01305nas a2200157   4500008004100000245008500041210006900126260001200195300001000207490000700217520083300224100000501057700000501062700002401067856005601091       2018                        eng d00a Non-words Spell Corrector of Social Media Data in Message Filtering Systems –0 aNonwords Spell Corrector of Social Media Data in Message Filteri  c04/2018  a64-750 v163 a<p>We develop an extended version of spell checker and corrector to check non-word errors in social media datasets, which will be used in message filtering systems especially for cyberbullying detection. We use the dictionary techniques to check words, twelve-word spell error checking and correction approaches to correct the non-word errors, and n-gram and Levenshtein distance to select the most suitable word among corrected words. If there is more than one corrected word we get from each approach, we use n-gram techniques to choose the corrected and reasonable word from the words in n-gram database. When we used the Levenshtein distance in our previous work, we found that it selected the first corrected word and it was not a reasonable one in some sentences. Therefore, we use the n-gram database in this paper.</p>
1 a1 a1 aAritsugi, Masayoshi  uhttp://dline.info/fpaper/jdim/v16i2/jdimv16i2_2.pdf