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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: 96