Enhancing English/Arabic CLIR Using Word Collocations and Statistical Translation and Transliteration Resources

In Cross Language Information Retrieval (CLIR), queries in one language retrieve documents in other language(s). This can be done through Query Translation that comes up against Translation/Transliteration challenges like ambiguity as the main problems. In this paper, a comprehensive solution has been introduced for these challenges. 1, 4 powerful English/Arabic Machine Readable Dictionaries (MRD) from English to Arabic, including a dictionary for collocations and 3 dictionaries for single English words that have been introduced from different perspectives, aiming to examine the effect of each perspective on the final query result. 2, A modern Arabic Corpus has been built. 3, a comprehensive model for Query Translation from English to Arabic that detects and translates collocations, single words translation and transliteration, and solves the replacement ambiguity, has been introduced. The experiments' results proved that the proposed models are very effective overcoming the Query Translation and CLIR challenges.