Abstract
We propose a machine learning approach for language-independent sentence boundary detection. The proposed method requires no heuristic rules and language-specific features, such as Part-of-Speech (POS) information, a list of abbreviations or proper names. With only the language-independent features, we perform experiments on not only an inflectional language but also an agglutinative language, having fairly different characteristics (in this paper, English and Korean, respectively). In addition, we obtain good performances in both languages.
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© 2004 Springer-Verlag Berlin Heidelberg
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Lee, DG., Rim, HC. (2004). Towards Language-Independent Sentence Boundary Detection. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2004. Lecture Notes in Computer Science, vol 2945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24630-5_17
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DOI: https://doi.org/10.1007/978-3-540-24630-5_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21006-1
Online ISBN: 978-3-540-24630-5
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