| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560420 |
| ISSN: | 1405-5546 |
| Autores: | Pathirana, Nadeesha1 Seneviratne, Sandaru1 Samarawickrama, Rangika1 Wolff, Shane1 Chitraranjan, Charith1 Thayasivam, Uthayasanker1 Ranasinghe, Tharindu2 |
| Instituciones: | 1University of Moratuwa, Department of Computer Science and Engineering, Moratuwa. Sri Lanka 2CodeGen International, Colombo. Sri Lanka |
| Año: | 2019 |
| Periodo: | Jul-Sep |
| Volumen: | 23 |
| Número: | 3 |
| Paginación: | 741-749 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | Concept identification is a crucial step in understanding and building a knowledge base for any particular domain. However, it is not a simple task in very large domains such as restaurants and hotel. In this paper, a novel approach of identifying a concept hierarchy and classifying unseen words into identified concepts related to restaurant domain is presented. Sorting, identifying, classifying of domain-related words manually is tedious and therefore, the proposed process is automated largely. Word embedding, hierarchical clustering, classification algorithms are effectively used to obtain concepts related to the restaurant domain. Further, this approach can also be extended to create a semi-automatic ontology on restaurant do-main. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Word embedding, Word2Vec, GloVe, Hierarchical clustering, Artificial intelligence |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
