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.
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. 29. A process according to claim 11 wherein the pattern recognition algorithm loop at steps (F)(2) and steps (F)(3), the parameter loop at steps (F)(2)(a) and steps (F)(2)(b), and the subset loop at steps (F)(1) may be interchanged to produce an evaluation measure for the outer loop.