In many applications, stream data are too voluminous to be collected in a central fashion and often transmitted on a distributed network. In this paper, we focus on the outlier det...
Liang Su, Weihong Han, Shuqiang Yang, Peng Zou, Ya...
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
This paper describes a parallel algorithm for correlating or “fusing” streams of data from sensors and other sources of information. The algorithm is useful for applications w...
Data is often collected over a distributed network, but in many cases, is so voluminous that it is impractical and undesirable to collect it in a central location. Instead, we mus...
Enterprise-level applications are becoming complex with the need for event and stream processing, multiple query processing and data analysis over heterogeneous data sources such ...