Random Walker Model: PageRank

This lecture introduces the Random Walker Model and its application in the PageRank algorithm. It covers the concept of relevance in web pages, the link matrix, and the computation of PageRank using a random walker. The lecture explains the importance of PageRank in web search and its practical computation, including the iterative computation process. It also delves into the Hyperlink-Induced Topic Search (HITS) algorithm, which focuses on finding hub and authoritative pages in response to a query. The lecture concludes with a discussion on the Louvain Modularity and Girvan-Newman algorithms for community detection in networks.