| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560405 |
| ISSN: | 1405-5546 |
| Autores: | Sharma, Vijay Kumar Mittal, Namita1 |
| Instituciones: | 1Malaviya National Institute Of Technology Jaipur, Jaipur, Rajasthan. India |
| Año: | 2018 |
| Periodo: | Oct-Dic |
| Volumen: | 22 |
| Número: | 4 |
| Paginación: | 1277-1285 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Cross-Lingual Information Retrieval (CLIR) enables a user to query to the different language target documents. CLIR incorporates a Machine Translation (MT) technique which is in growing state for Indian languages due to the unavailability of enough resources. In this paper, a Statistical Machine Translation (SMT) system is trained on two parallel corpora separately. A large English language corpus is used for language modeling in SMT. Experiments are evaluated by using BLEU score, further, these experimental setups are used to translate the Hindi language queries for the experimental analysis of Hindi-English CLIR. Since SMT does not deal with morphological variants while the proposed Translation Induction Algorithm (TIA) deals with that, therefore, TIA outperforms the SMT systems in perspective of CLIR. |
| Disciplinas: | Literatura y lingüística |
| Palabras clave: | Lingüística aplicada |
| Keyword: | Cross-lingual information retrieval, Parallel corpus, Statistical machine translation, Morphological variants, Applied linguistics |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
