G-thinker: A distributed framework for mining subgraphs in a big graph
Mining from a big graph those subgraphs that satisfy certain conditions is useful in many
applications such as community detection and subgraph matching. These problems have a …
applications such as community detection and subgraph matching. These problems have a …
面向大数据的图模式挖掘概率算法.
姜丽丽， 李叶飞， 豆龙龙， 陈智麒… - Application Research of …, 2020 - search.ebscohost.com
在当今大数据时代, MapReduce 等大数据处理框架处理数据能力有限, 其在处理有关图的数据
时常常显得缓慢低效, 典型如3 clique 计数问题, 故需要探究一种高效的算法处理这类clique …
时常常显得缓慢低效, 典型如3 clique 计数问题, 故需要探究一种高效的算法处理这类clique …
Supernodes: a generalization of the rich-club
In this article, we present two new concepts related to subgraph counting where the focus is
not on the number of subgraphs that are isomorphic to some fixed graph, but on the …
not on the number of subgraphs that are isomorphic to some fixed graph, but on the …
Scalable Subgraph Mining in a Big Graph
G Guo - 2022 - search.proquest.com
Finding from a big graph those subgraphs that satisfy certain conditions is useful in many
applications such as community detection and subgraph matching. These problems have a …
applications such as community detection and subgraph matching. These problems have a …
Alternative Branching Strategies in the Branch and Bound Algorithm by Using a k-clique covering vertex set for Maximum Clique Problems.
M Suyudi, AK Supriatna… - International Journal of …, 2020 - journal.rescollacomm.com
The Maximum clique problem (MCP) is graph theory problem that demand complete subgraf
with maximum cardinality (maximum clique) in arbitrary graph. Solving MCP usually use …
with maximum cardinality (maximum clique) in arbitrary graph. Solving MCP usually use …