Abstract
This paper presents a novel algorithm of extracting keywords from single-sentence natural language queries in English. The process involves applying a series of rules to a parsed query in order to pick out potential keywords based on part-of-speech and the surrounding phrase structure. A supervised machine learning method is also explored in order to find suitable rules, which has shown promising results when cross-validated with various training sets.
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Wang, D.X., Gao, X., Andreae, P. (2012). Automatic Keyword Extraction from Single-Sentence Natural Language Queries. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_56
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DOI: https://doi.org/10.1007/978-3-642-32695-0_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32694-3
Online ISBN: 978-3-642-32695-0
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