Answering binary causal questions through large-scale text mining: An evaluation using cause-effect pairs from human experts
- Oktie Hassanzadeh
- Debarun Bhattacharjya
- et al.
- IJCAI 2019
Dr. Oktie Hassanzadeh is a Senior Research Scientist at IBM T.J. Watson Research Center. He is the recipient of several academic and corporate awards, including a top prize at the FinCausal-2022 Shared Task, a top prize at the Semantic Web Challenge at ISWC conference, and two best-paper awards at ESWC conferences. He has received his M.Sc. and Ph.D. degrees from the University of Toronto, where he received the IBM PhD fellowship and the Yahoo! Key Scientific Challenges awards. He is also a two-time recipient of the first prize at the Triplification Challenge at the SEMANTiCS Conference for his projects in the areas of Semantic Technologies and Linked Data.
Dr. Hassanzadeh's research interests are in the areas of data curation, information integration, and knowledge management. His current research is focused on extraction of knowledge from large and heterogeneous sources of structured and unstructured data, and integration and management of the extracted knowledge. He actively participates in Semantic Web, Data Management, and AI research communities through publications and program committee activities.
In the past, he has worked on several problems related to accurate and efficient discovery of links within and between large data repositories. In particular:
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