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This book is the first volume that focuses on the specific challenges of machine translation with Arabic either as source or target language. It nicely fills a gap in the literature by covering approaches that belong to the three major paradigms of machine translation: Example-based, statistical and knowledge-based. It provides broad but rigorous coverage of the methods for incorporating linguistic knowledge into empirical MT. The book brings together original and extended contributions from a group of distinguished researchers from both academia and industry. It is a welcome and much-needed repository of important aspects in Arabic Machine Translation such as morphological analysis and syntactic reordering, both central to reducing the distance between Arabic and other languages. Most of the proposed techniques are also applicable to machine translation of Semitic languages other than Arabic, as well as translation of other languages with a complex morphology.
The use of mathematical logic as a formalism for artificial intelligence was recognized by John McCarthy in 1959 in his paper on Programs with Common Sense. In a series of papers in the 1960's he expanded upon these ideas and continues to do so to this date. It is now 41 years since the idea of using a formal mechanism for AI arose. It is therefore appropriate to consider some of the research, applications and implementations that have resulted from this idea. In early 1995 John McCarthy suggested to me that we have a workshop on Logic-Based Artificial Intelligence (LBAI). In June 1999, the Workshop on Logic-Based Artificial Intelligence was held as a consequence of McCarthy's suggestion. Th...
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