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Course Details

Fall 2017-2018
* COS 496   na, npdf

Special Topics in Computer Science - Complex Networks - Analysis and Applications

Andrea S. LaPaugh

Complex networks arise through the analysis of complex systems in many areas of study. Well known areas include social network analysis (e.g. Facebook friends), text citation analysis (e.g. Wikipedia) and biological network analysis (e.g. protein-protein interactions). Complex networks can be distinguished from random networks and from regular networks, such as grids, which are often created by design for applications such as interconnecting computers. This course examines methods of analysis of complex networks and how this analysis can be applied to enhance our understanding of real-world systems.

Sample reading list:
Mark Newman, Networks: An Introduction
Albert-Laszlo Barabasi, Marton Posfai,, Network Science

Reading/Writing assignments:
Approximately 6 homework assignments. Some may involve programming. Reading assignments will be textbook chapters or sections and conference/journal papers.

Mid Term Exam - 15%
Other Exam - 15%
Design Project - 40%
Class/Precept Participation - 5%
Problem set(s) - 25%

Other Requirements:
Statistical, design or other software use required

Prerequisites and Restrictions:
COS 226 and some experience with linear algebra..

Other information:
Books under "Sample Reading" are available online through the Princeton University library.


Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
20555 L01 01:30:00 pm - 02:50:00 pm M W   Computer Science Building   301   Enrolled:3 Limit:20