Abstract
As the quantity of publications increases daily, researchers are forced to narrow their attention to their own specialism and are therefore less likely to make new connections with other areas. Literature based discovery (LBD) supports the identification of such connections. A number of LBD tools are available, however, they often suffer from limitations such as constraining possible searches or not producing results in real-time. We introduce HiDE (Hidden Discovery Explorer), an online knowledge browsing tool which allows fast access to hidden knowledge generated from all abstracts in Medline. HiDE is fast enough to allow users to explore the full range of hidden connections generated by an LBD system. The tool employs a novel combination of two approaches to LBD: a graph-based approach which allows hidden knowledge to be generated on a large scale and an inference algorithm to identify the most promising (most likely to be non trivial) information. Available at https://skye.shef.ac.uk/kdisc- Anthology ID:
- C18-2008
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 34–37
- Language:
- URL:
- https://aclanthology.org/C18-2008
- DOI:
- Cite (ACL):
- Judita Preiss and Mark Stevenson. 2018. HiDE: a Tool for Unrestricted Literature Based Discovery. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 34–37, Santa Fe, New Mexico. Association for Computational Linguistics.
- Cite (Informal):
- HiDE: a Tool for Unrestricted Literature Based Discovery (Preiss & Stevenson, COLING 2018)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/C18-2008.pdf