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LREC
2010

United we Stand: Improving Sentiment Analysis by Joining Machine Learning and Rule Based Methods

8 years 10 months ago
United we Stand: Improving Sentiment Analysis by Joining Machine Learning and Rule Based Methods
In the past, we have succesfully used machine learning approaches for sentiment analysis. In the course of those experiments, we observed that our machine learning method, although able to cope well with figurative language could not always reach a certain decision about the polarity orientation of sentences, yielding erroneous evaluations. We support the conjecture that these cases bearing mild figurativeness could be better handled by a rule-based system. These two systems, acting complementarily, could bridge the gap between machine learning and rule-based approaches. Experimental results using the corpus of the Affective Text Task of SemEval '07, provide evidence in favor of this direction.
Vassiliki Rentoumi, Stefanos Petrakis, Manfred Kle
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where LREC
Authors Vassiliki Rentoumi, Stefanos Petrakis, Manfred Klenner, George A. Vouros, Vangelis Karkaletsis
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