Smart Interactive Farmer-Bot Using Bagging & Natural Language Processing

Authors

  • Uddhav Patil School of Computer Engineering and Technology, MIT Academy of Engineering, Alandi, Pune, Maharashtra, India
  • Nikhil Kinikar School of Computer Engineering and Technology, MIT Academy of Engineering, Alandi, Pune, Maharashtra, India
  • Madanu Amisha School of Computer Engineering and Technology, MIT Academy of Engineering, Alandi, Pune, Maharashtra, India
  • Aishwarya Chouthe School of Computer Engineering and Technology, MIT Academy of Engineering, Alandi, Pune, Maharashtra, India
  • Rajeshwari Goudar School of Computer Engineering and Technology, MIT Academy of Engineering, Alandi, Pune, Maharashtra, India

DOI:

https://doi.org/10.26438/ijcse/v10i12.813

Keywords:

Ensemble Learning, Bagging Method, Natural language processing, Data Cleaning, Prediction

Abstract

About 58% of Indians rely on agriculture as their main source of income, and this sector contributes significantly to the nation's Gross Domestic Product (GDP). As the agricultural process evolves, it is increasingly crucial to disseminate information about it when it becomes available. Improvements in the crop production and weather (rainfall) prediction can be increased with the right data and prediction responses obtained in relation to weather and regions. This can be accomplished with a farmer-chatbot, which is a conversational software that uses pre-programmed responses or artificial intelligence to answer the queries without the intervention of a human. The proposed Farmer-chatbot system, allows farmers to ask questions and receive precise replies in common language. The query is processed using the Ensemble Learning Algorithm and the Natural Language Processing to anticipate solutions to the users.

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Published

2022-12-31
CITATION
DOI: 10.26438/ijcse/v10i12.813
Published: 2022-12-31

How to Cite

[1]
U. Patil, N. Kinikar, M. Amisha, Aishwarya Chouthe, and R. Goudar, “Smart Interactive Farmer-Bot Using Bagging & Natural Language Processing”, Int. J. Comp. Sci. Eng., vol. 10, no. 12, pp. 8–13, Dec. 2022.

Issue

Vol. 10 No. 12 (2022): IJCSE December Edition

Section

Research Article

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