LACK OF TRAINING DATA IN SENTIMENT CLASSIFICATION: CURRENT SOLUTIONS
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2012, Vol 1, Issue 4
Abstract
In recent years, sentiment classification has attracted much attention from natural language processing researchers. Most of researchers in this field consider sentiment classification as a supervised classification problem and train a classifier from a large number of labelled documents. . Unfortunately, in some language other than English, a reliable and sufficient labelled data is not always available and manually labelling a reliable and rich training data is very time-consuming. Until now, researchers have developed several techniques to the solution of the problem. This paper try to cover some techniques and approaches that be used in this area.
Authors and Affiliations
Mohammad Sadegh Hajmohammadi, Roliana Ibrahim
Keywords
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