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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM40893

Customer Service Chatbot With ML

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM40893

Volume:

9 |

1 |

Jan 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM40893

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

D.NT

Dr . N Thrimoorthy

MSAK

MadarNaik Sami Ali Khan

BSMG

Bar Shaik Muhammed Gouse

KAA

Khasab Adil Ahamed

SF

Shaik Faiz

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Abstract

In the modern business landscape, customer support plays a critical role in shaping customer experiences and building brand loyalty. With the growing demand for instant responses and 24/7 availability, organizations are increasingly exploring artificial intelligence (AI) solutions to enhance the efficiency and effectiveness of their customer service operations. This work aims to design and develop an intelligent customer support chatbot that leverages machine learning (ML) and natural language processing (NLP) techniques to deliver automated, yet personalized, customer assistance. The core objective is to build a machine learning-based chatbot capable of understanding and responding to a wide array of customer queries in real-time. Traditional customer service models often require significant human resources, leading to high operational costs and long response times. By integrating an AI powered chatbot into the customer support process, businesses can streamline operations, reduce response time, and provide customers with timely, accurate information.

KEYWORDS

· Natural Language Understanding (NLU): The chatbot uses NLTK and Speech recognition to process and understand the user’s input in natural language

Cite This Article

Dr . N Thrimoorthy, MadarNaik Sami Ali Khan, Bar Shaik Muhammed Gouse, Khasab Adil Ahamed, Shaik Faiz, "Customer Service Chatbot With ML," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 1, Jan 2025. https://doi.org/10.55041/IJSREM40893

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Editorial & Review Transparency

Publication Date

1/19/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Review Report (Confidential)
Copyright Form (Office)

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0

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2

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5

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Conflict of Interest

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

Funding Information

No funding information available for this research.

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