Abstract
One of the main issues faced by cross language information retrieval (CLIR) is out of vocabulary (OOV) words. Those are words not found in the dictionary. Bilingual dictionaries in general do not cover most proper nouns, which are usually primary keys in a query. As they are spelling variants of each other in most languages, using a string matching technique against the target database index is the common approach taken to find the target language correspondents of the original query keys. N-gram technique proved to be the most effective among other string matching techniques. The issue arises when the languages dealt with have different alphabets. Transliteration is then applied based on phonetic similarities between the languages involved. In this study, both transliteration and the n-gram technique are combined to generate possible transliterations in an English-Arabic CLIR system. We call this technique: transliteration n-gram (TNG).
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