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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM31860

Agriculture eCommerce Website with ML Chatbot

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM31860

Volume:

8 |

4 |

Apr 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM31860

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PS

P Sowjanya

BR

Borra Rakesh

GV

Gannu Vamsi

GP

Gartham Pooja

ANR

Anapana Nagi Reddy

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Abstract

– The project aims to develop an innovative Agriculture eCommerce platform integrated with a Machine Learning (ML) chatbot to revolutionize the agricultural industry’s online marketplace. The proposed system addresses the growing need for efficient access to agricultural products and services while enhancing user engagement through intelligent conversational interfaces. The Agriculture eCommerce site serves as a digital marketplace where farmers, agricultural professionals, and enthusiasts can browse, purchase, and interact with a wide range of agricultural products, equipment, and services. Leveraging ML algorithms, the platform’s chatbot offers intuitive conversational interactions, allowing users to inquire about products, receive recommendations, and troubleshoot queries effectively. Through this project, B.Tech students will gain valuable experience in developing a comprehensive eCommerce solution integrated with cutting-edge ML technology. Additionally, the project holds the potential to make a significant impact on the agricultural sector by fostering digital transformation and facilitating access to agricultural resources.

KEYWORDS

– Agricultural industry eCommerce Machine Learning Digital experience User-friendly platform Chatbot Farming community.

Cite This Article

P Sowjanya, Borra Rakesh, Gannu Vamsi, Gartham Pooja, Anapana Nagi Reddy, "Agriculture eCommerce Website with ML Chatbot," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 4, Apr 2024. https://doi.org/10.55041/IJSREM31860

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Publication Date

12/31/45408

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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