We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We self-multiply the clustered adjacency matrices to show atta...
We present a novel approach for extracting cluttered objects based on their morphological properties1 . Specifically, we address the problem of untangling C. elegans clusters in h...
Tammy Riklin Raviv, Vebjorn Ljosa, Annie L. Conery...
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and findin...
Exploring communities is an important task in social network analysis. Such communities are currently identified using clustering methods to group actors. This approach often leads...
Link spam deliberately manipulates hyperlinks between web pages in order to unduly boost the search engine ranking of one or more target pages. Link based ranking algorithms such ...