Doan Van Ban

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In this paper, we present an approach for handling attribute values of object classes with fuzzy information and uncertainty in object-oriented database based on theory hedge algebraic. In this approach, semantics be quantified by quantitative semantic mapping of hedge algebraic that still preserving in order semantics may allow manipulation data on the(More)
In this paper, we present an approach for handling the attribute values of object classes with fuzzy and uncertain information in object-oriented database based on hedge algebraic theory. Through this approach, semantics is quantified by semantics quantitative mapping of hedge algebra in such a way that still preserves semantic order and may allow to(More)
In this paper, we present our solution and experimental results of the application of semi-supervised machine learning techniques and the improvement of SVM algorithm to build text classification applications. Firstly, we create a features model which is based on labeled data, and then we will be improved it by the unlabeled data. The technique that is to(More)
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