Stanford CS224W: Machine Learning with Graphs - Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.3 - The Small World Model

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/2ZIXpn5 Jure Leskovec Computer Science, PhD We introduce the small-world graphs (Watts–Strogatz graphs, W-S graphs). Even though the E-R graphs can fit the average path length of real-world graphs, its clustering coefficient is much smaller than real-world graphs. The small-world model is proposed to generative realistic graphs with both low diameter and high clustering coefficient. Specifically, W-S graphs are generative by randomly rewring edges from regular lattic graphs. To follow along with the course schedule and syllabus, visit: http://web.stanford.edu/class/cs224w/ #machinelearning #machinelearningcourse