图的数据挖掘算法研究  

Graph-based Data Mining Algorithm Research

作　　者：胡作霆[1] 董兰芳[1] 王洵[1] 

机构地区：[1]中国科学技术大学计算机科学技术系,合肥230027

出　　处：《计算机工程》2006年第3期76-78,共3页Computer Engineering

摘　　要：在计算机科学领域,图是最复杂的数据结构之一。它具有直观的表达形式,无论在研究领域还是在商业领域都有着广泛的应用。因此,如何从大量的图中挖掘出令人感兴趣的子图模式已经成为数据挖掘领域研究的热点之一。结合图论知识,对经典的Apriori算法进行改进,提出了一种图的数据挖掘方法,该方法能够有效地进行频繁子图的挖掘。Graph is one of the most complex data structures in computer science. It can be intuitively presented and has a wide variety of applications both in research and in business. Accordingly, how to derive the interesting subgraph patterns from the great volume of graph-structured data has become one of the hottest issues in data mining field. This article introduces some of the theoretical bases of graph, then proposes an improvement on the classic Apriori algorithm as well as a method of graph-based data mining, which can mine frequent subgraph patterns effectively.

关 键 词：图 APRIORI算法 数据挖掘 

分 类 号：TP311.12[自动化与计算机技术—计算机软件与理论]