| 基于对gSpan改进的有向频繁子图挖掘算法 |
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| 引用本文： | 周溜溜,业宁.基于对gSpan改进的有向频繁子图挖掘算法[J].南京大学学报(自然科学版),2011(5):532-543. |
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| 作者姓名： | 周溜溜 业宁 |
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| 作者单位： | 南京林业大学信息技术学院; |
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| 基金项目： | 国家自然科学基金(30671639); 江苏省自然科学基金(BK2009393); 江苏省青蓝工程学术带头人项目 |
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| 摘 要： | 提出的新算法对gSpan算法做了适用性改进,算法所采用的图编码技术与传统的频繁子图挖掘（FSG）,快速频繁子图挖掘（FFSM）,基于先验的图挖掘（AGM）等算法对图结构的编码均不同,由于对有向图进行了新的二维特征定义,因此可使算法适用范围有效地扩展至对有向图的学习,称之为基于对gSpan改进的有向频繁子图挖掘算法（DF...
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| 关 键 词： | 有向图挖掘 gSpan 频繁子图 适用性扩展 |
Digraph frequent subgraph mining based on gSpan |
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| Zhou Liu-Liu,Ye Ning.Digraph frequent subgraph mining based on gSpan[J].Journal of Nanjing University: Nat Sci Ed,2011(5):532-543. |
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| Authors: | Zhou Liu-Liu Ye Ning |
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| Institution: | Zhou Liu-Liu,Ye Ning (College of Computer Science and Technology,Nanjing Forestry University,Nanjing,210037,China) |
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| Abstract: | With graph data generated from various sources,meaningful pattern mining on this kind of data set becomes more and more urgent,especially along with the development of life science,yielding a considerable amount of directed graphs.However,existed related algorithms are all designed for undirected graphs,like Frequent Subgraph Discovery(FSG),Apriori-based Graph Mining(AGM),Fast Frequent Subgraph Mining(FFSM) and so on.Except for FFSM,there is not such an algorithm specially designed for directed graphs.Meanw... |
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| Keywords: | directed graph digraph frequent subgraph mining based on gSpan new data model complexity |
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