Implementation of AI-Powered Robotic Chatbot for Intelligent Customer Interaction

This work presents the implementation of an AI-powered robotic chatbot designed to transform customer service in the online shopping sector. The chatbot is engineered to manage key customer interactions, including order placement, shipment tracking, order modifications, and cancellations, through a seamless conversational interface. Utilizing advanced natural language processing (NLP) models from Hugging Face Transformers and intent recognition via Dialogflow, the system ensures context-aware and precise responses. The integration reduces response times and enhances customer satisfaction. Experimental evaluation demonstrates high accuracy in intent recognition and response generation, validating the chatbot's efficacy as a reliable solution for automating customer service tasks. The paper details the system's architecture, implementation, and performance, highlighting its capability to optimize customer support and boost e-commerce operational efficiency.

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Publication Details

Published
2025-02-13
DOI
https://doi.org/10.1109/ic363308.2025.10956525
Citations
4
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
8.43
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article

Implementation of AI-Powered Robotic Chatbot for Intelligent Customer Interaction

C. Gokul, Premkumar Duraisamy, A Jeevanandhan, Shirthik Ram S
4 citations
Impact of AI and Big Data on Business and Society
8.43
article

Implementation of AI-Powered Robotic Chatbot for Intelligent Customer Interaction

C. Gokul, Premkumar Duraisamy, A Jeevanandhan, Shirthik Ram S
article en
4 citations

Abstract

This work presents the implementation of an AI-powered robotic chatbot designed to transform customer service in the online shopping sector. The chatbot is engineered to manage key customer interactions, including order placement, shipment tracking, order modifications, and cancellations, through a seamless conversational interface. Utilizing advanced natural language processing (NLP) models from Hugging Face Transformers and intent recognition via Dialogflow, the system ensures context-aware and precise responses. The integration reduces response times and enhances customer satisfaction. Experimental evaluation demonstrates high accuracy in intent recognition and response generation, validating the chatbot's efficacy as a reliable solution for automating customer service tasks. The paper details the system's architecture, implementation, and performance, highlighting its capability to optimize customer support and boost e-commerce operational efficiency.

KPR Institute of Engineering and Technology (IN)
Openalex Percentile: Top 3%
Impact of AI and Big Data on Business and Society
8.43
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Implementation of AI-Powered Robotic Chatbot for Intelligent Customer Interaction — C. Gokul, Premkumar Duraisamy, et al. · (2025) | TGRS Research Map | TGRS