Novel Dense Subgraph Discovery Primitives: Risk Aversion and Exclusion Queries

CoRR(2019)

引用 10|浏览1
暂无评分
摘要
In the densest subgraph problem, given an undirected graph G(V, E, w) with non-negative edge weights we are asked to find a set of nodes \(S\subseteq V\) that maximizes the degree density w(S)/|S|, where w(S) is the sum of the weights of the edges in the graph induced by S. This problem is solvable in polynomial time, and in general is well studied. But what happens when the edge weights are negative? Is the problem still solvable in polynomial time? Also, why should we care about the densest subgraph problem in the presence of negative weights?
更多
查看译文
关键词
risk aversion
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要