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A D-truss-equivalence Based Index for Community Search over Large Directed Graphs

IEEE Transactions on Knowledge and Data Engineering(2024)

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Abstract
Community Search (CS) aims to enable online and personalized discovery of communities. Recently, attention to the CS problem in directed graphs (di-graph) needs to be improved despite the extensive study conducted on undirected graphs. Nevertheless, the existing studies are plagued by several shortcomings, e.g., Achieving high-performance CS while ensuring the retrieved community is cohesive is challenging. This paper uses the D-truss model to address the limitations of investigating the CS problem in large di-graphs. We aim to implement millisecond-level D-truss CS in di-graphs by building a summarized graph index. To capture the interconnectedness of edges within D-truss communities, we propose an innovative equivalence relation known as D-truss-equivalence, which allows us to divide the edges in a di-graph into a sequence of super nodes (s-nodes). These s-nodes form the D-truss-equivalencebased index, DEBI, an index structure that preserves the truss properties and ensures efficient space utilization. Using DEBI, CS can be performed without time-consuming access to the original graph. The experiments indicate that our method can achieve millisecond-level D-truss community query while ensuring high community quality. In addition, dynamic maintenance of indexes can also be achieved at a lower cost. Our code is available at https://github.com/XieCanhao04/DEBI .
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Key words
Community search,directed graphs,D-truss,Dtruss-equivalence
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