图 书 馆
网络结构指数的图聚类Graph Clustering With Network Structure Indices |
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| 课程网址: | http://videolectures.net/icml07_rattigan_gcns/ |
| 主讲教师: | Matthew J. Rattigan |
| 开课单位: | 马萨诸塞大学 |
| 开课时间: | 2007-06-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Graph clustering has become ubiquitous in the study of relational data sets. We examine two simple algorithms: a new graphical adaptation of the k -medoids algorithm and the Girvan-Newman method based on edge betweenness centrality. We show that they can be effective at discovering the latent groups or communities that are defined by the link structure of a graph. However, both approaches rely on prohibitively expensive computations, given the size of modern relational data sets. Network structure indices (NSIs) are a proven technique for indexing network structure and efficiently finding short paths. We show how incorporating NSIs into these graph clustering algorithms can overcome these complexity limitations. We also present promising quantitative and qualitative evaluations of the modified algorithms on synthetic and real data sets. |
| 关 键 词: | 图聚类; 图论; 网络结构指数 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-07-06：heyf |
| 阅读次数: | 51 |