Welcome to hands-on tutorial for link analysis. In this tutorial, we will study several techniques for link analysis in graphs. This tutorial consists of four sessions, and each session will handle the following topic:
- Session 1. Tutorial on PageRank - Part 1 (50 mins)
- Session 2. Tutorial on PageRank - Part 2 (50 mins)
- Session 3. Tutorial on Topic-specific PageRank (50 mins)
- Session 4. Tutorial on HITS (50 mins)
We recommend fully understanding link analysis (or ranking) models such as PageRank, Topic-specific PageRank (or Random Walk with Restart and Personalized PageRank with multiple seeds), and HITS before entering this tutorial since we will NOT explain the theoretical backgrounds on these techniques during the tutorial. We will mainly focus on how to implement the algorithms of those models and how to rank nodes in real-world graphs using the ranking models.
The main contributor of this material is as follows:
- Jinhong Jung (jinhongjung@snu.ac.kr)
- https://en.wikipedia.org/wiki/PageRank
- https://datalab.snu.ac.kr/~ukang/courses/18S-DM/
- Langville, A. N., & Meyer, C. D. (2011). Google's PageRank and beyond: The science of search engine rankings. Princeton University Press.