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Research Article

Integrating Intellectual Consciousness AI based on Ensemble Machine Learning for Price Negotiation in E-commerce using Text and Voice-Based Chatbot

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  • @ARTICLE{10.4108/eetiot.5370,
        author={Yagnesh Challagundla and Lohitha Rani Chintalapati and Trilok Sai Charan Tunuguntla and Anupama Namburu and Srinivasa Reddy K and Janjhyam Venkata Naga Ramesh},
        title={Integrating Intellectual Consciousness AI based on Ensemble Machine Learning for Price Negotiation in E-commerce using Text and Voice-Based Chatbot},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={IOT},
        year={2024},
        month={3},
        keywords={Price Negotiation, E-Commerce Negotiation, Online Shopping, Chatbot system, Voice assistant},
        doi={10.4108/eetiot.5370}
    }
    
  • Yagnesh Challagundla
    Lohitha Rani Chintalapati
    Trilok Sai Charan Tunuguntla
    Anupama Namburu
    Srinivasa Reddy K
    Janjhyam Venkata Naga Ramesh
    Year: 2024
    Integrating Intellectual Consciousness AI based on Ensemble Machine Learning for Price Negotiation in E-commerce using Text and Voice-Based Chatbot
    IOT
    EAI
    DOI: 10.4108/eetiot.5370
Yagnesh Challagundla1,*, Lohitha Rani Chintalapati1, Trilok Sai Charan Tunuguntla1, Anupama Namburu2, Srinivasa Reddy K1, Janjhyam Venkata Naga Ramesh3
  • 1: Vellore Institute of Technology University
  • 2: Jawaharlal Nehru University
  • 3: Koneru Lakshmaiah Education Foundation
*Contact email: yagneshnaidu1234@gmail.com

Abstract

Online shopping has experienced an enormous boost in recent years. With this evolution, the majority of internet shopping's capabilities have been developed, but some functions, such as negotiating with store owners, are still not available. This paper suggests employing a chatbot with a voice assistant to negotiate product prices. Customers can communicate with the chatbot to get assistance in finding a reasonable price for a product. In online purchasing, there is a possibility that the consumers or the product seller's budget may be compromised. In order to assist in purchasing, algorithm has been created in machine learning that uses the forecasting of historical data to avoid compromising situations. However, improper dataset or when irrelevant aspects or at- tributes of the data are used, price prediction might become less accurate. Ecommerce companies do not merely depend on price prediction tools due to the significant financial losses brought on even by a single inaccurate price prediction. Additionally, few models fail to perform well when the data saturates or when an attribute becomes inaccessible after the period for which the model's prediction was reliant. By controlling these alterations, the accuracy and dependability are preserved in the model pro- posed in this study.

Keywords
Price Negotiation, E-Commerce Negotiation, Online Shopping, Chatbot system, Voice assistant
Received
2023-12-17
Accepted
2024-03-05
Published
2024-03-11
Publisher
EAI
http://dx.doi.org/10.4108/eetiot.5370

Copyright © 2024 Y. Challagundla et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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