2005 ExtractingProductFeaturesAndOpinionsFromReviews
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- (Popescu & Etzioni, 2005) ⇒ Ana-Maria Popescu, Oren Etzioni. (2005). “Extracting Product Features and Opinions from Reviews.” In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (HLT-EMNLP 2005).
Subject Headings: Information Extraction Algorithm, Opinion Mining Task, Opine System, Unsupervised Learning Algorithm.
Notes
Cited By
~457 http://scholar.google.com/scholar?cites=17903921651569673563
Quotes
Abstract
- Consumers are often forced to wade through many on-line reviews in order to make an informed product choice. This paper introduces Opine, an unsupervised information-extraction system which mines reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across products. Compared to previous work, Opine achieves 22% higher precision (with only 3% lower recall) on the feature extraction task. Opine's novel use of relaxation labeling for finding the semantic orientation of words in context leads to strong performance on the tasks of finding opinion phrases and their polarity.
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