Electric Scooty Purchasing Recommendations Using Customer Review

Year : 2025 | Volume : 12 | Issue : 02 | Page : 92 102
    By

    Khushi Gupta,

  • Aarohi Chaudhary,

  • Khushi Kaushik,

  • Shobha Chaudhary,

  1. Student, Department of Information Technology, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India
  2. Student, Department of Information Technology, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India
  3. Student, Department of Information Technology, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India
  4. Assistant Professor, Department of Information Technology, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh, India

Abstract

As environmental awareness and sustainable practices have grown, E-scooters, often known as electric scooters, have gained popularity as a replacement for traditional automobiles. This research focuses on developing a recommendation framework for purchasing e-scooters, leveraging customer reviews as the primary data source. By analyzing reviews from diverse platforms, the framework aims to identify critical factors influencing customer satisfaction, including performance, battery life, design, comfort, and cost-efficiency. When we are considering things online, we frequently start by reading online reviews. When assessing a possible acquisition, we might have particular question in mind. We have to either search through many customer evaluations in an attempt to locate pertinent information, or we may use a Q&A system to ask the community directly for an answer. The rapid growth of electric bike market has led to overwhelming number of available options for consumers, making the process of customer feedback the most suitable process of selecting the bike and in enhancing product quality and promoting the adoption of sustainable transportation solutions.

Keywords: E-Bike, brand comparison, natural language processing (NLP), Eco-friendly vehicles, review based analysis

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Khushi Gupta, Aarohi Chaudhary, Khushi Kaushik, Shobha Chaudhary. Electric Scooty Purchasing Recommendations Using Customer Review. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):92-102.
How to cite this URL:
Khushi Gupta, Aarohi Chaudhary, Khushi Kaushik, Shobha Chaudhary. Electric Scooty Purchasing Recommendations Using Customer Review. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):92-102. Available from: https://journals.stmjournals.com/joaira/article=2025/view=216746


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Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 23/04/2025
Accepted 30/04/2025
Published 12/07/2025
Publication Time 80 Days
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