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Searching and Analyzing on Massive Text Corpora

February 1, 2018 at 2:00 PM to 3:30 PM

Location:5345 Herzberg Laboratories
Cost:Free

Abstract

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?

Speaker Biography

Dr. Qinmin Vivian Hu is an Associate Professor in the School of Computer Science and Software Engineering at East China Normal University, Shanghai, China. She received her MSc and PhD in Computer Science at York University, Toronto, Canada.

Dr. Hu’s research centres on searching and analyzing big data arising from a variety of contexts, such as real-time question answering systems, intelligent medical search, clinical decision support systems, and sentiment analysis in social networks. In particular, she is interested in developing algorithms and systems to support the real-time processing of massive data for high performance, as well as making sense of such data by learning patterns through modelling the interactions of temporal, spatial and personal aspects. Dr. Hu’s research has been supported by NSFC, NSERC and industrial partners such as Tencent and Baidu.