7 papers
Revisiting the Maximum Defective Clique Problem: Faster Branching and a Tighter Upper Bound
Kewu Yang, Kaiqiang Yu, Shengxin Liu +1
The -defective clique model relaxes the strict completeness constraint of the traditional clique by allowing up to missing edges, providing a robust formulation for detectin…
Maximal Biclique Enumeration with Improved Worst-Case Time Complexity Guarantee: A Partition-Oriented Strategy
Kaixin Wang, Kaiqiang Yu, Cheng Long
The maximal biclique enumeration problem in bipartite graphs is fundamental and has numerous applications in E-commerce and transaction networks. Most existing studies adopt a bran…
Efficient Computation of Maximum Flexi-Clique in Networks
Song Kim, Hyewon Kim, Kaiqiang Yu +4
Discovering large cohesive subgraphs is a key task for graph mining. Existing models, such as clique, k-plex, and γ-quasi-clique, use fixed density thresholds that overlook the na…
Maximum Degree-Based Quasi-Clique Search via an Iterative Framework
Hongbo Xia, Kaiqiang Yu, Shengxin Liu +2
Cohesive subgraph mining is a fundamental problem in graph theory with numerous real-world applications, such as social network analysis and protein-protein interaction modeling. A…
Temporal -Core Query, Revisited
Yinyu Liu, Kaiqiang Yu, Shengxin Liu +2
Querying cohesive subgraphs in temporal graphs is essential for understanding the dynamic structure of real-world networks, such as evolving communities in social platforms, shifti…
Fast Maximum Common Subgraph Search: A Redundancy-Reduced Backtracking Approach
Kaiqiang Yu, Kaixin Wang, Cheng Long +2
Given two input graphs, finding the largest subgraph that occurs in both, i.e., finding the maximum common subgraph, is a fundamental operator for evaluating the similarity between…