13. A system according to claim 11 in step A, further comprising a server wherein the storage device is located on the server.
11. A system using a model to filter documents according to quality comprising: A) a storage device; B) at least one processor to implement the following steps: C) obtaining from the storage device a first set of documents labeled according to content quality; D) extracting and representing features from the first set of documents; E) modifying the extracted represented features; F) constructing models for labeling documents based on content quality using pattern recognitional algorithms stored in the storage device consisting of the following steps; 1) dividing the first set of documents into N subsets such that the union of all the subsets is the first set of documents; 2) choosing at least one pattern recognition algorithm; a) instantiating a set of parameters for the pattern recognition algorithm; i) processing each of the N subsets comprising the following steps; a′) defining a first subset and defining a second subset mutually exclusive of the first subset; b′) training the pattern recognition algorithm to build a model using the first subset and the parameter set; c′) applying the model to the second subset of documents to obtain labels and scores for each document; d′) evaluating the labels and scores; e′) storing the evaluation measure, set of parameters, and current pattern recognition algorithm; and b) repeating step 2 a ) until all appropriate sets of parameters for the pattern recognition algorithm have been applied; and 3) repeating step 2) until all pattern recognition algorithms have been applied; 4) aggregating the evaluation measures for the N subsets, the pattern recognition algorithms with the set of parameters; 5) selecting the parameter set and pattern recognition algorithm with an aggregate evaluation measure that meets a selection criteria; 6) applying the parameter set and the pattern recognition algorithm identified from step 5) to the first set of documents to build a final model; and G) obtaining a second set of non-labeled documents related to the first set of documents; H) using the final model to label and score the second set of documents according to content quality; and I) displaying the label and/or score of at least one of the previously unlabeled documents.