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.

Alturki, S., Hulpus, I. and Stuckenschmidt, H. (2022). Predicting academic outcomes: A survey from 2007 till 2018. Technology, Knowledge and Learning, 27, 275–307.
Becker, M., Hulpus, I., Opitz, J., Paul, D., Kobbe, J., Stuckenschmidt, H. and Frank, A. (2020). Explaining arguments with background knowledge : Towards knowledge-based argumentation analysis. Datenbank-Spektrum, 20, 131–141.

Kobbe, J., Hulpus, I. and Stuckenschmidt, H. (2023). Effect graph: Effect relation extraction for explanation generation. In , Proceedings of the 1st Workshop on Natural Language Reasoning and Structured Explanations (NLRSE) (S. 116–127). , Association for Computational Linguistics: Toronto, Canada.
Hulpus, I., Kobbe, J., Stuckenschmidt, H. and 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. and 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. and 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. and 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. and 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. and 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: Aachen, Germany.
Hulpus, I., Štajner, S. and 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. and 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.