The goal of multi-objective clustering (MOC) is to decompose a dataset into similar groups maximizing multiple objectives in parallel. In this paper, we provide a methodology, arch...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Ricar...
The problem of counting specified combinations of a given set of variables arises in many statistical and data mining applications. To solve this problem, we introduce the PDtree...
Chad Scherrer, Nathaniel Beagley, Jarek Nieplocha,...
Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulat...
Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas...
We present data from detailed observations of CityWall, a large multi-touch display installed in a central location in Helsinki, Finland. During eight days of installation, 1199 p...
Peter Peltonen, Esko Kurvinen, Antti Salovaara, Gi...
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...
Milind Kulkarni, Martin Burtscher, Calin Cascaval,...