A Solution for Grouping Vietnamese Synonym Feature Words in Product Reviews

Author

Pham, Huyen-Trang ; Vu, Tien-Thanh ; Tran, Mai-Vu ; Ha, Quang-Thuy

Author_Institution

KTLab, Colege of Technol. Vietnam Nat. Univ., Hanoi, Vietnam

fYear

2011

fDate

12-15 Dec. 2011

Firstpage

503

Lastpage

508

Abstract

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.

Keywords

data mining; natural language processing; SVM-kNN classification; Vietnamese customer; feature based opinion mining; grouping Vietnamese synonym feature words; product reviews; Accuracy; Classification algorithms; Dictionaries; Feature extraction; Semantics; Support vector machines; Training; feature expression; feature expression vectors; feature word/phrase; feature-based opinion mining system; opinion summarization; opinion word; synonym feature expressions grouping;

fLanguage

English

Publisher

ieee

Conference_Titel

Services Computing Conference (APSCC), 2011 IEEE Asia-Pacific

Conference_Location

Jeju Island

Print_ISBN

978-1-4673-0206-7

Type

conf

DOI

10.1109/APSCC.2011.48

Filename

6128045