PageRank Algorithm

Overview

PageRank computes the importance of web pages by modeling a random surfer who follows links with probability d (damping factor) and jumps to a random page with probability 1-d. Converges in O(k * E) where k is iterations and E is number of edges.

When to Use

Trigger conditions:

• Computing page importance from link graph structure
• Building link-based authority scoring systems
• Analyzing citation networks or any directed graph importance

When NOT to use:

• When you only need keyword relevance (use TF-IDF instead)
• When the graph is undirected or unweighted (consider centrality measures)

Algorithm