| Revista: | Journal of technology management & innovation |
| Base de datos: | CLASE |
| Número de sistema: | 000307921 |
| ISSN: | 0718-2724 |
| Autores: | Wang, Zan1 Tsim, Y.C1 Yeung, W.S1 Chan, K.C1 Liu, Jinlan2 |
| Instituciones: | 1Hong Kong Polytechnic University, Department of Industrial and Systems Engineering, Hong Kong. China 2Tianjin University, School of Management, Tianjin. China |
| Año: | 2007 |
| Volumen: | 2 |
| Número: | 1 |
| Paginación: | 11-24 |
| País: | Chile |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Analítico |
| Resumen en inglés | Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA) has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA) which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency. Probabilistic Latent Semantic Analyses (PLSA) in Bibliometric Analysis for Technology Forecasting |
| Disciplinas: | Bibliotecología y ciencia de la información, Ciencia y tecnología, Literatura y lingüística |
| Palabras clave: | Análisis y sistematización de la información, Tecnología, Semántica y semiótica, Bibliometría, Análisis semántico latente, Predicción tecnológica |
| Texto completo: | Texto completo (Ver HTML) |
