document: Behavioral classification on the click graph A bipartite query-URL graph , where an edge indicates that a document was clicked for a query , is a useful construct for finding groups of related queries and URLs . Here we use this behavior graph for classification . We choose a click graph sampled from two weeks of image search activity , and the task of `` adult '' filtering : identifying content in the graph that is inappropriate for minors . We show how to perform classification using random walks on this graph , and two methods for estimating classifier parameters .
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