Making Sense of Big Data

It would not be an exaggeration to say that big data has transformed many aspects of how we approach problems in information organization and retrieval. In this context, my recent work focuses on two questions:  

How do we build effective and efficient information access systems that help users make sense of massive quantities of data?       How do we build scalable infrastructure to support these applications?    There is a tension between effective techniques that deliver high-quality results and efficient techniques that are fast and responsive. In this talk, I will discuss a number of case studies drawn from my academic research and industry experiences, and show how we are able to achieve a good balance between effectiveness and efficiency. Underscoring these applications is the importance of having the right infrastructure, both computational and human, to tackle big data challenges. I'll conclude with a discussion of the role that Information Schools should play within this broader intellectual space.

Speaker: Jimmy Lin, Univ. of Maryland