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Computational Linguistics - Special issue on web as corpus
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NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
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IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Lessons from building a Persian written corpus: Peykare
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ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
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FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
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AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
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The present study summarizes corpus-based research on linguistic characteristics from several different structural levels, in English as well as other languages, showing that register variation is inherent in natural language. It further argues that, due to the importance and systematicity of the linguistic differences among registers, diversified corpora representing a broad range of register variation are required as the basis for general language studies.First, the extent of cross-register differences are illustrated from consideration of individual grammatical and lexical features; these register differences are also important for probabilistic part-of-speech taggers and syntactic parsers, because the probabilities associated with grammatically ambiguous forms are often markedly different across registers. Then, corpus-based multidimensional analyses of English are summarized, showing that linguistic features from several structural levels function together as underlying dimensions of variation, with each dimension defining a different set of linguistic relations among registers. Finally, the paper discusses how such analyses, based on register-diversified corpora, can be used to address two current issues in computational linguistics: the automatic classification of texts into register categories and cross-linguistic comparisons of register variation.