Extracting word roots in Arabic language is very prob-lematic due to the specific morphological and structural changes in the language. To address this problem, several techniques have been proposed. This paper continues the problem of identifying and exploiting relationship amongst Arabic letters for Arabic root extraction begun in [1]. Eight different rules that detect the root letters according to other letters in the word have been pro-posed and tested, four of them benefiting from the idea of morphological substitution (MUTATION). The ap-proach has been evaluated using the Holy Quran words. The evaluation results show a promising root extraction algorithm
Stemming is a process of extracting the root of a given word, by stripping off the affixes attached...
Extracting the roots (stemming) of Arabic words is one of the most challenging skills taught to Arab...
The paper presents a rapid method of developing a shallow Arabic morphological analyzer. The analyze...
Extracting word roots in Arabic language is very problematic due to the specific morphological and s...
In this paper we present a new root-extraction approach for Arabic words. The approach tries to assi...
This paper presents a new root-extraction approach for Arabic words. The approach tries to assign fo...
In this paper we present a new root-extraction approach for Arabic words. The approach tries to assi...
Arabic language is distinguished by its morphological richness, which forces the workers in the fiel...
Analysis of Arabic language has become a necessity because of its big evolution; we propose in this ...
Arabic words are known to have complex morphological structure. The different structures produce var...
The performance of information retrieval in arabic language is very problematic due to the specific ...
Arabic words are known to have complex morphological structure. The different structures produce var...
Stemming in the Arabic language is extracting the root form of the verb, removing inflectional affix...
AbstractIn this paper, we address the problems of Arabic Text Classification and root extraction usi...
The paper presents a rapid method of developing a shallow Arabic morphological analyzer. The analyze...
Stemming is a process of extracting the root of a given word, by stripping off the affixes attached...
Extracting the roots (stemming) of Arabic words is one of the most challenging skills taught to Arab...
The paper presents a rapid method of developing a shallow Arabic morphological analyzer. The analyze...
Extracting word roots in Arabic language is very problematic due to the specific morphological and s...
In this paper we present a new root-extraction approach for Arabic words. The approach tries to assi...
This paper presents a new root-extraction approach for Arabic words. The approach tries to assign fo...
In this paper we present a new root-extraction approach for Arabic words. The approach tries to assi...
Arabic language is distinguished by its morphological richness, which forces the workers in the fiel...
Analysis of Arabic language has become a necessity because of its big evolution; we propose in this ...
Arabic words are known to have complex morphological structure. The different structures produce var...
The performance of information retrieval in arabic language is very problematic due to the specific ...
Arabic words are known to have complex morphological structure. The different structures produce var...
Stemming in the Arabic language is extracting the root form of the verb, removing inflectional affix...
AbstractIn this paper, we address the problems of Arabic Text Classification and root extraction usi...
The paper presents a rapid method of developing a shallow Arabic morphological analyzer. The analyze...
Stemming is a process of extracting the root of a given word, by stripping off the affixes attached...
Extracting the roots (stemming) of Arabic words is one of the most challenging skills taught to Arab...
The paper presents a rapid method of developing a shallow Arabic morphological analyzer. The analyze...