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AI Driven Scalable E-Commerce Marketplace Customer Review Analysis & Actionable Insights

Published: 15 December 2023 Publication History

Abstract

Each e-commerce marketplace consists of thousands of merchants who are onboarded to list products for customers to purchase. The success of an e-commerce platform is heavily reliant on customer experience, and reviews present wonderful opportunities for analyzing and enhancing that experience. This paper aims to discuss and address the issue of analyzing and deriving actionable insights for ’merchant trouble detection,’ followed by measuring and analyzing customer sentiment. We propose a scalable approach for Japanese content that can also be extended to other languages. An attempt is made to address merchant shop trouble detection through review classification and sentiment analysis and also a comparative study of the performance of Auto ML models offered by cloud service providers in terms of performance, price and training time.

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  1. AI Driven Scalable E-Commerce Marketplace Customer Review Analysis & Actionable Insights

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    ICEME '23: Proceedings of the 2023 14th International Conference on E-business, Management and Economics
    July 2023
    507 pages
    ISBN:9798400708022
    DOI:10.1145/3616712
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

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    Publication History

    Published: 15 December 2023

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    Author Tags

    1. Automated Machine Learning (Auto ML)
    2. Google Cloud Platform (GCP)
    3. NLP
    4. sentiment analysis
    5. text classification

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