A Novel Rule-Based Root Extraction Algorithm for Arabic Language

Thalji, Nisrean; Hanin, Nik Adilah; Hani, Walid Bani; Al-Hakeem, Sohair; Thalji, Zyad

doi:10.14569/ijacsa.2018.091015

Cited by 6 publications

(10 citation statements)

References 11 publications

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“…• Thalji et al, (2018) presented an algorithm to extract the Arabic roots according to set rules. They classified Arabic letters into two main groups: consonant letters that belong to the root and non-consonant letters that sometimes belong to the root and sometimes do not.…”

Section: Related Workmentioning

confidence: 99%

An Algorithm to Analyze Arabic Verbs Morphologically

Kassad,

Shaheen

2024

BAS-SJKFU

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Morphological analysis describes a word in isolation from the context, which is an important stage when trying to automatically understand and interpret the text. Many studies have provided morphological analyzers of Arabic verbs. However, although accurate, they do not deal with all cases of Arabic verbs. This research introduces an algorithm to analyze Arabic verbs morphologically based on regular expressions then on Morphological Database. The advantages of this algorithm are that it deals with verbs in their morphological cases, extracting their possible structures and some of their morphological data. This algorithm yielded highly accurate results after being tested on a sample of vocabulary and text. Furthermore, the extracted data is completely error-free. KEYWORDS language processing, match, pattern, regular expression, root, word structure

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Section: Related Workmentioning

confidence: 99%

An Algorithm to Analyze Arabic Verbs Morphologically

Kassad,

Shaheen

2024

BAS-SJKFU

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“…Besides, the researchers propose the best combination of factors that can help in the translation task within a proposed approach. On the other hand, Thalji et al [20] worked on the Arabic Language, created a rule-based algorithm for roots extraction to eliminate the weaknesses of the previous methods. They used the corpus of "Thalji" for the testing process and comparison with other works.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Translation Model [19] Madamira system translation model from Arabic to Chinese. 96.2% Rule-based root extraction [20] Provided a Root extraction algorithm based on Arabic roots' rules investigation.…”

Section: %mentioning

confidence: 99%

Arabic Text Processing Model: Verbs Roots and Conjugation Automation

2020

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The Natural Language Processing (NLP) is a process to automate the text or speech of Natural Languages. This automation is mainly conducted for Western languages. The Arabic Language got less focus in this area. This paper presents a Model to recognize an Arabic sentence. A new morphological model based on regular expressions is developed to recognize the Arabic verbs. A hash table containing all Arabic three-letters' root of verbs is implemented. The total number of Arabic verbs that are derived from three-letters' root size is 23090. The number of roots is 6104. A set of rules forming the Arabic grammar is used to derive and analyze the syntax of Arabic sentences. About 87% of the verbs represented in our regular expressions' engine are detected. Moreover, the sentences are also recognized. In several Surat of the Quran, only 9% of the detected verbs are false-positive (a non-verb declared as a verb), and 4% are considered false-negative (a verb is considered as a noun). This rate is mainly because we are not using vowels even that the Quran (our case study) is using them. The reason behind our decision is to be able to handle all Arabic texts, which mostly are not using vowels.

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“…These algorithms rely on linguistic rules and datasets to extract the root of a given Arabic word. They have proven to be effective in extracting roots from a variety of Arabic texts, including classical literature, modern newspapers, and social media [3]. The importance of Arabic root extraction algorithms lies in their ability to improve natural languages processing tasks such as machine translation, text classification, and sentiment analysis.…”

Section: Introductionmentioning

confidence: 99%

New Arabic Root Extraction Algorithm

Thalji,

Aljarrah,

Rateb

et al. 2023

IJACSA

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This research presents a new algorithm for Arabic root extraction, which aims to improve the accuracy of Arabic Natural Language Processing Algorithms by addressing the weaknesses and errors of existing algorithms. The proposed algorithm utilizes a database, that includes a collection of roots, patterns, and affixes, to generate potential derivation roots of a word without eliminating affixes initially. By matching the derived word with patterns to identify potential roots, the proposed algorithm avoids the inaccuracies caused by eliminating affixes based on expectation methods. The study conducted a comparison of the proposed algorithm with three commonly used Arabic root extraction algorithms. The evaluation process is performed on three corpora. Resultsshowed that the proposed algorithm achieved an average accuracy rate of 96%, which is significantly higher than the others.

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A Novel Rule-Based Root Extraction Algorithm for Arabic Language

Cited by 6 publications

References 11 publications

An Algorithm to Analyze Arabic Verbs Morphologically

An Algorithm to Analyze Arabic Verbs Morphologically

Arabic Text Processing Model: Verbs Roots and Conjugation Automation

New Arabic Root Extraction Algorithm

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