Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...
Cycles are one of the fundamental subgraph patterns and being able to enumerate them in graphs enables important applications in a wide variety of fields, including finance, biology, chemistry, and network science. However, to enable cycle enumeration in r ...
Various forms of real-world data, such as social, financial, and biological networks, can be
represented using graphs. An efficient method of analysing this type of data is to extract
subgraph patterns, such as cliques, cycles, and motifs, from graphs. For ...
Enumerating simple cycles has important applications in computational biology, network science, and financial crime analysis. In this work, we focus on parallelising the state-of-the-art simple cycle enumeration algorithms by Johnson and Read-Tarjan along ...
Many fundamental graph mining problems, such as maximal clique enumeration and subgraph isomorphism, can be solved using combinatorial algorithms that are naturally expressed in a recursive form. However, recursive graph mining algorithms suffer from a hig ...
Listing all maximal cliques of a given graph has important applications in the analysis of social and biological networks. Parallelisation of maximal clique enumeration (MCE) algorithms on modern manycore processors is challenging due to the task-level par ...
