应电工系徐跃动老师的邀请，腾讯高级研究员杨春风博士来复旦访问，欢迎感兴趣的老师和同学参加！
下面是详细信息。
题目：Multi-site User Behavior Modeling and Its Application in Video Recommendation
报告人：杨春风 博士，腾讯研究院
时间：2017年10月14日（周六） 下午3:00~4:00
地点：物理楼521室
联系人：徐跃东
摘要：
由于不同网站的数据隔离，对用户在多个视频网站行为研究有待进行。本工作通过挖掘从电信ISP获取到的中国六大主流视频网站用户观影行为，对用户兴趣建模。数据分析显示，用户观影偏好同时具有跨网站一致性和每个网站独特性。我们提出一个Multi-site Probabilistic Factorization (MPF) 的生成模型来捕捉这两种特性，并阐述了该模型设计原则。一系列推荐系统实验结果展示，MPF相比于其他state-of-the-art的factorization模型，取得了最好的效果。这一结果为利用多网站行为数据构建推荐系统来实现win-win的可能性提供了启发。初步研究成果发表在著名的ACM SIGIR 2017会议上。
Abstract：
As online video service continues to grow in popularity, video content providers compete hard for more eyeball engagement. Some users visit multiple video sites to enjoy videos of their interest while some visit exclusively one site. However, due to the isolation of data, mining and exploiting user behaviors in multiple video websites remain unexplored so far. In this work, we try to model user preferences in six popular video websites with user viewing records obtained from a large ISP in China. The empirical study shows that users exhibit both consistent cross-site interests as well as site-specific interests. To represent this dichotomous pattern of user preferences, we propose a generative model of Multi-site Probabilistic Factorization (MPF) to capture both the cross-site as well as site-specific preferences. Besides, we discuss the design principle of our model by analyzing the sources of the observed site-specific user preferences, namely, site peculiarity and data sparsity. Through conducting extensive recommendation validation, we show that our MPF model achieves the best results compared to several other state-of-the-art factorization models with significant improvements of F-measure by 12.96%, 8.24% and 6.88%, respectively. Our findings provide insights on the value of integrating user data from multiple sites, which stimulates collaboration between video service providers.
个人简介：
杨春风，2012年于华中科技大学电子信息工程系获得学士学位，2017年于香港中文大学信息工程系获得博士学位。博士研究方向：推荐系统，（大数据）数据挖掘，社交网络分析，计算广告，用户建模。2014~2017在腾讯数据平台部实习，从事社交化视频推荐和计算广告的研究和实践。现在为腾讯公司数据平台部高级研究员，从事社交广告相关的研发。
