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FLAIRS
2009

The Role of Knowledge-based Features in Polarity Classification at Sentence Level

13 years 1 months ago
The Role of Knowledge-based Features in Polarity Classification at Sentence Level
Though polarity classification has been extensively explored at document level, there has been little work investigating feature design at sentence level. Due to the small number of words within a sentence, polarity classification at sentence level differs substantially from document-level classification in that resulting bag-of-words feature vectors tend to be very sparse resulting in a lower classification accuracy. In this paper, we show that performance can be improved by adding features specifically designed for sentence-level polarity classification. We consider both explicit polarity information and various linguistic features. A great proportion of the improvement that can be obtained by using polarity information can also be achieved by using a set of simple domainindependent linguistic features.
Michael Wiegand, Dietrich Klakow
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where FLAIRS
Authors Michael Wiegand, Dietrich Klakow
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