Comparative Study of Machine Learning Approaches for Amazon Reviews-Reference-Cited by-同舟云学术

Comparative Study of Machine Learning Approaches for Amazon Reviews

Published:2018 Issue: Volume:132 Page:1552-1561
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Rathor Abhilasha Singh,Agarwal Amit,Dimri Preeti

Publisher

Elsevier BV

Subject

General Engineering

Reference52 articles.

1. Sentiment Analysis Of Smartphone Product Review Using Support Vector Machine Algorithm-Based Particle Swarm Optimization.;Wahyudi;Journal of Theoretical and Applied Information Technology,2016

2. Opinion Mining : Insight.;Rathor;International Journal Of Current Engineering And Scientific Research (IJCESR),2017

3. Ahlgren, Oskar. (2014) “Research On Sentiment Analysis:The First Decade.” Department of Information and Service Economy.

4. Review of Sentiment Classification Method and Opinion Mining : The Future Roadmap.;Bhole;International Journal of Engineering Research and Technology (IJERT),2014

5. Twitter Sentiment Analysis of Movie.;Amolik;International Journal of Engineering and Technology (IJET),2016

Cited by 36 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Framework for Choosing a Supervised Machine Learning Method for Classification Based on Object Categories : Classifying Subjectivity of Online Comments by Product Categories;Proceedings of the 13th International Conference on Advances in Information Technology;2023-12-06

2. Machine Learning Approach for Negation Handling in Sentiment Analysis;2023 Eleventh International Conference on Intelligent Computing and Information Systems (ICICIS);2023-11-21

3. Review on Sentiment Analysis of E-commerce Product Comments;2023 IEEE 15th International Conference on Advanced Infocomm Technology (ICAIT);2023-10-13

4. THE OVERSEAS DISSEMINATION AND RECEPTION OF THE TRANSLATION OF THE QUOTATIONS OF MAO ZEDONG: BASED ON AMAZON READER REVIEWS;MODERN VECTORS OF SCIENCE AND EDUCATION DEVELOPMENT IN CHINA AND UKRAINE;2023-05

5. Identification of Customers Satisfaction with Popular Online Shopping Apps in Saudi Arabia Using Sentiment Analysis and Topic modelling;Proceedings of the 2023 7th International Conference on E-Commerce, E-Business and E-Government;2023-04-27