1. A computer implemented method comprising: analyzing a plurality of attributes of a sample of online documents using a boosted decision tree and generating a machine learning model therefrom; using the machine learning model to predict a click through rate (CTR) of an additional online document based on the analyzing; outputting the predicted CTR to a display device, storage medium or network, wherein the plurality of attributes include a CTR of other documents having titles that are the same as or similar to a title of the additional online document; determining similarity of any two documents by cardinality of a difference set that includes non-overlapping terms included in the title of one of the two documents but not included in the title of the other of the two documents; using the machine learning model to predict respective CTR of a plurality of additional online documents based on the analyzing; and ranking the plurality of additional online documents by using the respective predicted CTR of each of the plurality of additional online documents as an input factor.