A D-truss-equivalence Based Index for Community Search over Large Directed Graphs
IEEE Transactions on Knowledge and Data Engineering(2024)
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
.
MoreTranslated text
Key words
Community search,directed graphs,D-truss,Dtruss-equivalence
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined