A hybrid feature selection method is proposed to distinguish the salient features that allow identifying the viewpoint underlying a text review, that is, to determine its sentiment polarity. This method makes use of fundamental pre-processing tasks known as filter and wrapper techniques. The effectiveness of this approach is demonstrated on a data set where each document is represented by two distinct feature vectors based on two different sets of rules.


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    Title :

    Optimizing Feature Selection Techniques for Sentiment Classification


    Contributors:
    Uribe, D. (author)


    Publication date :

    2011-11-01


    Size :

    149430 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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