In this paper, we deal with mining sequential patterns in multiple data streams. Building on a state-of-the-art sequential pattern mining algorithm PrefixSpan for mining transact...
Many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. Since a data warehouse is typically updated...
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to...
Since 9/11, intelligence agencies in the United States have expanded experimentation and use of data mining and analysis techniques to combat terrorism. These efforts have generat...
Despite a high level of activity and a large number of researchers involved, current research in data mining is plagued with several serious problems that should be regarded as to...
Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorit...
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su
The increasing interest in time series data mining has had surprisingly little impact on real world medical applications. Practitioners who work with time series on a daily basis ...
Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamon...
The iHealth Explorer tool, developed by CSIRO and DoHA, delivers web services type data mining and analytic facilities over a web interface, providing desktop access to sophistica...
Damien McAullay, Graham J. Williams, Jie Chen, Hui...
An undergraduate elective course in data mining provides a strong opportunity for students to learn research skills, practice data structures, and enhance their understanding of a...
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...