Robust Rule-based Approach in Arabic Processing

A rule-based approach to unknown word recognition in Arabic

This paper describes a small experiment to test a rule-based approach to unknown word recognition in Arabic. The morphological complexity of Arabic presents its challenges to a variety of NLP applications, but it can also be viewed as an advantage, if we can tap into the complex linguistic knowledge associated with these complex forms. In particular, the derived forms of verbs can be analysed a...

Arabic-Malay Machine Translation using Rule-based Approach

Arabic machine translation has been taking place in machine translation projects in recent years. This study concentrates on the translation of Arabic text to its equivalent in Malay language. The problem of this research is the syntactic and morphological differences between Arabic and Malay adjective sentences. The main aim of this study is to design and develop Arabic-Malay machine translati...

A rule-based approach for tagging non-vocalized Arabic words

In this work, we present a tagging system which classifies the words in a non-vocalized Arabic text to their tags. The proposed tagging system passes through three levels of analysis. The first level is a lexical analyzer that composed of a lexicon containing all fixed words and particles such as prepositions and pronouns. The second level is a morphological analyzer which relies on word struct...

Rule Merging in a Rule-Based Arabic Stemmer

Rule-based Approach for Arabic Root Extraction: New Rules to Directly Extract Roots of Arabic Words

Extracting word roots in Arabic language is very problematic 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 accordi...