Attribute-Sentiment Pair Correlation Model Based on Online User Reviews
Joint Authors
Chen, Jinpeng
Fu, Xiang Ling
Wu, Ji
Liu, Shaohui
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-17
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
With the popularization of Internet applications and the rapid development of e-commerce, online shopping has become a widespread and important pattern of consumption.
Online user comments are an important data asset on e-commerce sites and have a great potential value for online users and merchants.
However, accurate and effective extraction of the characteristics of products and users’ sentiment evaluation from a tremendous amount of comments is a significant challenge.
Based on the concept of the LinLog energy model, this paper proposes an online review attribute-sentiment pair correlation model that evaluates user comments.
After preprocessing the comment data of mobile phones and constructing an attribute dictionary, the proposed model conducts a clustering analysis of attributes and sentiment pairs to gain accurate assessment of attributes in order to explore potential information from user comments.
Experiments conducted on one real-world dataset with comprehensive measurements verify the efficacy of the proposed model.
American Psychological Association (APA)
Fu, Xiang Ling& Wu, Ji& Chen, Jinpeng& Liu, Shaohui. 2019. Attribute-Sentiment Pair Correlation Model Based on Online User Reviews. Journal of Sensors،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1187285
Modern Language Association (MLA)
Fu, Xiang Ling…[et al.]. Attribute-Sentiment Pair Correlation Model Based on Online User Reviews. Journal of Sensors No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1187285
American Medical Association (AMA)
Fu, Xiang Ling& Wu, Ji& Chen, Jinpeng& Liu, Shaohui. Attribute-Sentiment Pair Correlation Model Based on Online User Reviews. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1187285
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1187285