ActiveMotif: Interactive Motif Discovery with Human Feedback
- Title
- ActiveMotif: Interactive Motif Discovery with Human Feedback
- Author
- 김영훈
- Issue Date
- 2017-07
- Publisher
- IEEE
- Citation
- 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Page. 2736-2739
- Abstract
- Motif detection, which is to discover short patterns involved in many important biological processes, has been recently raised as an important task in bioinformatics. The traditional algorithms to find a sequence motif have been developed using machine learning only without involving the experience and domain knowledge of human experts effectively. In this paper, we propose an interactive motif discovery system by introducing a new learning algorithm, by generalizing a well-known statistical motif model, whose inference can be shepherded by human feedback. © 2017 IEEE.
- URI
- https://ieeexplore.ieee.org/document/8037423https://repository.hanyang.ac.kr/handle/20.500.11754/103484
- ISBN
- 978-1-5090-2809-2
- ISSN
- 1558-4615
- DOI
- 10.1109/EMBC.2017.8037423
- Appears in Collections:
- COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
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