The Open UniversitySkip to content
 

An upgrading feature-based opinion mining model on Vietnamese product reviews

Ha, Quang-Thuy; Vu, Tien-Thanh; Pham, Huyen-Trang and Luu, Cong-To (2011). An upgrading feature-based opinion mining model on Vietnamese product reviews. In: Active Media Technology, Lecture Notes in Computer Science, Springer Berlin Heidelberg, pp. 173–185.

DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-3-642-23620-4_21
Google Scholar: Look up in Google Scholar

Abstract

Feature-based opinion mining and summarizing (FOMS) of reviews is an interesting issue in the opinion mining field. SentiWordNet is an useful lexical resource for opinion mining, especially for FOMS. In this paper, an upgrading FOMS model on Vietnamese reviews on mobile phone products is described. Feature words and opinion words were extracted based on some Vietnamese syntactic rules. Extracted feature words were grouped by using HAC clustering and semi-supervised SVM-kNN classification. Customers’ opinion orientation and summarization on features was determined by using a VietSentiWordNet, which had been extended from an initial VietSentiWordNet. Experiments on feature extraction and opinion summarization on features are showed.

Item Type: Conference or Workshop Item
Copyright Holders: 2011 Springer-Verlag
ISBN: 3-642-23619-7, 978-3-642-23619-8
ISSN: 0302-9743
Keywords: feature-word; feature-based opinion mining system; opinion summarization; opinion-word; reviews; syntactic rules; VietSentiWordnet dictionary
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 40126
Depositing User: Thanh Vu
Date Deposited: 12 May 2014 13:22
Last Modified: 02 May 2018 13:59
URI: http://oro.open.ac.uk/id/eprint/40126
Share this page:

Metrics

Altmetrics from Altmetric

Citations from Dimensions

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU