This project aims to address the challenges associated with various aspects of question answering tasks on unstructured textual data.
This project has been funded by:
- Jinho Choi - Assistant Professor at Emory University
- Analysis of Wikipedia-based Corpora for Question Answering. Jurczyk, T.; Deshmane, A.; and Choi, J. D. arXiv, 1801.02073, 2018.
- SelQA: A New Benchmark for Selection-based Question Answering. Jurczyk, T.; Zhai, M.; and Choi, J. D. Proceedings of the International Conference on Tools with Artificial Intelligence (ICTAI), 2016.
- QA-It: Classifying Non-Referential It for Question Answer Pairs. Lee, T.; Alex, L.; and Choi, J. D. Proceedings of the Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL:SRW), 2016.
- Multi-Field Structural Decomposition for Question Answering. Jurczyk, T.; and Choi, J. D. arXiv, 1604.00938, 2016.
- Semantics-based Graph Approach to Complex Question-Answering. Jurczyk, T.; and Choi, J. D. Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop (NAACL:SRW), 2015.
- Real-Time Community Question Answering: Exploring Content Recommendation and User Notification Strategies. Liu, Q.; Jurczyk, T.; Choi, J. D.; and Agichtein, E. Proceedings of the Conference on Intelligent User Interfaces (iUI), 2015.