Motif-based graph local clustering is a popular method for graph mining tasks due to its various applications, such as community detection, network optimization and graph learning. However, the ...

Did you know that the tools used for analyzing relationships between social network users or ranking web pages can also be extremely valuable for making sense of big science data? On a social network ...

Recently, Applied Mathematics graduate student Alec Dunton and his team won the Graph Challenge as a part of his summer internship at Lawrence Livermore National Laboratory. The GraphChallenge, as ...

Spectral clustering is quite complex, but it can reveal patterns in data that aren't revealed by other clustering techniques. Data clustering is the process of grouping data items so that similar ...

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory. This past October, as Jacob Holm and Eva Rotenberg were thumbing through a ...

Computer scientists are abuzz over a fast new algorithm for solving one of the central problems in the field. (January 15, 2017, update: On January 4, Babai retracted his claim that the new algorithm ...

Researchers took one of the most popular clustering approaches in modern biology -- Markov Clustering algorithm -- and modified it to run efficiently and at scale on supercomputers. Their algorithm ...