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Showing 1 to 4 of 4 for “"big graphs"”.
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PPDQ-BG: Parallel Partition and Distributed Query Processing for Big Graphs
… often requires expensive computations to perform big graph analysis and query processing. Graph data represent irregular and unstructured relationships that usually result in a lack of locality so that it is often difficult to extract relevant information from big graphs. Although there have been …
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SCALABLE GRAPH REPRESENTATIONAL LEARNING ALGORITHMS FOR NETWORK MEDICINE
In the era of big data, advanced computational techniques are needed to process, analyze and visualize increasing amounts of data generated by high-throughput technologies. In this context, analyzing biomedical Knowledge Graphs that embrace bio- logical and medical concepts structured in ontologies …
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Optimisation techniques for finding connected components in large graphs using GraphX
… of finding connected components in undirected graphs has been well studied. It is an essential pre-processing step to many graph computations, and a fundamental task in graph analytics applications, such as social network analysis, web graph mining and image processing. Recently, it has been a …
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Enhancements in high performance subgraph enumeration on graphics processors
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01