| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560750 |
| ISSN: | 1405-5546 |
| Autores: | Yerkhassym, Altynay1 Pak, Alexandr A.1 Akhmetov, Iskander1 Yelenov, Amir1 Gelbukh, Alexander3 |
| Instituciones: | 1Institute of Information and Computational Technologies, Kazajistán 2Kazakh-British Technical University, Kazajistán 3Instituto Politécnico Nacional, Centro de Investigación en Computación, México |
| Año: | 2022 |
| Periodo: | Oct-Dic |
| Volumen: | 26 |
| Número: | 4 |
| Paginación: | 1549-1556 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Natural language processing (NLP) field has been developing rapidly recently. This article consists mainly of literature review of the basic understanding and solving the causality problem in natural language processing field. Existing models may benefit from the concept of causality because conventional language models are brittle and spurious 10. Incorporating the principle of causality could assist in resolving this issue. Since this issue affects seriously on the accuracy value of NLP methods and algorithms, it is worth paying attention to. Content of the article includes the authors who have been covered this topic and have made researches respecting mentioned problem, the results that have been achieved, the methods and approached that have been used and the data that was used in researches. |
| Keyword: | Natural language processing, Neural network, Causality |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
