Existing distributed publish/subscribe systems (DPSS) offer loosely coupled and easy to deploy content-based stream delivery services to a large number of users. However, the lack ...
We present a mining system that can predict the future health status of the patient using the temporal trajectories of health status of a set of similar patients. The main noveltie...
Data stream processing systems have become ubiquitous in academic and commercial sectors, with application areas that include financial services, network traffic analysis, battlef...
Abstract We address the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. We follow a two-step methodology: first we iden...
Data streams are a prevalent and growing source of timely data. As streams become more prevalent, richer interrogation of the contents of the streams are required. Value of the con...