A Lightweight System for Correction of Arabic Derived Words

Nejja, Mohammed; Yousfi, Abdellah

doi:10.1007/978-3-319-30301-7_14

Cited by 7 publications

(3 citation statements)

References 6 publications

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“…The recent works can be summarized in several aspects. The aspect of techniques used; many studies generally focused on spell checking using different techniques, such as the rule-based approaches [11], [12], the distance similarity techniques, the exploitation of morphological analysis [13], [14], techniques based on phonetics, and finally hybrid ones [15]- [16]. Despite these efforts, no particular existing system has advantages and overcomes the entire spelling problem.…”

Section: Related Workmentioning

confidence: 99%

A new spell-checking approach based on the user profile

Saty¹,

Aouragh²,

Bouzoubaa³

2023

IJCDS

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This paper presents a new approach for spell-checking based on the user profile and that can be applied for any language. For this purpose and for the specific case of Arabic, spelling errors are studied and divided into 18 types. Then, a relationship model between users and their errors is obtained. The proposed architecture initially gives apposite values for a current user, then corrects misspelled words by applying the spelling rules, and the remaining words are corrected based on the probability given by an adopted model of the profile values. To show the efficiency of our profile-based approach, we conducted an experiment with a corpus of 11,908 words containing 1,888 errors. It showed that our approach suggests the correct word in 88.43% times and ranks it in the first four positions in 75.14% times. Moreover, using the same corpus we compared our implemented tool with two existing ones where ours ranked better in 69.79% times than Sahehly and 77.63% times than MS word.

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Section: Related Workmentioning

confidence: 99%

A new spell-checking approach based on the user profile

Saty¹,

Aouragh²,

Bouzoubaa³

2023

IJCDS

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“…Our objectives in this research work were to improve the scheduling rate and the precision rate in the edit distance based correction process [14]- [16], as well as to integrate the level of morphological analysis in the spelling correction phase [17], as well as taking into consideration the context in the correction process [18]. For a decade, our research team has consistently presented a series of relevant approaches in the field of spelling correction for errors made in typing Arabic texts [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Improving SpellChecking: an effective Ad-Hoc probabilistic lexical measure for general typos

Gueddah

Nejja

Iazzi

et al. 2022

IJEECS

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<p>Since the era of learning to write by human beings, mistakes made in typing words have occupied a privileged place in linguistic studies, integrating new disciplines into school curricula such as spelling and dictation. According to exhaustive studies that we have done in the field of spellchecking errors made in typing Arabic texts, very few research works that deal with typographical errors specifically caused by the insertion or missing of the blank-space in words. On the other hand, spelling correction software remains ineffective for handling this type of errors. Failure to process errors due to the insertion/missing of blankspace between and in words leads and brings us back to situations of ambiguity and incomprehension of the meaning of the typed text. To remedy this limitation of correction, we propose in this article an ad-hoc probabilistic method which is based jointly on two approaches. The first approach treats the errors due to deletion or missing of blank-space between or inside words, while the second puts emphasis in correcting space insertion errors in a word of course in addition to other kinds of elementary editing errors (addition, deletion, permutation of characters). Our new approach combines edit distance with n-gram language models to correct the errors already mentioned. Our new approach gave an accuracy rate that reaches 98,14% for missing blank-space errors (noted MBSE) and 89,5% for insertion blank-dpace errors (noted IBSE), which gives an average correction rate of around 95,26%. These results are very encouraging and show the interest and the importance of our approach.</p>

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“…• Probabilistic correction approaches such as n-grams decomposition [11], the correction method based on the noisy channel model [12], Alpha-code methods [13], or those based on probabilistic automatons [14], [15] • Since 2012 Gueddah, Yousfi and Nejja have carried out a series of work on spelling correction for the Arabic language, with the aim of improving the scheduling rate of solutions returned by the classical edit distance [16] [17] [18], or integrating the morphological analysis into the spelling correction phase [19] [20], or integrating context into spelling correction [21] [22].…”

Section: Introductionmentioning

confidence: 99%

Efficient Weighted Edit Distance and N-gram Language Models to Improve Spelling Correction of Segmentation Errors

Gueddah¹

2021

IJACSA

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In most research that has dealt with the correction of spelling errors, the errors are caused by the misuse of space (deletion or insertion of space) are not tackled. Forgetting to deal with this type of errors in the texts poses a problem of understanding and ambiguity of the meaning of the sentence containing these errors. In this article, we propose a new approach to correct errors due to the insertion of space in a word, and at the same time correct other types of editing errors. This approach is based on the edit distance and uses bi-grams language models to correct words in context. The test conducted on hundreds of erroneous words (by insertion of space and/or by simple editing errors) made it possible to assess the relevance and validity of the methods developed to correct this type of error. The approaches proposed in this article provide a very important clarification and reminder by comparing them to those of other existing approaches.

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A Lightweight System for Correction of Arabic Derived Words

Cited by 7 publications

References 6 publications

A new spell-checking approach based on the user profile

A new spell-checking approach based on the user profile

Improving SpellChecking: an effective Ad-Hoc probabilistic lexical measure for general typos

Efficient Weighted Edit Distance and N-gram Language Models to Improve Spelling Correction of Segmentation Errors

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