Mining Big Network Data: Challenges and Algorithms
Speaker: Xiang Zhang, Penn State University
Abstract: Networks (or graphs) provide a natural data model for numerous applications ranging from social, web, scientific data to biological and medical data. The real-world networks are usually very large, noisy and collected in different domains. Motivated by these properties of the data, in this talk, I will focus on three important algorithmic issues in analyzing large network data, i.e., scalability, robustness and integrativeness. I will use query and clustering, which are of fundamental importance to many advanced tasks, as examples to illustrate how we address these issues. In particular, I will introduce a local search algorithm for proximity query, a node weighting method for local clustering, and the network of networks model for integrating multiple networks.
Room Reservation Information
Room Number: 114 McAllister
Time: 2:30pm - 3:30pm