International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 184 - Issue 11 |
Published: May 2022 |
Authors: Pravinkrishnan K., Prabavathy Balasundaram, Lekshmi Kalinathan |
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Pravinkrishnan K., Prabavathy Balasundaram, Lekshmi Kalinathan . An Overview of Chatbots using ML Algorithms in Agricultural Domain. International Journal of Computer Applications. 184, 11 (May 2022), 15-22. DOI=10.5120/ijca2022922082
@article{ 10.5120/ijca2022922082, author = { Pravinkrishnan K.,Prabavathy Balasundaram,Lekshmi Kalinathan }, title = { An Overview of Chatbots using ML Algorithms in Agricultural Domain }, journal = { International Journal of Computer Applications }, year = { 2022 }, volume = { 184 }, number = { 11 }, pages = { 15-22 }, doi = { 10.5120/ijca2022922082 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2022 %A Pravinkrishnan K. %A Prabavathy Balasundaram %A Lekshmi Kalinathan %T An Overview of Chatbots using ML Algorithms in Agricultural Domain%T %J International Journal of Computer Applications %V 184 %N 11 %P 15-22 %R 10.5120/ijca2022922082 %I Foundation of Computer Science (FCS), NY, USA
The agricultural sector plays a vital part in a country’s economic growth. It has already made a major contribution to advanced countries’ economic growth. The impact it hason less-developed countries’ economic development is vitally important. The farmers involved in agricultural activities lack the resources to stay updated with the information related to the latest advancements in technologies and farming practices. Existing human-involved operations such as Kissan Call Center (KCC), even though capable of delivering expected results, has its own drawbacks. Hence there is a need for an automated chatbot system that can function as a substitute to KCC. A chatbot system is a system that delivers domain-specific knowledge to its users. Such a system in the field of agriculture is very helpful in keeping the farmers updated. In this paper, existing works on such question-answer systems focusing entirely on works involving machine learning techniqueshave been reviewed. Suggestionsto improve the overall usability of the existing systemshave also been made.