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Document Cards: A Top Trumps Visualization for Documents

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      A vector space model for automatic indexing

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        A STATISTICAL INTERPRETATION OF TERM SPECIFICITY AND ITS APPLICATION IN RETRIEVAL

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          Support vector machines for histogram-based image classification.

          Traditional classification approaches generalize poorly on image classification tasks, because of the high dimensionality of the feature space. This paper shows that support vector machines (SVM's) can generalize well on difficult image classification problems where the only features are high dimensional histograms. Heavy-tailed RBF kernels of the form K(x, y) = e(-rho)Sigma(i)/xia-yia/b with a x(i)(a) improves the performance of linear SVM's to such an extend that it makes them, for this problem, a valid alternative to RBF kernels.
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            Author and article information

            Journal
            IEEE Transactions on Visualization and Computer Graphics
            IEEE Trans. Visual. Comput. Graphics
            Institute of Electrical and Electronics Engineers (IEEE)
            1077-2626
            November 2009
            November 2009
            : 15
            : 6
            : 1145-1152
            10.1109/TVCG.2009.139
            © 2009
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