Instructor: Yizhou Sun
Lecture times: M/W 10am-11:50am
Lecture location: PAB Room 1749
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. Students are expected to read and present research papers, and work on a research project related to this topic.
1. Introduction and Basics of Information/Social
2. Clustering / Community Detection
3. Classification / Label Propagation
4. Similarity Search
5. Network Embedding
6. K-Core Subgraph Decomposition and Its Applications
7. Diffusion and Influence Maximization
*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/ucla/winter2017/comsci2492/home
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