The Named Entity Recognition (NER) is a task in Information Extraction (IE). The Named entity recognition has become very important for natural language processing. The named entity recognition is defined as the detection and classification of entities from un-structured text where for the Arabic language, the named entity recognition is new in the natural language processing although it has pr...

Arabic Sign Language (ArSL) is the native language for the Arab deaf community. ArSL allows deaf people to communicate among themselves and with non-deaf people around them to express their needs, thoughts and feelings. Opposite to spoken languages, Sign Language (SL) depends on hands and facial expression to express the thought instead of sounds. In recent years, interest in translating sign l...

english is an important language in hong kong, an international city located on the southern coast of the people’s republic of china that, for over 150 years to 1997, was a british colony. this paper describes and analyses changes in teaching methodologies in the english language curriculum formally proposed for hong kong junior secondary schools from 1975 to the present day, to study how the c...

Arabic Numerals are one of the major aspects to be considered in Arabic language processing. In this paper, we present an approach for developing a numeral checker application for the Arabic language, called “Arabic Numerals Checker”. Arabic Numerals Checker is intended to help users achieve competence in writing according to the Arabic numeral rules. It is supported by an explanation facility ...

This paper presents a novel approach for Arabic root generation and lexicon development. The approach provides three algorithms; in the first algorithm Arabic word root is generated using the concept of permutation and combination, the root generator algorithm generates roots by applying permutations to the Arabic alphabetic letters. Then, the second algorithm is used for developing difference ...

Language modeling for large-vocabulary conversational Arabic speech recognition is faced with the problem of the complex morphology of Arabic, which increases the perplexity and out-of-vocabulary rate. This problem is compounded by the enormous dialectal variability and differences between spoken and written language. In this paper we investigate improvements in Arabic language modeling by deve...

Arabic morphological analysis is one of the essential stages in Arabic Natural Language Processing. In this paper we present an approach for Arabic morphological analysis. This approach is based on Arabic morphological automaton (AMAUT). The proposed technique uses a morphological database realized using XMODEL language. Arabic morphology represents a special type of morphological systems becau...

Arabic dialects present a special problem for natural language processing because there are few Arabic dialect resources, they have no standard orthography, and they have not been studied much. However, as more and more written dialectal Arabic is found on social media, natural language processing for Arabic dialects has become an important goal. We present a methodology for creating a morpholo...

The Arabic language has a very rich morphology where a word is composed of zero or more prefixes, a stem and zero or more suffixes. This makes Arabic data sparse compared to other languages, such as English, and consequently word segmentation becomes very important for many Natural Language Processing tasks that deal with the Arabic language. We present in this paper two segmentation schemes th...