| Revista: | Polibits |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000368172 |
| ISSN: | 1870-9044 |
| Autores: | Sun, Jianshu1 Long, Chong1 Zhu, Xiaoyan1 Huang, Minlie1 |
| Instituciones: | 1Tsinghua University, Department of Computer Science and Technology, Beijing. China |
| Año: | 2009 |
| Periodo: | Ene-Jun |
| Número: | 39 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | Recently, as the amount of customer reviews grows rapidly on product service websites, it costs customers much time to select and compare their favorite products. Researchers have been aware of this problem and many studies are investigated to mine the opinions from the online reviews. Unfortunately, few previous works give comparisons or recommendations among the products. In this paper, we propose an automated system to address this problem. We first build a product feature sentiment database from the reviews. Then we perform the comparison among various products from both subjective and objective perspectives on the feature level. Finally, product recommendations can be suggested according to the previous comparisons and an evolution tree constructed from the reviews. Experiment results demonstrate the effectiveness of the proposed approach in mining the digital camera reviews. And now a demo system is put in to practical use |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Procesamiento de datos, Clientes, Comparación de productos, Minería de datos, Hábitos de consumo |
| Keyword: | Computer science, Data processing, Customers, Product comparison, Data mining, Consumption habits |
| Texto completo: | Texto completo (Ver HTML) |
