barcelona, Spain (Online), December 2020 (S. 71-80). , Association for Computational Linguistics: Stroudsburg, PA.
  • Kobbe, J., Hulpus, I. und Stuckenschmidt, H. (2020). Unsupervised stance detection for arguments from consequences. In , EMNLP 2020 : proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 16th – 20th November 2020 (S. 50-60). , Association for Computational Linguistics: Online.
  • Kobbe, J., Rehbein, I., Hulpus, I. und Stuckenschmidt, H. (2020). Exploring morality in argumentation. In , Proceedings of the 7th Workshop on Argument Mining : Barcelona, Spain (Online), December 13, 2020 (S. 30-40). , Association for Computational Linguistics, ACL: Stroudsburg, PA.
  • Štajner, S. und Hulpus, I. (2020). When shallow is good enough: Automatic assessment of conceptual text complexity using shallow semantic features. In , LREC 2020 Marseille : Twelfth International Conference on Language Resources and Evaluation : May 11-16, 2020, Palais du Pharo, Marseille, France : conference proceedings (S. 1414-1422). , European Language Resources Association, ELRA-ELDA: Paris.
  • Štajner, S., Nisioi, S. und Hulpus, I. (2020). CoCo: A tool for automatically assessing conceptual complexity of texts. In , LREC 2020 Marseille : Twelfth International Conference on Language Resources and Evaluation : May 11-16, 2020, Palais du Pharo, Marseille, France : conference proceedings (S. 7179-7186). , European Language Resources Association: Paris.
  • Hulpus, I., Kobbe, J., Becker, M., Opitz, J., Hirst, G., Meilicke, C., Nastase, V., Stuckenschmidt, H. und Frank, A. (2019). Towards explaining natural language arguments with background knowledge. In , PROFILES-SEMEX 2019 : Joint Proceedings of the 6th International Workshop on Dataset PROFlLing and Search & the 1st Workshop on Semantic Explainability co-loc. with 18th International Semantic Web Conference (ISWC 2019) Auckland, NZ, Oct. 27, 2019 (S. 62-77). CEUR Workshop Proceedings, RWTH: Aachen.
  • Hulpus, I., Štajner, S. und Stuckenschmidt, H. (2019). A spreading activation framework for tracking conceptual complexity of texts. In , 57th Annual Meeting of the Association for Computational Linguistics, ACL 2019 : Proceedings of the conference : July 28 – August 2, 2019, Florence, Italy (S. 3878-3887). , Association for Computational Linguistics, ACL: Stroudsburg, PA.
  • Kobbe, J., Opitz, J., Becker, M., Hulpus, I., Stuckenschmidt, H. und Frank, A. (2019). Exploiting background knowledge for argumentative relation classification. In , 2nd Conference on Language, Data and Knowledge (LDK 2019) (S. 8:1-8:14). OASIcs – OpenAccess Series in Informatics, Leibniz-Zentrum für Informatik: Wadern.
  • Štajner, S. und Hulpus, I. (2018). Automatic assessment of conceptual text complexity using knowledge graphs. In , 27th International Conference on Computational Linguistics, COLING 2018 : Proceedings of the conference : August 20-26, 2018, Santa Fe, New Mexico, USA (S. 318-330). , Association for Computational Linguistics, ACL: Stroudsburg, PA.
  • Weiland, L., Hulpus, I., Ponzetto, S. P. und Dietz, L. (2017). Using object detection, NLP, and knowledge bases to understand the message of images. In , MultiMedia Modeling : 23rd International Conference, MMM 2017, Reykjavik, Iceland, January 4-6, 2017, Proceedings, Part II (S. 405-418). Lecture Notes in Computer Science, Springer International Publishing: Cham.
  • Weiland, L., Hulpus, I., Ponzetto, S. P. und Dietz, L. (2016). Understanding the message of images with knowledge base traversals. In , Proceedings of the 2016 ACM on International Conference on the Theory of Information Retrieval, ICTIR 2016, Newark, DE, USA, September 13-16, 2016 (S. 199-208). , ACM: New York, NY.