| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560421 |
| ISSN: | 1405-5546 |
| Autores: | Sancheti, Abhilasha1 Modani, Natwar1 Choudhary, Gautam2 Priyadarshini, Chintha3 Moparthi, Sai Sandeep4 |
| Instituciones: | 1Adobe Research, Big data Experience Lab, Bangalore. India 2Indian Institute Of Technology, Department of Computer Science, Roorkee. India 3Indian Institute Of Technology, Department of Mathematics, Kanpur. India 4Indian Institute Of Technology, Department of Computer Science, Bombay. India |
| Año: | 2019 |
| Periodo: | Jul-Sep |
| Volumen: | 23 |
| Número: | 3 |
| Paginación: | 1033-1042 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | In order to keep their audience engaged, authors need to make sure that the blogs or articles they write cater to the taste of their audience and are understood by them. With the rapid proliferation of online blogging websites, the participation of readers by expressing their opinions and reviews has also increased in the form of comments on the blogs. These comments are valuable source for the authors to understand how their audience are perceiving their blogs. We believe that associating comments to the specific part of the blog they refer to will help author in getting insights about parts of the blog which are being discussed and the questions or concerns that readers have about those parts. Moreover, categorizing these comments will further aid the author in imbibing the comments. In this work, we describe a method to associate comments to the specific parts of the blog and introduce a hierarchical way to categorize the comments as Suggestion, Agreement, Disagreement or Question. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Classification, Comments association, Support vector machine, Feature selection, Artificial intelligence |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
