Speaker: Yingcai Wu (Zhejiang University)
Online service providers, such as Twitter, Amazon, Google, and Wikipedia, generate huge volumes of user behavior data daily, in which valuable patterns and correlations of user behaviors are hidden. For companies, effective analysis of the behavior data allows them to learn more about their customers on an unprecedented scale to improve customer relations and develop social media marketing strategies. For governments, effective tracking of the behavior data allows them to detect and predict critical events to make proper decisions in a timely manner. However, analysis of the behavior data is challenging due to the enormous amount of data and the heterogeneity of information. In my talk, I will discuss the challenges of the research on visual behavior analytics, and then give some examples of applying interactive visualization techniques to making sense of the behavior data.