This paper presents a loosely coupled service-composition paradigm. This paradigm employs a distributed data flow that differs markedly from centralized information flow adopted b...
David Liu, Jun Peng, Kincho H. Law, Gio Wiederhold
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
High dimensional directional data is becoming increasingly important in contemporary applications such as analysis of text and gene-expression data. A natural model for multivaria...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
In this paper we consider the problem of discovering frequent temporal patterns in a database of temporal sequences, where a temporal sequence is a set of items with associated da...