Abstract
Malapropism is a type of semantic errors. It replaces one content word by another content word similar in sound but semantically incompatible with the context and thus destructing text cohesion. We propose to signal a malapropism when a pair of syntactically linked content words in a text exhibits the value of a specially defined Semantic Compatibility Index (SCI) lower than a predetermined threshold. SCI is computed through the web statistics of occurrences of words got together and apart. A malapropism detected, all possible candidates for correction of both words are taken from precompiled dictionaries of paronyms, i.e. words distant a letter or a few prefixes or suffixes from one another. Heuristic rules are proposed to retain only a few highly SCI-ranked candidates for the user’s decision. The experiment on mala-propism detection and correction is done for a hundred Russian text fragments—mainly from the web newswire—in both correct and falsified form, as well as for several hundreds of correction candidates. The raw statistics of occurrences is taken from the web searcher Yandex. Within certain limitations, the experiment gave very promising results.
Work done under partial support of Mexican Government (CONACyT, SNI) and CGEPI-IPN, Mexico. Many thanks to Denis Filatov for help with manuscript preparation.
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Bolshakov, I.A. (2005). An Experiment in Detection and Correction of Malapropisms Through the Web. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2005. Lecture Notes in Computer Science, vol 3406. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30586-6_91
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DOI: https://doi.org/10.1007/978-3-540-30586-6_91
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