In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...
Document understanding techniques such as document clustering and multi-document summarization have been receiving much attention in recent years. Current document clustering meth...
Dingding Wang, Shenghuo Zhu, Tao Li, Yun Chi, Yiho...
Common document clustering algorithms utilize models that either divide a corpus into smaller clusters or gather individual documents into clusters. Hierarchical Agglomerative Clus...
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
Short texts clustering is one of the most difficult tasks in natural language processing due to the low frequencies of the document terms. We are interested in analysing these kind...
Diego Ingaramo, David Pinto, Paolo Rosso, Marcelo ...