1. A computer system for classifying a web page, comprising: one or more processors to execute instructions; a classification engine for determining a quality of the web page using local features of a seed set of web pages and global web graph information about the seed set of web pages, wherein: each web page of the seed set of web pages is a web page of a known quality, the local features of the seed set of web pages comprises text, clicking, domain, or time stamp information concerning the seed set of web pages, and the global web graph information about the seed set of web pages comprises hyperlink or co-citation relationships among the seed set of web pages; a binary classifier coupled to the classification engine for performing binary classification to provide a binary score for the web page; and a collective inference engine coupled to the binary classifier for performing collective inference by applying collective inference for binary classification using the local features of the seed set of web pages and the global web graph information about the seed set of web pages, comprising finding a minimum value of a regularized convex dual of a logistic regression loss function for a node of a graph.