Syntactic Dependency for relation extraction from Biomedical literature
Xiaomei Wei, Jianyong Wang, Yang Li
Available Online November 2012.
- https://doi.org/10.2991/citcs.2012.186How to use a DOI?
- syntactic parsing; Dependency; Classification; extraction
- Relation extraction is important to improve complex natural language processing (NLP) applications. The Bio-Event extraction in GE shared task is important to understand biological processes. Although some progress has made in GE research, there is still much work to do to improve the performance of the extraction system. In this paper, we build a extraction system based on syntactic dependency technique. Relying on the output of the sentence parsing, we get rich features to build a classification model to separate the candidate edges into positive class and negative class. We obtain promising results on GE develop data set. Especially the results of simple events are comparable with the state-of-the-art GE extraction systems.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xiaomei Wei AU - Jianyong Wang AU - Yang Li PY - 2012/11 DA - 2012/11 TI - Syntactic Dependency for relation extraction from Biomedical literature BT - 2012 National Conference on Information Technology and Computer Science PB - Atlantis Press SP - 733 EP - 736 SN - 1951-6851 UR - https://doi.org/10.2991/citcs.2012.186 DO - https://doi.org/10.2991/citcs.2012.186 ID - Wei2012/11 ER -