科学研究
报告题目:

Extension of Math: Intelligent Search via Math and Statistics Models on Big Data

报告人:

胡琴敏 教授(Ryerson University,Canada)

报告时间:

报告地点:

理学院东北楼四楼报告厅(404)

报告摘要:

Yesterday’s data analytics and insights were limited to (and for) traditional data, such as data from ERP, CRM and other databases. But as we have all seen, the data landscape has been rapidly changing over the past few years–90% of the data available today was created in just the last three years–and the landscape will continue to change due to the fastest growing. This situation is urging us to work out more open innovative data analytics to satisfy our new data age. We therefore propose intelligent search and analysis to provide continuous delivery of real-time and data driven insights. In particular, we bridge the gap between multiple data sources and users’desire by answering the following three questions: (1) how to understand users’queries? (2) how to identify the most relevant results to queries? (3) how to satisfy users’underlying goals?