This paper deals with building linguistic resources for Gulf Arabic, one of the Arabic variations, for sentiment analysis task using machine learning. To our knowledge, no previous works were done for Gulf Arabic sentiment analysis despite the fact that it is present in different online platforms. Hence, the first challenge is the absence of annotated data and sentiment lexicons. To fill this g...

Offline Arabic handwriting character recognition (AHCR) systems are very important since they make life easier for governments, researchers and scholars who are dealing with Arabic language in education, documentation and security. A widening use of the Arabic script in countries that deals with the Arabic language and countries that use the Arabic script in their languages such as Persian and ...

Named entity recognition is an involved task and is one that usually requires the usage of numerous resources. Recognizing Arabic entities is an even more difficult task due to the inherent ambiguity of the Arabic language. Previous approaches that have tackled the problem of Arabic named entity recognition have used Arabic parsers and taggers combined with a huge set of gazetteers and sometime...

This paper describes the parallel development of an Egyptian Arabic Treebank and a morphological analyzer for Egyptian Arabic (CALIMA). By the very nature of Egyptian Arabic, the data collected is informal, for example Discussion Forum text, which we use for the treebank discussed here. In addition, Egyptian Arabic, like other Arabic dialects, is sufficiently different from Modern Standard Arab...

We present OSMAN (Open Source Metric for Measuring Arabic Narratives) a novel open source Arabic readability metric and tool. It allows researchers to calculate readability for Arabic text with and without diacritics. OSMAN is a modified version of the conventional readability formulas such as Flesch and Fog. In our work we introduce a novel approach towards counting short, long and stress syll...

Recently the rate of written colloquial text has increased dramatically. It is being used as a medium of expressing ideas especially across the WWW, usually in the form of blogs and partially colloquial articles. Most of these written colloquial has been in the Egyptian colloquial dialect, which is considered the most widely dialect understood and used throughout the Arab world. Modern Standard...

We provide lexical profiling for Arabic by covering two important linguistic aspects of Arabic lexical information, namely morphological inflectional paradigms and syntactic subcategorization frames, making our database a rich repository of Arabic lexicographic details. First, we provide a complete description of the inflectional behaviour of Arabic lemmas based on statistical distribution. We ...

The main aim of this thesis is to build adaptive language models of Arabic text that can achieve the best compression performance over existing models. Prediction by partial matching (PPM) language models has been the best performing over the other adaptive language models through the past three decades in term of compression performance. In order to get such performance for Arabic text, the ri...

This paper explains for the Arabic language, how to extract named entities and topics from news articles. Due to the lack of high quality tools for Named Entity Recognition (NER) and topic identification for Arabic, we have built an Arabic NER (RenA) and an Arabic topic extraction tool using the popular LDA algorithm (ALDA). NER involves extracting information and identifying types, such as nam...