Norbert Roma

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Support vector machine (SVM) learning algorithms focus on finding the hyperplane that maximizes the margin (the distance from the separating hyperplane to the nearest examples) since this criterion provides a good upper bound of the generalization error. When applied to text classification, these learning algorithms lead to SVMs with excellent precision but(More)
In this paper, we describe the system and methods used for the CLARITECH entries in the TREC-8 Filtering Track. Our focus of participation was on the adaptive filtering task, as this comes closest to actual applications. In TREC-7, we proposed, evaluated, and proved effective two algorithms for threshold setting and updating—the delivery ratio mechanism,(More)
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