In general, word stemming is one of the most important factors that affect the performance of information retrieval systems. The optimization issues of Arabic light stemming algorithm as a main component in natural language processing and information retrieval for Arabic language are based on root-pattern schemes. Since Arabic language is a highly inflected language and has a complex morphologi...

Clitics in Arabic language can be attached to a stem or to each other without orthographic marks such as an apostrophe. In this paper we present a statistical study of clitics and its effect in Arabic language. We tokenize large Arabic text using white-spaces and an automatic clitics tokenizer (AMIRA 2.0) and compare the unique-word count in both cases with English language. We also show the re...

In this paper, we present the details of creating a pilot Arabic proposition bank (Propbank). Propbanks exist for both English and Chinese. However the morphological and syntactic expression of linguistic phenomena in Arabic yield a very different type of process in creating an Arabic propbank. Hence, we highlight those characteristics of Arabic that make creating a propbank for the language a ...

♣ This work was supported financially by Alakhawayn University in Ifrane, Morocco under R&D Grant RPF1/2001 and by CoreSoft SARL. * 0-7803-7952-7/03/$17.00  2003 IEEE. Abstract Barq is a distributed multilingual search engine with focus on the Arabic language. The Barq R&D project has involved, over a period of some two years, work on Arabic language processing, Arabic word root extraction, in...

In this paper, a novel for Query Translation and Expansion for enabling English/Arabic CLIR for both normal and OCR-Degraded Arabic Text model has been proposed, implemented, and tested. First, an English/Arabic Word Collocations Dictionary has been established plus reproducing three English/Arabic Single Words Dictionaries. Second, a modern Arabic Corpus has been built. Third, a model for simu...

Applications of statistical Arabic NLP in general, and text mining in specific, along with the tools underneath perform much better as the statistical processing operates on deeper language factorization(s) than on raw text. Lexical semantic factorization is very important in that aspect due to its feasibility, high level of abstraction, and the language independence of its output. In the core ...

The limited coverage of available Arabic language lexicons causes a serious challenge in Arabic cross language information retrieval. Translation in cross language information retrieval consists of assigning one of the semantic representation terms in the target language to the intended query. Despite the problem of the completeness of the dictionary, we also face the problem of which one of th...

Morphological analysis and disambiguation are crucial stages in a variety of natural language processing applications such as machine translation, especially when languages with complex morphology are concerned such as Arabic. Arabic is a highly flexional language, in that, the same root can lead to various forms according to its context. In this paper, we present a system which disambiguates t...

Arabic has a very complex morphological system, though a very structured one. Character patterns are often indicative of word class and word segmentation. In this paper, we e xplore a novel approach to Arabic word segmentation and part-of-speech tagging relying on character information. The approach is lexicon-free and does not require any morphological analysis, eliminat ing the factor of dict...

We carried out a masked priming lexical decision experiment to study whether visual letter similarity plays a role during the initial phases of word processing in young readers of Arabic (fifth graders). Arabic is ideally suited to test these effects because most Arabic letters share their basic shape with at least one other letter and differ only in the number/position of diacritical points (e...