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Extracting product features and opinions from product reviews using dependency analysis

Author(s)
Somprasertsri, Gamgarn
Lalitrojwong, Pattarachai
Date Issued
November 29, 2010
Type
Conference Paper
DOI
10.1109/FSKD.2010.5569865
Abstract
In web pages, the reviews are written in natural language and are unstructured-free-texts scheme. Online product reviews is considered as a significant informative resource which is useful for both potential customers and product manufacturers. The task of manually scanning through large amounts of review one by one is computational burden and is not practically implemented with respect to businesses and customer perspectives. Therefore it is more efficient to automatically process the various reviews and provide the necessary information in a suitable form. The task of product feature and opinion is to find product features that customers refer to their topic reviews. It would be useful to characterize the opinions about product. In this paper, we propose an approach to extract product features and to identify the opinions associated with these features from reviews through syntactic information based on dependency analysis. ©2010 IEEE.
Citation
Proceedings 2010 7th International Conference on Fuzzy Systems and Knowledge Discovery Fskd 2010, 5, 2358-2362, 2010
Subjects

Customer review

Dependency analysis

Opinion extraction

Opinion mining

Metrics
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