1. A method, comprising: building a domain model for processing data specific to an enterprise; applying historical enterprise data and contextual data to the model to build entity relations annotated with contextual data; wherein said method comprises sending said enterprise data and/or said contextual data to one or more of an importer module, an extraction module, a learning module, a classification module, a feedback module, a scoring module, and/or an export module; extracting features of interest from the annotated entity relations defined in the domain model; classifying and clustering the features to develop enterprise-specific metadata; storing the metadata for use by the domain model; and receiving and applying expert feedback to improve the model.
1. A method, comprising: building a domain model for processing data specific to an enterprise; applying historical enterprise data and contextual data to the model to build entity relations annotated with contextual data; wherein said method comprises sending said enterprise data and/or said contextual data to one or more of an importer module, an extraction module, a learning module, a classification module, a feedback module, a scoring module, and/or an export module; extracting features of interest from the annotated entity relations defined in the domain model; classifying and clustering the features to develop enterprise-specific metadata; storing the metadata for use by the domain model; and receiving and applying expert feedback to improve the model. 4. The method of claim 1 , wherein the enterprise data comprises unstructured data, said method further comprising: associating and adapting a domain-specific meaning to the unstructured data using the extracted features; and generating metadata associated with the enterprise data based on the domain model.