DocumentCode
3441728
Title
Semantic Analysis and Implicit Target Extraction of Comments from E-Commerce Websites
Author
Hui Song ; Jianfeng Chu ; Yun Hu ; Xiaoqiang Liu
Author_Institution
Sch. of Comput. Sci. & Technol., Donghua Univ., Shanghai, China
fYear
2013
fDate
3-4 Dec. 2013
Firstpage
331
Lastpage
335
Abstract
In e-commerce websites, customers usually make comments, which include the properties of the product, the attitude to the vendor, express delivery information after buying the products. The information provides an important reference when others buy products in the website. In sentiment analysis, a finer-grained opinion mining approach focuses on not only the product itself as a whole but also product features, which can be a part or attribute of the product. Previous related research focuses on the explicit target mining but neglects the implicit ones. Whereas, the implicit features, which are implied by some words or phrases, are very significant and meaningful to express users´ opinion. In this paper, we propose a new approach to uniformly extract explicit and implicit opinion features from the comments. Our experimental results prove the effectiveness of the approach. The recall is improved, suggesting that taking the implicit features into consideration can extract more useful information, meanwhile, the precision is stable, not decreases.
Keywords
Web sites; customer satisfaction; data mining; electronic commerce; customer comments; delivery information; e-commerce Web sites; implicit target extraction; opinion mining; semantic analysis; sentiment analysis; Data mining; Electronic publishing; Encyclopedias; Feature extraction; Internet; Semantics; POS patterns; implicit syntactic extraction; opinion mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering (WCSE), 2013 Fourth World Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4799-2882-8
Type
conf
DOI
10.1109/WCSE.2013.62
Filename
6754311
Link To Document