In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
— Distributed data mining has recently caught a lot of attention as there are many cases where pooling distributed data for mining is probibited, due to either huge data volume o...
Chak-Man Lam, Xiaofeng Zhang, William Kwok-Wai Che...
For the convenient reuse of large-scale 3D motion capture data, browsing and searching methods for the data should be explored. In this paper, an efficient indexing and retrieval...
We discuss the use of database met hods for data mining. Recently impressive results have been achieved for some data mining problems using highly specialized and clever data stru...
Marcel Holsheimer, Martin L. Kersten, Heikki Manni...