.png){kind=icon}
返回
An exact algorithm for the maximum quasi-clique problem
.png){kind=icon}
PRE
AI
DOI：10.1111/itor.12637.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Given a graph G=(V,E) and a threshold gamma is an element of(0,1], the maximum quasi-clique problem amounts to finding a maximum cardinality subset C* of the vertices in V such that the edge density of the graph induced in G by C* is greater than or equal to the threshold. This problem is NP-hard and has a number of applications in data mining, for example, in social networks or phone call graphs. In this work, we present an exact algorithm to solve this problem, based on a quasi-hereditary property. We also propose a new upper bound that is used for pruning the search tree. Numerical results show that the new approach is competitive and outperforms the best integer programming approaches in the literature. The new upper bound is consistently tighter than previously existing bounds.
Keyword:
maximum cardinality quasi-clique problem
maximum quasi-clique problem
maximum gamma-clique problem
maximum clique problem
graphs
graph density
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.9
论文数:
1.8K
被引数:
3.7K
机构
引用论文
.png){kind=icon}
分享收藏
分享收藏 没有更多内容
没有更多内容