In traditional text clustering methods, documents are represented as "bags of words" without considering the semantic information of each document. For instance, if two ...
Xiaohua Hu, Xiaodan Zhang, Caimei Lu, E. K. Park, ...
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
This paper introduces the problem of combining multiple partitionings of a set of objects into a single consolidated clustering without accessing the features or algorithms that d...
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...
Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algor...
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa...