The NCU team members are the NCU alumnus Mr. Jen-Chieh Han (right) and his thesis advisor Professor Tzong-Han Tsai (left). The team participated in the BioASQ challenge for the first time and won the first prize.
The NCU team, consisting of members from the Intelligent Information Service Research Lab of the Department of Computer Science and Information Engineering at National Central University (NCU), participated in the BioASQ, an international biomedical semantic indexing and question answering contest. The NCU team competed with hotshots from all over the world for several batches and finally turned defeat into victory in the final contest at the fifth, beating the Korean team and winning the first prize. Though it was NCU’s first participation in the contest, the team achieved great results.
BioASQ is a world-renowned international competition in artificial intelligence and biomedicine. In 2020, the eighth competition was co-organized by several scientific research centers in the European Union (EU) countries and was sponsored by corporations including Google and Atypon. There are various competitive events related to biomedicine. One of the events is the biomedical semantic question and answering (BioASQ Task 8b: Biomedical Semantic QA), in which the NCU team was competing. Competitors came from Australia, Korea, Russia, and the U.S., and the whole challenge went on for several rounds over several months. Finally, in the fifth batch, the NCU team won the contest.
Members of the NCU team were Mr. Jen-Chieh Han, the alumnus of the Department of Computer Science and Information Engineering, and Han’s thesis advisor Dr. Tzong-Han Tsai, Professor at the same department. Though the NCU team did not outstand other teams in batch one to four, they stuck to the end and turned defeat into victory in the last batch, defeating the team from Korea University and winning the first prize.
The Intelligent Information Service Research Lab of the Department of Computer Science and Information Engineering endeavors to develop various types of biomedical information extraction technology that enables semantic analysis, and to work on emerging biomedical missions including Named Entity Recognition (NER), Relation Extraction (RE), and Question Answering. “I think it contributes to our everyday practice so that we could stick to the end, reverse the game at the end, and beat the Korean team. This achievement was also the recognition to our team,” said Professor Tsai.