1. A method for large-scale behavioral targeting, the method comprising: receiving training data that is processed raw data of user behavior; generating selected features by performing feature selection on the training data; generating feature vectors from the selected features; initializing weights of a behavioral targeting model by scanning the feature vectors once; and updating the weights of the behavioral targeting model by scanning iteratively the feature vectors using a multiplicative recurrence.