Abstract
The chapter provides an introduction to probabilistic modelling of word sequences, revealing the often predictable nature of words’ occurrences in text. Many examples are shown to understand both the strengths and weaknesses (mostly the sparse data problem) of such models. The chapter presents how to build a word trigram model and use it in sequence prediction. Experiment: Performing orthographic error correction using language models.
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© 2016 Springer International Publishing Switzerland
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Barrière, C. (2016). Words in Sequence. In: Natural Language Understanding in a Semantic Web Context. Springer, Cham. https://doi.org/10.1007/978-3-319-41337-2_6
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DOI: https://doi.org/10.1007/978-3-319-41337-2_6
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41335-8
Online ISBN: 978-3-319-41337-2
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