This paper addresses the problem of real-word spell checking, i.e., the detection and correction of typos that result in real words of the target language. This paper proposes a methodology based on a mixed trigrams language model. The model has been implemented, trained, and tested with data from the Penn Treebank. The approach has been evaluated in terms of hit rate, false positive rate, and coverage. The experiments show promising results with respect to the hit rates of both detection and correction, even though the false positive rate is still high. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Fossati, D., & Di Eugenio, B. (2007). A mixed trigrams approach for context sensitive spell checking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4394 LNCS, pp. 623–633). Springer Verlag. https://doi.org/10.1007/978-3-540-70939-8_55
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