Making Big Data More Digestible
The average broadband and cellular users now spend more time in online social networks than in face-to-face interactions with people other than their immediate families.
Social networks tend to create tight-knit groups characterized by a high density of connections, and these connections are often good predictors of users’ tastes and future connections. But, finding these communities is both computationally and statistically challenging.
The Wireless Networking and Communications Group at The University of Texas at Austin’s Cockrell School of Engineering developed a new graph-clustering technique that helps with community detection, user profiling, link prediction and collaborative filtering. Learn how researchers were able to both reach globally optimal solutions with better statistical properties and provide an algorithm that easily scales.
Presented by The University of Texas
Presenters
Alex Dimakis
Asst Prof
The University of Texas at Austin
Alex Dimakis is an Assistant Professor in the Electrical & Computer Engineering department at The University of Texas at Austin.
Prof. Dimakis received his Ph.D. in 2008 and M.S. degree in 2005 in...
Show the restConstantine Caramanis
Assoc Prof
The University of Texas at Austin
Joydeep Ghosh
Professor
The University of Texas at Austin
Joydeep Ghosh is currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin. He joined the UT-Austin faculty in 1988 after being...
Show the restSriram Vishwanath
Professor
The University of Texas at Austin
Dr. Sriram Vishwanath is a Professor in the Electrical and Computer Engineering department at The University of Texas at Austin. Dr. Vishwanath received his B.Tech. from the Indian Institute of Tec...
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