Domain Dependent Product Feature and Opinion Extraction Based on E-Commerce Websites

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 183)

Abstract

The rapid growth of the Internet and social web communities has changed on-line merchandising. Opinions expressed on websites by the customers became useful information for new customers and product manufacturers. Opinion mining techniques started to be attractive as a method for processing user generated content with sentiment payload. Presented approach uses product reviews from e-commerce websites for the product feature opinion mining task. Manual data annotation process is avoided by fully automated building training data corpus. As a classifier CRF model is employed. Proof of concept on Polish e-commerce website was performed. Experiment has shown promising results.

Keywords

Association Rule Noun Phrase Opinion Mining Conditional Random Field Opinion Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarsawPoland

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