We investigate four hierarchical clustering methods (single-link, complete-link, groupwise-average, and single-pass) and two linguistically motivated text features (noun phrase he...
Vasileios Hatzivassiloglou, Luis Gravano, Ankineed...
We present a method to represent unstructured scalar fields at multiple levels of detail. Using a parallelizable classification algorithm to build a cluster hierarchy, we generate...
Clustering of data has numerous applications and has been studied extensively. It is very important in Bioinformatics and data mining. Though many parallel algorithms have been des...
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
Abstract— This paper presents a new hierarchical segmentation of the observed driving behavioral data based on the levels of abstraction of the underlying dynamics. By synthesizi...
Ato Nakano, Hiroyuki Okuda, Tatsuya Suzuki, Shinki...