Mining Big Network Data: Challenges and Algorithms

Computational and Applied Mathematics Colloquium

Meeting Details

For more information about this meeting, contact Kendra Stauffer, Ludmil Zikatanov, Jinchao Xu, Wenrui Hao,

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

Date: 08/21/2017

Time: 2:30pm - 3:30pm