LINK SPAM DETECTION USING SMOOTH CLASSIFICATION FUNCTION

摘要

A collection of web pages is considered as a directed graph in which the pages themselves are nodes and the hyperlinks between the pages are directed edges in the graph. A trusted entity identifies training examples for spam pages and normal pages. A random walk is conducted through the directed graph that includes the collection of web pages and the stationary probabilities, and transitional probabilities, among the nodes in the directed graph are obtained. A classifier training component estimates a classification function that changes slowly on densely connected subgraphs within the directed graph. The classification function assigns a value to each of the nodes in the directed graph and identifies them as spam or normal pages based upon whether the value meets a given function threshold value.