Sentiment Analysis in Customer Reviews for Product Recommendation in E-commerce Using Machine Learning

被引：0

作者：

Panduro-Ramirez, Jeidy ^{[1
]}

机构：

[1] Univ Autonoma Peru, Lima, Peru

来源：

2024 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND APPLIED INFORMATICS, ACCAI 2024 | 2024年

关键词：

Sentiment analysis; Customer reviews; Product recommendation; E-commerce; Machine learning; Online shopping; User feedback;

D O I：

10.1109/ACCAI61061.2024.10602027

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

When it comes to delivering product recommendations on e-commerce platforms, the purpose of this research project is to evaluate the use of sentiment analysis in customer reviews to give recommendations. During the course of this inquiry, the procedures that were utilized were developed from various machine-learning approaches. Customer reviews have emerged as a significant source of information for both customers and businesses alike as a result of the meteoric rise in the popularity of online purchasing. This is because customers provide feedback on products and services that they have purchased electronically. Through the utilization of sentiment analysis, e-commerce platforms can glean insights from the textual comments they receive from customers. After these insights have been collected, they can be used to enhance the algorithms that are used to recommend products to specific individuals. To analyze customer reviews, categorizing sentiments as either positive, negative, or neutral, and determining the essential characteristics and components that have an impact on customer satisfaction, we employ a strategy that involves the utilization of machine learning algorithms.

引用

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