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ADAPTIVE REORDERING OF OBSERVATION SPACE TO IMPROVE PATTERN RECOGNITION
In: http://www.task.gda.pl/files/quart/TQ2007/01-02/tq111m-e.pdf (2007)
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Words Reordering Based On Statistical Language Model ...
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Words Reordering Based On Statistical Language Model ...
Abstract: There are multiple reasons to expect that detecting the word order errors in a text will be a difficult problem, and detection rates reported in the literature are in fact low. Although grammatical rules constructed by computer linguists improve the performance of grammar checker in word order diagnosis, the repairing task is still very difficult. This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns. ... : {"references": ["E.S., Atwell, How to detect grammatical errors in a text without parsing\nit. In Proceedings of the 3rd EACL, 38-45, 1987.", "A., Golding, A Bayesian hybrid for context-sensitive spelling correction.\nProceedings of the 3rd Workshop on Very Large Corpora, 39--53. 1995", "M.,Chodorow, C., Leacock. An unsupervised method for detecting\ngrammatical errors. In Proceedings of NAACL-00, 140-147. 2000.", "T. Heift, Designed Intelligence: A Language Teacher Model,\nUnpublished Ph.D. Dissertation, Simon Fraser University,1998", "T. Heift, Intelligent Language Tutoring Systems for Grammar Practice.\nZeitschrift f\u251c\u255dr Interkulturellen Fremdsprachenunterricht (Online), 6 (2),\n15 pp. 2001", "J., Bigert, O., Knutsson. Robust error detection: A hybrid approach\ncombining unsupervised error detection and linguistic knowledge. In\nProceedings of Robust Methods in Analysis of Natural language Data,\n(ROMAND 2002), 10-19, 2002.", "J., Sj\u00f6bergh, Chunking: an unsupervised method to find errors in ...
Keyword: Permutations filtering; Statistical languagemodel N-grams; Word order errors
URL: https://dx.doi.org/10.5281/zenodo.1056066
https://zenodo.org/record/1056066
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N-Grams: A Tool For Repairing Word Order Errors In Ill-Formed Texts ...
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N-Grams: A Tool For Repairing Word Order Errors In Ill-Formed Texts ...
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