Abstract: Syntactic features are useful for many text classification tasks. Among these, tree kernels (Collins and Duy, 2001) have been perhaps the most robust and eective syntactic tool, appealing for their empirical success, but also because they do not require an answer to the dicult question of which tree features to use for a given task. We compare tree kernels to dierent explicit sets of tree features on five diverse tasks, and find that explicit features often perform as well as tree kernels on accuracy and always in orders of magnitude less time, and with smaller models. Since explicit features are easy to generate and use (with publicly available tools), we suggest they should always be included as baseline comparisons in tree kernel method evaluations.
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