A Solution for Grouping Vietnamese Synonym Feature Words in Product Reviews

Feature-based opinion mining is an interesting opinion mining issue. For this problem, feature words/phrases are discovered at sentence level. However, customers usually use different words/phrases referring to the same feature in reviews. To produce a meaningful summary, synonym feature words/phrases in domain, need to be grouped under the same feature. This paper proposes a solution for grouping synonym features in Vietnamese customer reviews based on semi-supervised SVM-kNN classification and HAC clustering. Experimental results on reviews in mobile phone domain demonstrate that the proposed method is promising for the task. The Purity, Accuracy measures are 0.68 and 0.65 respectively.

I. Introduction

In recent years, feature-based opinion mining (FOM) is an interesting issue described in articles, such as [1–3, 5, 12–14]. The target of this problem is to create a summary of customer reviews for each product feature. The summary provides a visual view for potential customers about opinions of customers who used the product. Concurrently, it helps the manufacturer to keep track and manage customer opinions.