Abstract
The pages and hyperlinks of the World-Wide Web may be viewed as nodes and edges in a directed graph. This graph has about a billion nodes today, several billion links, and appears to grow exponentially with time. There are many reasons - mathematical, sociological, and commercial - for studying the evolution of this graph. We first review a set of algorithms that operate on the Web graph, addressing problems from Web search, automatic community discovery, and classification. We then recall a number of measurements and properties of the Web graph. Noting that traditional random graph models do not explain these observations, we propose a new family of random graph models.