TM has been shown to be effective in several Information Retrieval ( IR ) and Natural Language Processing ( NLP ) applications . For example , in cross language IR , TM was used to handle out-of-vocabulary query words by mining transliterations between words in queries and top n retrieved documents and then using transliterations to expand queries ( Udupa et al , 2009a ) . In Machine Translation ( MT ) , TM can improve alignment at training time and help enrich phrase tables with named entities that may not appear in parallel training data . More broadly , TM is a character mapping problem .