A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
In traditional data clustering, similarity of a cluster of objects is measured by pairwise similarity of objects in that cluster. We argue that such measures are not appropriate f...
This paper investigates the new problem of automatic sense induction for instance names using automatically extracted attribute sets. Several clustering strategies and data source...
Ricardo Martin-Brualla, Enrique Alfonseca, Marius ...
Clustering time-series data poses problems, which do not exist in traditional clustering in Euclidean space. Specifically, cluster prototype needs to be calculated, where common s...
Spatial clustering is an important topic in knowledge discovery research. However, most clustering methods do not consider semantic information during the clustering process. In th...