Mining product reviews based on shallow dependency parsing

Authors:
Qi Zhang;Yuanbin Wu;Tao Li;Mitsunori Ogihara;Joseph Johnson;Xuanjing Huang
Affiliations:
Fudan University, Shanghai, China;Fudan University, Shanghai, China;Florida International University, Miami, FL, USA;University of Miami, Coral Gables, FL, USA;University of Miami, Coral Gables, FL, China;Fudan University, Shanghai, China
Venue:
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Year:
2009

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Abstract

This paper presents a novel method for mining product reviews, where it mines reviews by identifying product features, expressions of opinions and relations between them. By taking advantage of the fact that most of product features are phrases, a concept of shallow dependency parsing is introduced, which extends traditional dependency parsing to phrase level. This concept is then implemented for extracting relation between product features and expressions of opinions. Experimental evaluations show that the mining task can benefit from shallow dependency parsing.