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http://dx.doi.org/10.3745/KIPSTB.2007.14-B.7.559

Combining Sentimental Expression-level and Sentence-level Classifiers to Improve Subjective Sentence Classification  

Kang, In-Ho (CMU/LTI 연구소)
Publication Information
The KIPS Transactions:PartB / v.14B, no.7, 2007 , pp. 559-566 More about this Journal
Abstract
Subjective sentences express opinions, emotions, evaluations and other subjective ideas relevant to products or events. These expressions sometimes can be seen in only part of a sentence, thus extracting features from a full-sentence can degrade the performance of subjective-sentence-classification. This paper presents a method for improving the performance of a subjectivity classifier by combining two classifiers generated from the different representations of an input sentence. One representation is a sentimental phrase that represents an automatically identified subjective expression or objective expression and the other representation is a full-sentence. Each representation is used to extract modified n-grams that are composed of a word and its contextual words' polarity information. The best performance, 79.7% accuracy, 2.5% improvement, was obtained when the phrase-level classifier and the sentence-level classifier were merged.
Keywords
Subjective Sentence; Objective Sentence; Subjective Expression; Semantic Phrase; Sentiment Analysis;
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