Abstract
A novel literature-based discovery system based on UMLS Ontologies, Semantic Filters, Statistics, and Word Embed-dings was developed and validated against the well-established Raynaud’s disease – Fish Oil discovery by min-ing different size and specificity corpora of Pubmed titles and abstracts. Results show an ‘inverse effect’ between open ver-sus closed discovery search modes. In open discovery, a more general and bigger corpus (Vascular disease or Peri-vascular disease) produces better results than a more specific and smaller in size corpus (Raynaud disease), whereas in closed discovery, the exact opposite is true.- Anthology ID:
- 2020.icon-demos.1
- Volume:
- Proceedings of the 17th International Conference on Natural Language Processing (ICON): System Demonstrations
- Month:
- DECEMBER
- Year:
- 2020
- Address:
- Patna, India
- Venue:
- ICON
- SIG:
- Publisher:
- NLP Association of India (NLPAI)
- Note:
- Pages:
- 1–3
- Language:
- URL:
- https://aclanthology.org/2020.icon-demos.1
- DOI:
- Cite (ACL):
- Toby Reed and Vassilis Cutsuridis. 2020. Demonstration of a Literature Based Discovery System based on Ontologies, Semantic Filters and Word Embeddings for the Raynaud Disease-Fish Oil Rediscovery. In Proceedings of the 17th International Conference on Natural Language Processing (ICON): System Demonstrations, pages 1–3, Patna, India. NLP Association of India (NLPAI).
- Cite (Informal):
- Demonstration of a Literature Based Discovery System based on Ontologies, Semantic Filters and Word Embeddings for the Raynaud Disease-Fish Oil Rediscovery (Reed & Cutsuridis, ICON 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.icon-demos.1.pdf