Abstract
Unsupervised and knowledge-free natural language processing in the Structure Discovery paradigm has shown to be successful and capable of producing a pre-processing quality equal to traditional systems, if just sufficient in-domain raw text can be provided. It is therefore not only a viable alternative for languages with scarce annotated resources, but might also overcome the acquisition bottleneck of language processing for new tasks and applications. In this chapter, the contributions of this book are summarised and put in to a larger perspective. An outlook is given on how Structure Discovery might change the way we design NLP systems in the future.
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© 2012 Springer-Verlag Berlin Heidelberg
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Biemann, C. (2012). Conclusion. In: Structure Discovery in Natural Language. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25923-4_8
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DOI: https://doi.org/10.1007/978-3-642-25923-4_8
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Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-25923-4
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