Abstract
In this paper, we propose an empirical Bayesian method for determining whether a word is used out of context. We suggest we can treat a word’s context as a multinomially distributed random variable, and this leads us to a simple and direct Bayesian hypothesis test for the problem in question. We demonstrate this method to be superior to a method based upon common practice in the literature. We also demonstrate how an empirical Bayes method, whereby we use the behaviour of other words to specify a prior distribution on model parameters, improves performance by an appreciable amount where training data is sparse.
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Jabbari, S., Allison, B., Guthrie, L. (2008). An Empirical Bayesian Method for Detecting Out of Context Words. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2008. Lecture Notes in Computer Science(), vol 5246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87391-4_15
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DOI: https://doi.org/10.1007/978-3-540-87391-4_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87390-7
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