Machine Learning/Kaggle Social Network Contest/lit review
This page contains links to relevant articles and summaries of the papers.
Supervised Random Walks
- title: "Supervised Random Walks: Predicting and Recommending Links in Social Networks"
- authors: Lars Backstrom and Jure Leskovec
- develop an algorithm based on Supervised Random Walks
- uses network structure info combined with node and edge level attributes to guide the walk
- learn a function to weight edges s.t. random walker more likely to visit nodes to which new links will be created (equivalent to missing nodes for our application)
- they develop a good training algorithm.
- test it on a facebook network and on co-author network
- compare to decision trees, logistic regression and unsupervised techniques.