Knowledge Based Machine Translation

Machine translation, a part of computational Linguistics, belongs to Natural Language Processing (NLP) and is a hot issue in the computational society. Gap between the linguist and the computer programmer, gives birth to so many problems like lexical ambiguity, syntactic and structural ambiguity, polysemy, induction, discourses, anaphoric ambiguity and different shade of meanings. Mostly English-to-Urdu machine translation systems were developed without considering the target language and also semantics are not included in existing systems. This alarming problem generates several issues during Natural Language Processing. We, in this paper, proposed and designed a new Knowledge Based Machine Translation System to overcome the above mentioned problems by using data mining and text mining techniques. Our machine translation system fulfills almost all the requirements of Natural Language Processing and Computational Linguistics. Basically this system is designed for Urdu but it can be used for many other languages. The proposed system will give better results as compared to existing systems.