LSTM-RASA Based Agri Farm Assistant for Farmers
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Abstract (arXiv)
The application of Deep Learning and Natural Language based ChatBots are growing rapidly in recent years. They are used in many fields like customer support, reservation system and as personal assistant. The Enterprises are using such ChatBots to serve their customers in a better and efficient manner. Even after such technological advancement, the expert advice does not reach the farmers on timely manner. The farmers are still largely dependent on their peers knowledge in solving the problems they face in their field. These technologies have not been effectively used to give the required information to farmers on timely manner. This project aims to implement a closed domain ChatBot for the field of Agriculture Farmers Assistant. Farmers can have conversation with the Chatbot and get the expert advice in their field. Farmers Assistant is based on RASA Open Source Framework. The Chatbot identifies the intent and entity from user utterances and retrieve the remedy from the database and share it with the user. We tested the Bot with existing data and it showed promising results.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 26 references that are in the map. First posted on arXiv 7 Apr 2022.
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14 of 26 references.
References · 14
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
- 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,303
- 2018Self-Attention with Relative Position Representationscited by 1,112
- 2014word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding methodcited by 109
- 2019Training Neural Response Selection for Task-Oriented Dialogue Systemscited by 48
- 2020DIET: Lightweight Language Understanding for Dialogue Systemscited by 35
- 2016Leveraging Sentence-level Information with Encoder LSTM for Semantic Slot Fillingcited by 25
- 2019Dialogue Transformerscited by 13
- 2020A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineeringcited by 10
- 2015How to Generate a Good Word Embedding?cited by 9
2 more
- 2018Few-Shot Generalization Across Dialogue Taskscited by 5
- 2021Building a Question and Answer System for News Domaincited by 1
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Citing papers per year: 2025: 1.
1 paper.