Graph Contraction on Attribute-Based Coloring

Procedia Computer Science(2022)

引用 0|浏览1
暂无评分
摘要
Graph structures are nowadays pervasive in Big Data. It is often useful to regroup such data in clusters, according to distinctive node features, and use a representative element for each cluster. In many real-world cases, clusters can be identified by a set of connected vertices that share the result of some categorical function, i.e. a mapping of the vertices into some categorical representation that takes values in a finite set C. As an example, we can identify contiguous terrains with the same discrete property on a geographical map, leveraging Space Syntax. In this case, thematic areas within cities are labelled with different colors and color zones are analysed by means of their structure and their mutual interactions. Contracted graphs can help identify issues and characteristics of the original structures that were not visible before.
更多
查看译文
关键词
Graph Contraction,Clustering Contraction/Analysis,Divide-et-impera,Graph Analysis,2020 MSC,90C35,94A16,68W10
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