20. The method of claim 1 , wherein said step of forming a training set comprises updating the closest neighbors as new reference files appear in the database of reference files.
1. A method for automatic ranking of target files according to a predefined scheme, comprising the steps of: building a database of reference files already ranked according to the predefined scheme; for each target file: i) determining a neighborhood of the target file among the reference files in the database of reference files, and forming a training set comprising reference files of this neighborhood, versus which neighborhood as a whole the target file is to be assessed, wherein said step of forming a training set comprises extracting a feature vector of the target file and finding n closest neighbors of the feature vector of the target file among features vectors in the database of reference files, and wherein said finding n closest neighbors comprises using one of: i) Euclidean distance, ii) cosine distance and iii) Jensen-Shannon distribution similarity; ii) building a test set from features of the target file; iii) dynamically generating a learning model from the training set, the learning model defining a correlation between the reference files in the training set and a rank thereof according to the predefined scheme; and iv) applying the learning model to the test set; whereby a rank corresponding to the target file is predicted according to the predefined scheme.