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    Dimensionality reduction of features for text categorization
    (2007-12-01)
    Jitpakdee, Parisut
    ;
    Kreesuradej, Worapoj
    This paper proposes a new technique for dimensionality reduction of features for text categorization. Unlike conventional method, our phrase features are generated based on word sequences of different length (Multigrams) from phrases extracted from whole documents. Then, we utilize Odds ratio (OR) to perform phase feature selection. From preliminary experiments, the proposed techniques show better performance than that of conventional methods.
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    Text processing simplified ARTMAP neural network
    (2005-02-01)
    Kreesuradej, Worapoj
    ;
    Kunasit, Puangpaka
    This paper proposes text processing simplified ARTMAP neural network. The algorithm works directly on textual information without transforming to numerical value. The input layer of the neural network can directly receive a qualitative value without mapping the qualitative value into numerical value. Then, based on simplified fuzzy ARTMAP neural network and the concept of similarity measure for symbolic objects, the proposed neural network can assigns class labels to the objects correctly.