Research on the Sentiment Analysis of Customer Reviews Based on the Ontology of Phone

DOI

10.2991/icemct-15.2015.59How to use a DOI?

Keywords

Product review, Ontology, Feature-sentiment mining, Polarity computation

Abstract

In this paper, we develop FOBPRM (Feature Ontology Based Product Review Miner) system, to semi-automatically build the ontology tree of Phone area and extract the most representative expressions and customer opinions in the reviews, which represents for feature-sentiment pairs. Finally we develop our method of polarity calculation of feature-sentiment pairs and generate the all-round summary for customers and vendors. Instead of putting the emphasis on feature extraction and sentiment classification as the existing work did,we focus on the association between the features and sub-features of a product and their associated sentiment that influence the polarity of the attributes in fine-grained in this paper. Ontology built by computation of special degree and similarity degree has improved the accuracy and recall rate of features, and the information entropy computes the polarity of feature-sentiment pairs. The whole system works out the desired result.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Can Yang
AU  - Zhiye Chen
AU  - Tianyi Wang
AU  - Pengfei Sun
PY  - 2015/06
DA  - 2015/06
TI  - Research on the Sentiment Analysis of Customer Reviews Based on the Ontology of Phone
BT  - Proceedings of the 2015 International Conference on Education, Management and Computing Technology
PB  - Atlantis Press
SP  - 273
EP  - 280
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemct-15.2015.59
DO  - 10.2991/icemct-15.2015.59
ID  - Yang2015/06
ER  -