基于图论的化学分子数据挖掘研究  

Research on based-graph molecular data mining

作　　者：沙金[1] 张翠肖[1] 贾玉锋[1] 胡迎新[1] 

机构地区：[1]河北石家庄铁道学院计算机系,050043

出　　处：《微计算机信息》2006年第05X期180-182,共3页Control & Automation

基　　金：河北省自然科学基金资助(编号:E2004000206)

摘　　要：近年来,人们提出了很多频繁图模式挖掘的算法。首先分析了贪婪搜索策略,然后对各种不同的图数据挖掘的方法进行比较。受购物篮分析的影响,基于ILP方法引起了人们的重视。如何修改各种不同的图数据挖掘方法以适用化学分子数据的挖掘是人们研究的热点问题。因为化学分子不仅是标准的图结构,而且它有典型的频繁环和链结构,还有一些频繁出现的代表原子类型的结点,所以在这个领域有一些特殊问题需要考虑。In the last years quite a lot of algorithms concerning frequent graph pattern mining have been published. In this paper an overview on the differem methods for graph data mining is Oven,starting with the greedy searches.The ILP-based approaches are tak- en into account as well as ideas influenced by basket analyses proposed lately. A remaining question is how the different approaches can be tailored to meet the needs for mining molecules. In this area special problems occur as molecules are not just ＂normal arbitrary graphs＂. There are structures that are typical and frequent as rings and chains, some node types resp. atoms occur more often than others.

关 键 词：化学分子 分子片断 图挖掘 频繁结构模式 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]