Abstract
We present a Graph Based Approach to automatically extract domain specific terms from technical domains like Biochemistry, Communication, Computer Science and Law. Our approach is similar to TextRank with an extra post-processing step to reduce the noise. We performed our experiments on the mentioned domains provided by ICON TermTraction - 2020 shared task. Presented precision, recall and f1-score for all experiments. Further, it is observed that our method gives promising results without much noise in domain terms.- Anthology ID:
- 2020.icon-termtraction.1
- Volume:
- Proceedings of the 17th International Conference on Natural Language Processing (ICON): TermTraction 2020 Shared Task
- Month:
- December
- Year:
- 2020
- Address:
- Patna, India
- Venue:
- ICON
- SIG:
- Publisher:
- NLP Association of India (NLPAI)
- Note:
- Pages:
- 1–4
- Language:
- URL:
- https://aclanthology.org/2020.icon-termtraction.1
- DOI:
- Cite (ACL):
- Hema Ala and Dipti Sharma. 2020. Graph Based Automatic Domain Term Extraction. In Proceedings of the 17th International Conference on Natural Language Processing (ICON): TermTraction 2020 Shared Task, pages 1–4, Patna, India. NLP Association of India (NLPAI).
- Cite (Informal):
- Graph Based Automatic Domain Term Extraction (Ala & Sharma, ICON 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.icon-termtraction.1.pdf