Discovering K-Core-Truss on Multilayer Graphs
Licheng Zhuo · 2024
Multilayer graphs are an effective framework for mode$\text{ling}$complex systems and have garnered significant research attention. Previous studies on dense structure decomposition in multilayer graphs have generally relied on a single perspective to describe density. In contrast, this paper introduces a novel model called multilayer-k-core-truss, which combines the concepts of vertex importance as defined by both k-core and k-truss, thereby capturing relationships across multiple dimensions. Building on this dense subgraph model, we develop a basic decomposition algorithm and propose the MKCT-Index to efficiently address search problems. Extensive experiments on several real-world da-tasets validate the effectiveness and efficiency of our proposed algorithms.