Topic modeling and machine learning at Twitter

报告题目: Topic modeling and machine learning at Twitter

主讲人: Shuang Yang 研究员

主持人: 查宏远 教授

时间: 2014年12月29日 14:30

地址: 中北校区数学馆201室

报告摘要：
    We aim to provide a topic-aware multi-channel experience on Twitter to facilitate content creation, discovery and consumption. This requires the ability to organize in real-time a continuous stream of sparse and noisy texts (i.e., tweets) into hundreds of topics with measurable and stringently high precision.  I will introduce Jubjub, a high-precision tweet topic modeling system deployed inside Twitter, and the machine learning infrastructure behind it (and many other products).
报告人简介：
    Shuang is a Senior Research Scientist at Twitter, where he leads the machine learning infrastructure team. Prior to Twitter, he worked on machine learning and predictive analytics at Microsoft Research and Yahoo! Labs. He earned his Ph.D from Georgia Institute of Technology (advised by Professor Hongyuan Zha) in 2012. He has published actively at leading academic conferences and journals. He is the winner of Yahoo! Key Scientific Challenge award (2011) and Facebook Fellow (2011, finalist), and the recipient of the ACM SIGIR 2011 Best Student Paper award, the UAI 2010 Best Student Paper award (nominated) and the PAKDD 2008 Best Student Paper award.