Abstract
The article focuses on acquiring new vocabulary used to express opinion attributes. We apply two automated expansion techniques to a manually annotated corpus of attribute-level opinions. The first method extracts opinion attribute words using patterns. It has been augmented by the second, wordnet and similarity-based expansion procedure. We examine the types of errors and shortcomings of both methods and end up proposing two hybrid, machine learning approaches that utilise all the available information: rules, lexical and distributional. One of them proves highly successful.
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Wawer, A., Gołuchowski, K. (2012). Expanding Opinion Attribute Lexicons. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_8
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DOI: https://doi.org/10.1007/978-3-642-32790-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32789-6
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