CS 7280: Special Topics in Data (Mining Information/Social Networks)

Instructor: Yizhou Sun

Lecture times: Tuesdays 11:45am-1:25pm, Thursdays 2:50-4:30pm
Lecture location: Snell Library 115

About the Course

Information and social networks including World Wide Web, Facebook, Twitter, Weibo, Forum network, Citation network, Game network, Movie network, and Medical network now become a very important and ubiquitous data type. Which patterns can be defined on such data? What kind of prediction can be made? Which models and algorithms can be used to deal with networked data? How can we handle large-scale networked data? All these issues will be discussed in this course.

The goal of the course is to learn the most cutting-edge topics, models and algorithms in information and social network mining, and to solve real problems on real-world large-scale information/social network data using these techniques. The students are expected to read and present research papers, and work on a research project related to this topic.

Syllabus (Schedule)

1.      Basics of Information/Social Networks
2.      Ranking for infonet
3.      Clustering / community detection
4.      Matrix factorization
5.      Classification / label propagation / node or link profiling
6.      Probabilistic models for infonets
7.      Similarity search
8.      Diffusion / Influence maximization
9.      Recommendation
10.    Link / relationship prediction
11.    Trustworthy analysis
12.    Large graph computation



*Note: all the deadlines are 11:59PM (midnight) of the due dates.

 Q & A

This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza.

Tips: Answering other students' questions will increase your participation score.

Find our class page at: https://piazza.com/northeastern/spring2014/cs7280/home

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For more information, please refer to the Academic Integrity Web page.