Location & Time
TR 4.15 PM-5.30 PM116 EES Building
Instructor
Kamesh MadduriOffice hours:
TR 1.00 PM-2.30 PM (343E IST)
Appointment (cal)
This class provides students a hands-on introduction to scalable graph mining. Topics include graph modeling, centrality analysis, community detection, partitioning, visualization, compression, subgraph mining, and several other optimization problems. We will review current work and identify research challenges related to computational analysis of large graph data. We will implement most of the algorithms studied in class to analyze collaboration graphs constructed from the Internet Movie Database (IMDb) and the DBLP Computer Science bibliography database.