Data mining model based on user reviews and star ratings
by Yusong Cheng; Lei Lyu; Jin Wenxin; Chenhui Wang
International Journal of High Performance Systems Architecture (IJHPSA), Vol. 9, No. 2/3, 2020

Abstract: With the rapid development of e-commerce, the research on sentiment analysis of online reviews has been paid more and more attention. This paper presents an Aspect-Level Sentiment Analysis Method based on long short-term memory (LSTM) and boot-strapping, which performs semantic mining and prediction on time-based data patterns and data combinations of text, star rating and helpful votes. A high prediction accuracy rate is obtained in the open data set. Compared with the traditional methods, which single analysis comment or evaluation, merchants can gain a deeper understanding of user feedback from sentiment analysis.

Online publication date: Tue, 01-Dec-2020

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