Title :
Product Review Information Extraction Based on Adjective Opinion Words
Author :
Luo, Yan ; Huang, Wei
Author_Institution :
Sch. of Manage., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
Product review mining can provide effective help for manufacturers, retailers and potential customers. We propose a framework of product review information extraction based on adjective opinion words. Firstly, we extract the web page information with web page template features. Secondly, we manually label seed adjective opinion word set, and expanded it to a set with words coverage reaching 90%. We also identify comparative sentence, word match and negation patterns. Finally, we summarize the product reviews from the various perspectives. In order to demonstrate our methods of the framework, we conduct the experiment with the product reviews of digital camera from www. Epinions.com. The experiment shows that the methods can provide the number of emotion polarity for the products and features.
Keywords :
Web sites; data mining; reviews; Web page information; Web page template features; digital camera; emotion polarity; negation pattern; product review information extraction; product review mining; seed adjective opinion word set; word match; Algorithm design and analysis; Data mining; Databases; Feature extraction; Semantics; Training; Web pages; adjective opinion words; information extraction; product review opinion mining;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
DOI :
10.1109/CSO.2011.209
