| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560130 |
| ISSN: | 1405-5546 |
| Autores: | Rudrapal, Dwijen1 Das, Amitava2 Bhattacharya, Baby1 |
| Instituciones: | 1National Institute of Technology, Agartala, Texas. India 2Indian Institute Of Information Technology, Sricity, Uttar Pradesh. India |
| Año: | 2019 |
| Periodo: | Ene-Mar |
| Volumen: | 23 |
| Número: | 1 |
| Paginación: | 143-152 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | Textual entailment (TE) is a unidirectional relationship between two expressions where the meaning of one expression called Hypothesis (H), infers from the other expression called Text (T). The definition of TE is rigid in a sense that if the H entails from T but lacks minor information or have some additional information, then the pair is treated as non-entailed. In such cases, we could not measure the relatedness of a T-H pair. Partial textual entailment (PTE) is a possible solution of this problem which defines partial entailment relation between a T-H pair. PTE relationship can plays an important role in different Natural Language Processing (NLP) applications like text summarization and question-answering system by reducing redundant information. In this paper we investigate the idea of PTE for Indian social media text (SMT). We developed a PTE annotated corpus for Bengali tweets and proposed a Sequential Minimal Optimization (SMO) based PTE recognition approach. We also evaluated our proposed approach through experiment results. |
| Keyword: | Textual entailment, Social media text, Text summarization, Partial textual entailment, Question-answering system, Machine learning |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
