摘要
图作为一种重要的数据结构，可以用来描述事物之间的复杂联系。随着社交网络、Web网等网络中图数据数量不断增加，图数据挖掘技术逐渐成为研究热点。传统数据挖掘技术不断应用到图数据挖掘领域，加快图数据挖掘技术的发展。首先介绍图数据的定义，其次介绍现阶段图数据挖掘算法，包括图分类、图聚类、图查询、图匹配、图的频繁子图挖掘等，以及图数据库的发展现状，最后介绍图挖掘技术所面临的挑战。
Abstract
Graph as an important data structure, it can be used to describe the complex relationship between things. In social network, web network and other network in figure data is increasing , data mining technology has become a hot research. Traditional data mining technology has been applied to the field of graph data mining, and has accelerated the development of the technology of data mining. In this paper first introduced the definition of graph data, followed by the introduction of the current graph data mining algorithms, including classification graph, graph clustering, query graph, graph matching, graph of frequent subgraph mining, and graph database development status, at last, the paper introduces the graph mining technology is facing the challenges.
NETL
NSTL
维普
万方数据