首页   → 概率论
首页 → 应用数学
首页 → 计算机应用
  
    
 首页 → 应用数学
首页 → 计算机应用
冷启动链路预测Cold Start Link Prediction | 
  |
| 课程网址: | http://videolectures.net/kdd2010_leroy_cslp/ | 
| 主讲教师: | Vincent Leroy | 
| 开课单位: | IRISA公司 | 
| 开课时间: | 2010-10-01 | 
| 课程语种: | 英语 | 
| 中文简介: | 在传统的链路预测问题中,以社会网络快照为起点,通过图论方法对未来可能出现的链路进行预测。本文将冷启动链路预测作为一个社会网络结构的预测问题,在网络本身完全缺失的情况下,利用其它有关节点的信息进行预测。提出了一种基于自举概率图的两相方法。第一阶段以概率图的形式生成一个隐含的社会网络。第二阶段采用基于概率图的方法进行最终预测。我们对从Flickr收集的大量数据进行了经验评估,并将兴趣组作为初始信息。实验证实了我们方法的有效性。 | 
| 课程简介: | In the traditional link prediction problem, a snapshot of a social network is used as a starting point to predict, by means of graph-theoretic measures, the links that are likely to appear in the future. In this paper, we introduce cold start link prediction as the problem of predicting the structure of a social network when the network itself is totally missing while some other information regarding the nodes is available. We propose a two-phase method based on the bootstrap probabilistic graph. The first phase generates an implicit social network under the form of a probabilistic graph. The second phase applies probabilistic graph-based measures to produce the final prediction. We assess our method empirically over a large data collection obtained from Flickr, using interest groups as the initial information. The experiments confirm the effectiveness of our approach. | 
| 关 键 词: | 链路预测; 社会网络; 自举概率图 | 
| 课程来源: | 视频讲座网 | 
| 最后编审: | 2020-01-13:chenxin | 
| 阅读次数: | 136 | 
