Today we’ll move on to two new questions about graphs: how do you find the most “influential” nodes in a directed graph (if an edge confers a small amount of influence from its tail to its head) AKA the Google Guide to How to Win at Search, and how do you cluster nodes in a graph (if an edge’s weight denotes similarity)?

• Here are today’s notes.
• Your assignment is posted and due Thu 6 Oct at 10PM on handin (under assn2). (Note the later due time!)
• For next time, please read Sections 4.1-4.2. (No pre-class quiz.)
• Just for fun: We’ll try a little in-class experiment. Here’s a form for our experimental results.
• Just for fun: Our algorithm isn’t Google’s, but it computes the same PageRank quantity.
• Just for fun: UBC CS’s most cited paper (last I checked!), by David Lowe, looks at how to find similar features between images using the SIFT algorithm.