A Study of Query Translation Using Google Machine Translation System

Query translation is an important step in cross-language information retrieval (CLIR), therefore the quality of the translations of queries can significantly affect CLIR's retrieval effectiveness. Recent advancement in commercial online machine translation (MT) systems, such as Google Translate, makes it possible for layman Web users to utilize the MT systems for perform cross-language search. To study the effectiveness of using MT for query translation, we conducted a set of CLIR experiments using Google Translate for translating queries. The experiments show that MT is an excellent tool for the query translation task, and with the help of relevance feedback, it can achieve significant improvement over the monolingual baseline. The MT based query translation not only works for long queries, but is also effective for the short Web queries.