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ECML '98 Proceedings of the 10th European Conference on Machine Learning
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PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
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Text classification by support vector machines can benefit from semantic smoothing kernels that regard semantic relations among index terms while computing similarity. Adding expansion terms to the vector representation can also improve effectiveness. However, existing semantic smoothing kernels do not employ term expansion. This paper proposes a new nonlinear kernel for text classification to exploit semantic relations between terms to add weighted expansion terms.