Using SOM to Mine Product Features from Free-Text Customer Reviews

Author

Yu, Chuanming ; An, Lu ; Zhang, Xiaoqing

Author_Institution

Bus. Sch., Univ. of Shanghai for Sci. & Technol., Shanghai, China

Volume

3

fYear

2009

fDate

14-16 Aug. 2009

Firstpage

473

Lastpage

477

Abstract

This study examines how the Self-Organizing Map (SOM) technique can be used to identify product features from free-text customer reviews. A novel SOM display named Â¿Attribute Accumulative MatrixÂ¿ is presented. To verify the validity of the proposed approach, 22157 restaurant reviews are collected and product features of catering industry are identified. The experiment results show that this approach can effectively identify the product features.

Keywords

catering industry; data mining; feature extraction; natural language processing; self-organising feature maps; attribute accumulative matrix; catering industry; free-text customer reviews; product feature mining; restaurant reviews; self-organizing map technique; Displays; Feature extraction; Humans; Information analysis; Information management; Internet; Motion pictures; Natural language processing; Negative feedback; Speech processing; Attribute Accumulative Matrix; Customer Reviews; Opinion Mining; Product Feature Identification; Self-Organization Map;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2009. ICNC '09. Fifth International Conference on

Conference_Location

Tianjin

Print_ISBN

978-0-7695-3736-8

Type

conf

DOI

10.1109/ICNC.2009.359

Filename

5366282