Abstract
In this paper we propose a methodology to assess the syntax complexity of a sentence representing it as sequence of parts-of-speech and comparing Recurrent Neural Networks and Support Vector Machine. We have carried out experiments in English language which are compared with previous results obtained for the Italian one.
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References
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Schicchi, D., Lo Bosco, G., Pilato, G. (2020). Machine Learning Models for Measuring Syntax Complexity of English Text. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2019. BICA 2019. Advances in Intelligent Systems and Computing, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-25719-4_59
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DOI: https://doi.org/10.1007/978-3-030-25719-4_59
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