Cross Lingual Information Retrieval with SMT and Query Mining

In this paper, we have taken the English Corpus and Queries, both translated and transliterated form. We use Statistical Machine Translator to find the result under translated and transliterated queries and then analyzed the result. These queries wise results can then be undergone mining and therefore a new list of queries is created. We have design an experimental setup followed by various steps which calculate Mean Average Precision. We have taken assistance ship of Terrier Open Source for the Information Retrieval. On the basis of created new query list, we calculate the Mean Average Precision and find a significant result i.e. 93.24% which is very close to monolingual results calculated for English language.