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 |
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