图 书 馆
在社会化网络学习的影响概率Learning Influence Probabilities in Social Networks |
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| 课程网址: | http://videolectures.net/wsdm2010_goyal_lip/ |
| 主讲教师: | Amit Goyal |
| 开课单位: | 不列颠哥伦比亚大学 |
| 开课时间: | 2010-04-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Recently, there has been tremendous interest in the phenomenon of influence propagation in social networks. The studies in this area assume they have as input to their problems a social graph with edges labeled with probabilities of influence between users. However, the question of where these probabilities come from or how they can be computed from real social network data has been largely ignored until now. Thus it is interesting to ask whether from a social graph and a log of actions by its users, one can build models of influence. This is the main problem attacked in this paper. In addition to proposing models and algorithms for learning the model parameters and for testing the learned models to make predictions, we also develop techniques for predicting the time by which a user may be expected to perform an action. We validate our ideas and techniques using the Flickr data set consisting of a social graph with 1.3M nodes, 40M edges, and an action log consisting of 35M tuples referring to 300K distinct actions. Beyond showing that there is genuine influence happening in a real social network, we show that our techniques have excellent prediction performance. |
| 关 键 词: | 社会图; 数据集; 网络数据 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-05-21：王淑红(课程编辑志愿者) |
| 阅读次数: | 64 |