ملخص: Information diusion kernels - similarity metrics in non- Euclidean information spaces - have been found to produce state of the art results for document classication. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of experiments addressing the well-known movie review data set of Pang and Lee, a de facto benchmark, comparing information diusion kernels with a standard RBF kernel ma- chine. Our results show that interpolation of unigram and bigram information is beneciary for sentiment classification.

لغة: إنجليزية