| W06-1003 | multilingual process , such as | crosslingual information retrieval | , must involve both resources |
| N10-1065 | downstream application , namely , a | Crosslingual Information Retrieval | system . We used the standard |
| P11-2094 | such as machine translation and | crosslingual information retrieval | . They are often translated through |
| D14-1129 | Machine Translation ( MT ) and | Crosslingual Information Retrieval | ( CLIR ) . However , it 's time-consuming |
| N04-3005 | ognition , machine translation , and | crosslingual information retrieval | components to enable real-time |
| W03-1502 | language processing , such as | crosslingual information retrieval | , crosslingual information extraction |
| W03-1003 | exploiting cross-lingual cues , via | crosslingual information retrieval | and machine translation , proposed |
| C04-1127 | performance gain by using current | crosslingual information retrieval | tech - niques . the source document |
| C04-1127 | corpora , are currently used in | crosslingual information retrieval | ( Larkey and Connell , 2003 ) |
| W06-2810 | example-based machine translation , | crosslingual information retrieval | , statistical machine translation |
| Q14-1020 | conceptual document representations for | crosslingual information retrieval | ( Potthast et al. , 2008 ; Cimiano |
| P04-1067 | al. , 2002 ) as a way to build a | crosslingual information retrieval | system from parallel corpora |
| P09-4008 | Machine Translation ( SMT ) and | Crosslingual Information Retrieval | ( CLIR ) sys - tems , as the |
| P07-1061 | of the CLEF 2003 evaluation for | crosslingual information retrieval | : each evaluation document was |
| W13-4039 | appropriate response is seen as | crosslingual information retrieval | where the response utterance |
| P06-2106 | Machine Translation ( MT ) and | Crosslingual Information Retrieval | ( CLIR ) application systems |
