图 书 馆
使用判别随机游动的图表分类Classification in Graphs using Discriminative Random Walks |
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| 课程网址: | http://videolectures.net/mlg08_callut_cgdrw/ |
| 主讲教师: | Jerome Callut |
| 开课单位: | 鲁汶大学 |
| 开课时间: | 2008-08-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This paper describes a novel technique, called D-walks, to tackle semi-supervised classification problems in large graphs. We introduce here a betweenness measure based on passage times during random walks of bounded lengths in the input graph. The class of unlabeled nodes is predicted by maximizing the betweenness with labeled nodes. This approach can deal with directed or undirected graphs with a linear time complexity with respect to the number of edges, the maximum walk length considered and the number of classes. Preliminary experiments on the CORA database show that D-walks outperforms NetKit (Macskassy & Provost, 2007) as well as Zhou et al's algorithm (Zhou et al., 2005), both in classification rate and computing time. |
| 关 键 词: | 半监督分类; 中介度量; 线性时间复杂度 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-06-30：cjy |
| 阅读次数: | 19 |