Research on comment target extracting in Chinese online shopping platform

International Journal of Crowd Science

article

Zhishuo Liu¹  Qianhui Shen¹  Jingmiao Ma¹  Ziqi Dong² 

[1] School of Traffic and Transportation, Beijing Jiaotong University , Beijing, China;School of Traffic and Transportation, Beijing Jiaotong University , Beijing, China ...Show all authors

关键词: Opinion mining;    Association rule;    Implicit features;    SA-FCM;    SA-PSO;   

DOI  :  10.1108/IJCS-09-2018-0019

学科分类：内科医学

来源: Emerald Publishing

【 摘 要 】

Purpose This paper aims to extract the comment targets in Chinese online shopping platform. Design/methodology/approach The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment. Findings The extracting comment target method the authors proposed in this paper is effective. Research limitations/implications First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information. Practical implications Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients. Originality/value The extracting comment target method the authors proposed in this paper is effective.

【 授权许可】

CC BY