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Combining content and structure similarity for XML document classification using composite SVM kernels

13 years 24 days ago
Combining content and structure similarity for XML document classification using composite SVM kernels
Combination of structure and content features is necessary for effective retrieval and classification of XML documents. Composite kernels provide a way for fusion of content and structure information. In this paper, we demonstrate that a linear combination of simple and low cost kernels such as cosine similarity on terms and selective paths provide a good classification performance. We also propose a corpus-driven entropybased heuristic for determining the optimal combination weights. Classification experiments performed on
Pabitra Mitra, Saptarshi Ghosh
Added 05 Nov 2009
Updated 05 Nov 2009
Type Conference
Year 2008
Where ICPR
Authors Pabitra Mitra, Saptarshi Ghosh
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