1. A method of analyzing web pages, comprising: accessing a plurality of web pages; generating a plurality of different graphical representations of the web pages, each graphical representation having nodes that represent the web pages and links between the nodes, the nodes in each of the graphical representations representing a same set of the web pages as represented in other of the graphical representations, and the links in each graphical representation representing different relationships between the nodes in each graphical representation from the other graphical representations; generating a model that models a random walk through all of the different graphical representations; receiving training pages, wherein each of a plurality of training nodes, in the graphical representations, corresponding to a training page has a target function value indicative of a label for the corresponding training page, the label indicating the corresponding training page belongs to one of a plurality of different groups; generating a classifier based on the model, based on classifier function values of nodes in the graphical representations, and based on the target function values of the training pages; and grouping the web pages into groups with the classifier.
1. A method of analyzing web pages, comprising: accessing a plurality of web pages; generating a plurality of different graphical representations of the web pages, each graphical representation having nodes that represent the web pages and links between the nodes, the nodes in each of the graphical representations representing a same set of the web pages as represented in other of the graphical representations, and the links in each graphical representation representing different relationships between the nodes in each graphical representation from the other graphical representations; generating a model that models a random walk through all of the different graphical representations; receiving training pages, wherein each of a plurality of training nodes, in the graphical representations, corresponding to a training page has a target function value indicative of a label for the corresponding training page, the label indicating the corresponding training page belongs to one of a plurality of different groups; generating a classifier based on the model, based on classifier function values of nodes in the graphical representations, and based on the target function values of the training pages; and grouping the web pages into groups with the classifier. 11. The method of claim 1 wherein grouping the web pages into groups comprises: grouping the web pages into groups based on similarity of content.