讲座时间：6月27日上午10：30-11：30

报告人：吕昌田博士

地点：海韵行政楼C414

摘要：Social media has become a popular data source as a surrogate for monitoring and detecting events. Analyzing social media (e.g., tweets) to reveal event information requires sophisticated techniques. Tweets are written in unstructured language and often contain typos, non-standard acronyms, and spam. In addition to the textual content, Twitter data form a heterogeneous information network where users, tweets, and hashtags have mutual relationships. These features pose technical challenges for designing event detection and forecasting methods. In this talk, I will present the design and implementation a fully automated forecasting system for significant societal events using open source data including tweets, blog posts, and news articles. I will describe the system architecture, individual models that leverage specific data sources, and a fusion engine that supports trading off specific evaluation criteria. I will also demonstrate its capability to forecast significant societal happenings.

报告人简介：吕昌田博士，弗吉尼亚理工大学教授，北弗州校区计算机系主任，数据挖掘与知识发现研究中心副主任(Associate Director of the Discovery Analytics Center at Virginia Tech)。2001获得明尼苏达大学双子城校区博士学位。曾担任18th IEEE International Conference on Tools with Artificial Intelligence人工智能工具国际会议程序委员会主席，17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems地理信息系统国际会议和2017年International Symposium on Spatial and Temporal Databases空间和时间数据库国际研讨会会议主席，ACM Special Interest Group on Spatial Information 计算机协会空间信息组副主席(2011-2014)。目前主要从事空间数据库，数据挖掘，人工智能，城市计算，和智能交通系统等方面的研究。在ACM KDD，IEEE CDM，ACM GIS, IJCAI，AAAI，TKDE，TKDD等高水平会议、期刊共发表150多篇文章。目前担任ACM Transactions on Spatial Algorithms and Systems，Data & Knowledge Engineering，GeoInformatica等期刊副主编。研究工作获得美国国家科学基金(NSF), 美国国家卫生研究院(NIH), 国防部(DoD),国防高等研究计划署(IARPA),弗吉尼亚州交通局(VDOT), and哥伦比亚特区交通局(DCDOT)等基金支持，获评美国计算机学会杰出科学家(ACM Distinguished Scientist)。

邀请人：网络空间安全系 肖亮教授