Discovering e-commerce user groups from online comments: An emotional correlation analysis-based clustering method-Reference-Cited by-同舟云学术

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Discovering e-commerce user groups from online comments: An emotional correlation analysis-based clustering method

Published:2024-01 Issue: Volume:113 Page:109035
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Ke Jia^ORCID,Wang Ying^ORCID,Fan Mingyue,Chen Xiaojun,Zhang Wenlong^ORCID,Gou Jianping

Funder

National Social Science Fund of China

Major Project of Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference30 articles.

1. eMarketer. Worldwide ecommerce continues double-digit growth following pandemic push to online. August 29, (2021) (Accessed on April 2023 https://www.emarketer.com/content/worldwide-ecommerce-continues-double-digit-growth-following-pandemic-push-online).

2. Platform or wholesale? A strategic tool for online retailers to benefit from third-party information;Kwark;MIS Quart,2017

3. User Preferance Similarity Based on Reviews Improvement of E-Commerce Recommadation Algorithm Using;Li,2021

4. Direction-based Text Interpretation as an Information Access Refinement;Hearst,1992

5. Research on E-commerce Personalized Recommendation Model Based on Semantic Emotion Analysis;Lv,2016

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