Abstract
In this paper, we focus on classifying documents according to opinion and value judgment they contain. The main originality of our approach is to combine linguistic pre-processing, classification and a voting system using several classification methods. In this context, the relevant representation of the documents allows to determine the features for storing textual data in data warehouses. The conducted experiments on very large corpora from a French challenge on text mining (DEFT) show the efficiency of our approach.
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Plantié, M., Roche, M., Dray, G., Poncelet, P. (2008). Is a Voting Approach Accurate for Opinion Mining?. In: Song, IY., Eder, J., Nguyen, T.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2008. Lecture Notes in Computer Science, vol 5182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85836-2_39
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DOI: https://doi.org/10.1007/978-3-540-85836-2_39
Publisher Name: Springer, Berlin, Heidelberg
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