A scalable hierarchical fuzzy clustering algorithm for text mining

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2004

Autores

Maria Eduarda Silva Mendes Rodrigues (Autor) FEUP; L. Sacks (Autor) Outra

Ata de Conferência Internacional

Título: 4th International Conference on Recent Advances in Soft Computing, RASC'2004

Páginas: 1-6

Nottingham, UK, December 2004

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

Abstract (EN): Clustering techniques are generally applied for finding unobvious relations and structures in data sets. In this paper, we propose a novel scalable hierarchical fuzzy clustering algorithm to discover relationships between information resources based on their textual content, as well as to represent knowledge through the association of topics covered by those resources. The algorithm addresses the important problem of defining a suitable number of clusters for appropriately capturing all the topics of the knowledge domain. In particular, the sought granularity level defines the number of clusters. Furthermore, the algorithm exploits the concept of asymmetric similarity to link clusters hierarchically and to form a topic hierarchy

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6