Programs
- M. Tech. in Automotive Engineering -
- Fellowship In Interventional Pulmonology and Pulmonary Critical care - Fellowship
Publication Type : Book Chapter
Publisher : Springer Netherlands
Source : Lecture Notes in Computational Vision and Biomechanics, Springer Netherlands, Volume 30, p.937-944 (2019)
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Year : 2019
Abstract : Identifying the relationship between the entities plays a key role in understanding any natural language. The relation extraction is a task, which finds the relationship between entities in a sentence. The relation extraction and named entity recognition are the subtasks of information extraction. In this paper, we have experimented and analyzed the closed-domain relation extraction using three variants of temporal convolutional neural network on SemEval-2018 and SemEval-2010 relation extraction corpus. In this approach, the word-level features are formed from the distributed representation of text and the position information of entity are used as the feature for the model. © Springer Nature Switzerland AG 2019.
Cite this Research Publication : V. Hariharan, M. Kumar, A., and Dr. Soman K. P., “Relation extraction using convolutional neural networks”, in Lecture Notes in Computational Vision and Biomechanics, vol. 30, Springer Netherlands, 2019, pp. 937-944.