Abstract: Graph data mining algorithms rely on graph canonical forms to compare different graph structures. These canonical form definitions depend on node and edge labels. In this paper, we introduce ...
Abstract: We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We self-multiply the clustered adjacency matrices to show attacker ...
A famous problem at the intersection of topology and combinatorial graph theory is the Utility Problem. Say you have three houses and three utilities and you need to connect each house to each utility ...
LONDON–(BUSINESS WIRE)–#ai–Cloud enterprise software leader BlackSwan Technologies has won the category for the Most Innovative Implementation of Knowledge Graph Technologies at the 2022 A-Team ...
Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph ...
An everyday problem in our industry is understanding how software is consuming resources, particularly CPUs. What exactly is consuming how much, and how did this change since the last software version ...
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