Text Based Smart Answering System in Agriculture using RNN

Raji Sukumar, Hemalatha N, Sarin S, Rose Mary C A


Abstract
Agriculture is an important aspect of India’s economy, and the country currently has one of the highest rates of farm producers in the world. Farmers need hand holding with support of technology. A chatbot is a tool or assistant that you may communicate with via instant messages. The goal of this project is to create a Chatbot that uses Natural Language Processing with a Deep Learning model. In this project we have tried implementing Multi-Layer Perceptron model and Recurrent Neural Network models on the dataset. The accuracy given by RNN was 97.83%.
Anthology ID:
2021.icon-main.83
Volume:
Proceedings of the 18th International Conference on Natural Language Processing (ICON)
Month:
December
Year:
2021
Address:
National Institute of Technology Silchar, Silchar, India
Editors:
Sivaji Bandyopadhyay, Sobha Lalitha Devi, Pushpak Bhattacharyya
Venue:
ICON
SIG:
Publisher:
NLP Association of India (NLPAI)
Note:
Pages:
663–669
Language:
URL:
https://aclanthology.org/2021.icon-main.83
DOI:
Bibkey:
Cite (ACL):
Raji Sukumar, Hemalatha N, Sarin S, and Rose Mary C A. 2021. Text Based Smart Answering System in Agriculture using RNN. In Proceedings of the 18th International Conference on Natural Language Processing (ICON), pages 663–669, National Institute of Technology Silchar, Silchar, India. NLP Association of India (NLPAI).
Cite (Informal):
Text Based Smart Answering System in Agriculture using RNN (Sukumar et al., ICON 2021)
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PDF:
https://preview.aclanthology.org/emnlp22-frontmatter/2021.icon-main.83.pdf