| 基于类别信息的特征子图选择策略 |
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| 引用本文： | 王桂娟,印鉴,詹卫许.基于类别信息的特征子图选择策略[J].计算机科学,2011,38(8):169-170,175. |
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| 作者姓名： | 王桂娟 印鉴 詹卫许 |
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| 作者单位： | (中山大学信息科学与技术学院 广州510275);(华南师范大学计算机学院 广州510631);(广东电网信息中心 广州510000) |
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| 摘 要： | 选择频繁的特征子图在基于频繁子图的图数据分类中起着非常重要的作用.提出了一种基于类别信息的特征子图选择策略,即从候选的频繁子图中选出独有频繁子图和显著频繁子图作为特征子图.实验结果显示,在对化合物数据分类时,该选择策略在分类性能上优于SVM方法特征选择策略和CEP方法的特征选择策略.
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| 关 键 词： | 频繁子图 图分类 图挖掘 特征选择 |
Feature Subgraph Selection Strategy Based on Category Information |
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| WANG Gui-juan,YIN Jian,ZHAN Wei-xu.Feature Subgraph Selection Strategy Based on Category Information[J].Computer Science,2011,38(8):169-170,175. |
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| Authors: | WANG Gui-juan YIN Jian ZHAN Wei-xu |
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| Affiliation: | (College of Information Science and Technology,Sun Yat sen University,Guangzhou 510275,China);(School of Computer,South China formal University,Guangzhou 510631,China);(Guangdong Power Grid Information Center,Guangzhou 510000,China) |
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| Abstract: | Selecting frequent subgraph as feature in graph datasets classification based on frequent subgraph plays a very important role. hhe new feature selection strategy was presented based on the information about classes,which is to select unictue and distinctive frectuent subgraphs as feature subgraphs from the candidate subgraphs. The results showed:in the compound data classification, the selection strategy is superior to AutoSVM's and CEP's in classification performance. |
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| Keywords: | Frequent subgraph pattern Graph classification Uraph mining Feature selection |
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