Data stream clustering algorithms play a pivotal role in the analysis of rapidly accumulating and evolving data sets, particularly as technologies such as the Internet of Things expand and generate ...

Data stream algorithms have become indispensable in handling the increasing volumes of network data generated in today’s digital environment. These algorithms skilfully process continuous streams of ...

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

Data runs business. We’ve been told this now immutable truth countless times throughout the early dawn and later progression of the information age. The entire act of so-called digital transformation ...

Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields. This problem has been widely studied in the context of graph stream processing.