Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study

arXiv: Computation and Language, Volume abs/1712.07004, 2017.

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Abstract:

Any-gram kernels are a flexible and efficient way to employ bag-of-n-gram features when learning from textual data. They are also compatible with the use of word embeddings so that word similarities can be accounted for. While the original any-gram kernels are implemented on top of tree kernels, we propose a new approach which is independ...More

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