Triangle-Connected Top-k D-truss Community Search in Directed Graph

Recently, community search in directed graphs has received significant attention, and the D-truss model is recognized as a fundamental community structure. However, existing research has yet to thoroughly investigate the top-k query problem in directed graphs. In response, we introduces the triangle-connected top-k D-truss community search problem. First, following an in-depth analysis of the D-truss community structure, we develops the Hierarchical Equivalent Index HEI. Based on this index, we introduce an efficient triangle-connected top-k D-truss community search algorithm, Which enables the efficient retrieval of triangle-connected top-k D-truss community. Finally, we perform experiments using four real-world datasets. Experimental results indicate that, compared to state-of-the-art methods, the proposed algorithm enhances community search efficiency by one to two orders of magnitude.

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Publication Details

Published
2025-06-06
DOI
https://doi.org/10.1109/ngdn66208.2025.11182121
Primary Topic
Optimization and Search Problems
Type
article
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article

Triangle-Connected Top-k D-truss Community Search in Directed Graph

Chao Han, Chuanyu Zong
Optimization and Search Problems
article

Triangle-Connected Top-k D-truss Community Search in Directed Graph

Chao Han, Chuanyu Zong
article en

Abstract

Recently, community search in directed graphs has received significant attention, and the D-truss model is recognized as a fundamental community structure. However, existing research has yet to thoroughly investigate the top-k query problem in directed graphs. In response, we introduces the triangle-connected top-k D-truss community search problem. First, following an in-depth analysis of the D-truss community structure, we develops the Hierarchical Equivalent Index HEI. Based on this index, we introduce an efficient triangle-connected top-k D-truss community search algorithm, Which enables the efficient retrieval of triangle-connected top-k D-truss community. Finally, we perform experiments using four real-world datasets. Experimental results indicate that, compared to state-of-the-art methods, the proposed algorithm enhances community search efficiency by one to two orders of magnitude.

Shenyang Aerospace University (CN)
Openalex Percentile: Top 68%
Optimization and Search Problems
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