Teaching or conference talk
Temporal Networks, Where Page Rank meets Lord of the Rings - Computerphile
Temporal networks add time to the picture of how things connect, and Dr Richard Clegg uses PageRank and Lord of the Rings to show why.
Topic
PageRank
7 videos.
PageRank is the scoring method Google's founders described in the late 1990s. It gives each page a number based on the pages that link to it, with links from well-scored pages counting for more. Google has changed a great deal since, so these lectures explain the original idea rather than today's rankings.
All the videos here are teaching material, mostly from universities. Readers new to it should begin with How Google's PageRank Algorithm Works, a five-minute explainer of the random surfer and the damping factor. Google's PageRank Algorithm Explained with Examples from Georgia Tech works through small numbers, and expects some maths.
The Stanford, data mining and linear algebra lectures go deeper and need comfort with matrices. Temporal Networks is closer to computer science than to search practice.
Teaching or conference talk
Data Mining (Spring 2023) - PageRank Part II
Basic PageRank gets stuck on spider traps and dead ends. This data mining lecture shows how teleportation gets round both, then builds up to the final algorithm.
Older: check current guidanceTeaching or conference talk
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.1 - PageRank
PageRank, random walks and matrix factorisation are worked through in a Stanford lecture from Jure Leskovec, which treats graphs as matrices and builds towards node embeddings. Lecture 4.1 of the CS224W course.
Older: check current guidanceTeaching or conference talk
IR Course Lecture 16: Popularity - Page Rank and HITS
PageRank and HITS are two classic ways to score how important a web page is, and this lecture works through both, including the random surfer idea and Markov chains.
Older: check current guidanceTeaching or conference talk
How Google's PageRank Algorithm Works
What makes a web page important to PageRank? This short video explains the random surfer idea and what the damping factor is for.
Older: check current guidanceTeaching or conference talk
Google’s PageRank Algorithm Explained with Examples | Georgia Tech CSE6242
A Georgia Tech lecture works through PageRank with a small numbers example, first without teleportation and then with it, before moving to huge matrices and the personalised version.
Older: check current guidanceTeaching or conference talk
M4ML - Linear Algebra - 5.7 Introduction to PageRank
An Imperial College London lecturer introduces PageRank through linear algebra, in week 5 of a Mathematics for Machine Learning course on Coursera.
Older: check current guidance
