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This paper introduces a novel, parallel, and scalable implementation of the VF2 algorithm for subgraph monomorphism developed in the …

The hypergraph community detection problem seeks to identify groups of related vertices in hypergraph data. We propose an …

Analyzing large-scale graphs poses challenges due to their increasing size and the demand for interactive and user-friendly analytics …

Counting and finding triangles in graphs is often used in real-world analytics to characterize cohesiveness and identify communities in …

Massive-scale analytics is an emerging field that integrates the power of high-performance computing and mathematical modeling to …

Due to the emergence of massive real-world graphs, whose sizes may extend to terabytes, new tools must be developed to enable data …

Large scale graph algorithms are required to help extract useful information from graphs. One of the main challenges arises when the …

Exploratory graph analytics helps maximize the informational value from a graph. However, increasing graph sizes makes it impossible …

Large scale data sets from the web, social networks, and bioinformatics are widely available and can often be rep-resented by strings …

Machine learning (ML) is becoming a powerful tool for a variety of applications where artificial intelligence solutions are required. A …