图 书 馆
聚类同步Clustering by Synchronization |
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| 课程网址: | http://videolectures.net/kdd2010_shao_cs/ |
| 主讲教师: | Junming Shao |
| 开课单位: | 路德维希马克西米兰大学 |
| 开课时间: | 2010-10-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Synchronization is a powerful basic concept in nature regulating a large variety of complex processes ranging from the metabolism in the cell to social behavior in groups of individuals. Therefore, synchronization phenomena have been extensively studied and models robustly capturing the dynamical synchronization process have been proposed, e.g. the Extensive Kuramoto Model. Inspired by the powerful concept of synchronization, we propose Sync, a novel approach to clustering. The basic idea is to view each data object as a phase oscillator and simulate the interaction behavior of the objects over time. As time evolves, similar objects naturally synchronize together and form distinct clusters. Inherited from synchronization, Sync has several desirable properties: The clusters revealed by dynamic synchronization truly reflect the intrinsic structure of the data set, Sync does not rely on any distribution assumption and allows detecting clusters of arbitrary number, shape and size. Moreover, the concept of synchronization allows natural outlier handling, since outliers do not synchronize with cluster objects. For fully automatic clustering, we propose to combine Sync with the Minimum Description Length principle. Extensive experiments on synthetic and real world data demonstrate the effectiveness and efficiency of our approach. |
| 关 键 词: | 同步; 动态同步; 数据的内在结构; 合成 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-08-27：zyk |
| 阅读次数: | 90 |