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http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/2388| OClustR: A new graph-based algorithm for overlapping clustering | |
| AIREL PEREZ SUAREZ José Francisco Martínez Trinidad Jesús Ariel Carrasco Ochoa José Eladio Medina Pagola | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| Data mining Overlapping clustering Graph-based algorithms | |
| Clustering is a Data Mining technique, which has been widely used in many practical applications. From these applications, there are some, like social network analysis, topic detection and tracking, information retrieval, categorization of digital libraries, among others, where objects may belong to more than one cluster; however, most clustering algorithms build disjoint clusters. In this work, we introduce OClustR, a new graph-based clustering algorithm for building overlapping clusters. The proposed algorithm introduces a new graph-covering strategy and a new filtering strategy, which together allow to build overlapping clusterings more accurately than those built by previous algorithms. The experimental evaluation, conducted over several standard collections, showed that our proposed algorithm builds less clusters than those built by the previous related algorithms. Additionally, OClustR builds clusters with overlapping closer to the real overlapping in the collections than the overlapping generated by other clustering algorithms. | |
| Elsevier B.V. | |
| 2013 | |
| Artículo | |
| Inglés | |
| Estudiantes Maestros Público en general | |
| Pérez, A., et al., (2013). OClustR: A new graph-based algorithm for overlapping clustering, Neurocomputing Vol. 2013 (121): 234-247 | |
| CIENCIA DE LOS ORDENADORES | |
| Versión aceptada | |
| acceptedVersion - Versión aceptada | |
| Aparece en las colecciones: | Artículos de Ciencias Computacionales |
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| 205. OClustR- A new graph-based algorithm for overlapping clustering.pdf | 906.89 kB | Adobe PDF | Visualizar/Abrir |