Hierarchical confidence-based active clustering

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Nogueira, BM (Autor) Outra; Jorge, AM (Autor) FCUP; Rezende, SO (Autor) Outra

Ata de Conferência Internacional

Título: Proceedings of the ACM Symposium on Applied Computing

Páginas: 216-217

27th Annual ACM Symposium on Applied Computing, SAC 2012

Trento, 26 March 2012 through 30 March 2012

Indexação

Scopus - 9 Citações

Outras Informações

ID Authenticus: P-008-4RQ

DOI: 10.1145/2245276.2245318

Abstract (EN): In this paper, we address the problem of semi-supervised hierarchical clustering by using an active clustering solution with cluster-level constraints. This active learning approach is based on a concept of merge confidence in agglomerative clustering. The proposed method was compared with an un-supervised algorithm (average-link) and a semi-supervised algorithm based on pairwise constraints. The results show that our algorithm tends to be better than the pairwise constrained algorithm and can achieve a significant improvement when compared to the unsupervised algorithm. © 2012 Authors.

Idioma: Inglês

Tipo (Avaliação Docente): Científica