A Mixed Trigrams Approach for Context Sensitive Spell Checking

Fossati, Davide; Eugenio, Barbara Di

doi:10.1007/978-3-540-70939-8_55

Cited by 24 publications

(17 citation statements)

References 10 publications

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“…2 These schemes encode words based on their sound 1 Spell correction is also considered as a variant of text normalization (Damerau, 1964;Tahira, 2004;Fossati and Di Eugenio, 2007). Here, we limit ourselves to the previous work on short text normalization.…”

Section: Urduphonementioning

confidence: 99%

An Unsupervised Method for Discovering Lexical Variations in Roman Urdu Informal Text

Rafae

Qayyum

Moeenuddin

et al. 2015

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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We present an unsupervised method to find lexical variations in Roman Urdu informal text. Our method includes a phonetic algorithm UrduPhone, a featurebased similarity function, and a clustering algorithm Lex-C. UrduPhone encodes roman Urdu strings to their phonetic equivalent representations. This produces an initial grouping of different spelling variations of a word. The similarity function incorporates word features and their context. Lex-C is a variant of k-medoids clustering algorithm that group lexical variations. It incorporates a similarity threshold to balance the number of clusters and their maximum similarity. We test our system on two datasets of SMS and blogs and show an f-measure gain of up to 12% from baseline systems.

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Section: Urduphonementioning

confidence: 99%

An Unsupervised Method for Discovering Lexical Variations in Roman Urdu Informal Text

Rafae

Qayyum

Moeenuddin

et al. 2015

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

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show abstract

“…The combination of word uni-gram and bi-grams is also proposed in [20]. To make use of the syntactic constraints of part-of-speech (POS), Fossati [22] and Golding [21] combine word tri-grams with POS tri-grams. Yang [23] incorporate word bi-grams into minimized-path segmentation method.…”

Section: Introductionmentioning

confidence: 99%

A study of binary local histogram correlation for automatic detection of optical printed Chinese character recognition errors

Zhang

Xie

Luo

2015

Optik

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“…Correction hit rate, it is the ratio between the number of typos corrected and the total number of typos [8].…”

Section: Correction Hit Rate and False Positive Ratementioning

confidence: 99%

Spelling Correction for Text Documents in Bahasa Indonesia Using Finite State Automata and Levinshtein Distance Method

2018

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Abstract. Any mistake in writing of a document will cause the information to be told falsely. These days, most of the document is written with a computer. For that reason, spelling correction is needed to solve any writing mistakes. This design process discuss about the making of spelling correction for document text in Indonesian language with document's text as its input and a .txt file as its output. For the realization, 5 000 news articles have been used as training data. Methods used includes Finite State Automata (FSA), Levenshtein distance, and N-gram. The results of this designing process are shown by perplexity evaluation, correction hit rate and false positive rate. Perplexity with the smallest value is a unigram with value 1.14. On the other hand, the highest percentage of correction hit rate is bigram and trigram with value 71.20 %, but bigram is superior in processing time average which is 01:21.23 min. The false positive rate of unigram, bigram, and trigram has the same percentage which is 4.15 %. Due to the disadvantages at using FSA method, modification is done and produce bigram's correction hit rate as high as 85.44 %.

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A Mixed Trigrams Approach for Context Sensitive Spell Checking

Cited by 24 publications

References 10 publications

An Unsupervised Method for Discovering Lexical Variations in Roman Urdu Informal Text

An Unsupervised Method for Discovering Lexical Variations in Roman Urdu Informal Text

A study of binary local histogram correlation for automatic detection of optical printed Chinese character recognition errors

Spelling Correction for Text Documents in Bahasa Indonesia Using Finite State Automata and Levinshtein Distance Method

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