Arabic Natural Language Processing

Abstract

The Arabic language presents researchers and developers of natural language processing (NLP) applications for Arabic text and speech with serious challenges. The purpose of this article is to describe some of these challenges and to present some solutions that would guide current and future practitioners in the field of Arabic natural language processing (ANLP). We begin with general features of the Arabic language in Sections 1, 2, and 3 and then we move to more specific properties of the language in the rest of the article. In Section 1 of this article we highlight the significance of the Arabic language today and describe its general properties. Section 2 presents the feature of Arabic Diglossia showing how the sociolinguistic aspects of the Arabic language differ from other languages. The stability of Arabic Diglossia and its implications for ANLP applications are discussed and ways to deal with this problematic property are proposed. Section 3 deals with the properties of the Arabic script and the explosion of ambiguity that results from the absence of short vowel representations and overt case markers in contemporary Arabic texts. We present in Section 4 specific features of the Arabic language such as the nonconcatenative property of Arabic morphology, Arabic as an agglutinative language, Arabic as a pro-drop language, and the challenge these properties pose to ANLP. We also present solutions that have already been adopted by some pioneering researchers in the field. In Section 5 we point out to the lack of formal and explicit grammars of Modern Standard Arabic which impedes the progress of more advanced ANLP systems. In Section 6 we draw our conclusion.

Sentiment Analysis of Arabic Tweets in e-Learning

“…Even though they emphasised that it is a Natural Language Processing approach (NLP) that works relatively well for other languages, the main limitation of this approach is that it is not applicable to the Arabic language. The main reason for that is the morphological richness of Arabic as a language (Pang and Lee, 2008;Cambria et al, 2013;Duwairi et al, 2014;Farghaly and Shaalan, 2009;Farra et al, 2010). In fact, the Arabic informal (colloquial) language lacks structure and is difficult to standardise.…”

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“…Nowadays, MSA has become the standardized linguistic Arabic that is used in an official spoken occasions, (such as conferences and lectures) and in official documents (such as books, magazines, newspapers). In MSA, there is no orthographic representation such that Arabic NLP tasks require a higher disambiguation degree [16]. Moreover, a linguistic resource in MSA would be rich in both Arabic NLP and Penn Arabic Treebank annotations.…”

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“…Arabic is a Semitic language spoken by more than 330 million people as a native language (Farghaly & Shaalan, 2009). While Arabic language has many spoken dialects, it has a standard written language.…”

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