Patent Document ID: 7529737
Application ID: 11129388

Base Claim:
1. A process performed by a processor for retrieving information organized in documents containing information in the form of text, meta-data, citation information and potentially other types of information comprising the steps of: obtaining and labeling a selected set of documents; extracting and selecting features from each document in the selected set; representing the extracted and selected features; dividing the set of documents into a plurality of splits of documents, each split comprising first, second, and third subsets; constructing models using a parametric learning algorithm, the constructed models being capable of assigning a label to a document, the models being instantiated using the first subset of a first of the plurality of splits of documents, and parameters associated with the model being chosen by validating the model against the second subset of the first of the plurality of splits; repeating the constructing, instantiating, and validating steps for each of the second and subsequent splits in the plurality of splits; testing the validated models by applying them to the third subset of a respective split; and selecting a best validated model, wherein the best validated model is configured to assign labels to documents exclusive of the selected set of documents.

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Claim 7:
7. A process according to claim 1 , further comprising using feature selection methods and symbolic learning to create explanations and visualizations of how the models label documents.