Adaptable systems and methods for processing enterprise data
First Claim
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.
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Abstract
A system, or platform, for processing enterprise data is configured to adapt to different domains and analyze data from various data sources and provide enriched results. The platform includes a data extraction and consumption module to translate domain specific data into defined abstractions, breaking it down for consumption by a feature extraction engine. A core engine, which includes a number of machine learning modules, such as a feature extraction engine, analyzes the data stream and produces data fed back to the clients via various interfaces. A learning engine incrementally and dynamically updates the training data for the machine learning by consuming and processing validation or feedback data. The platform includes a data viewer and a services layer that exposes the enriched data results. Integrated domain modeling allows the system to adapt and scale to different domains to support a wide range of enterprises.
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Citations
11 Claims
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1. A method, comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method comprising:
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identifying, by a natural language processor, that a computer-readable enterprise data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the natural language processor; associating, by the natural language processor, a meaning with the enterprise data based on the terms of the natural human language represented by the enterprise data that match the one or more taxonomy terms; generating, by the natural language processor, metadata that represents the meaning associated with the enterprise data; providing the metadata to a data processing machine for generating content based at least in part on the metadata; and wherein said method comprises sending said enterprise data and/or said metadata 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. - View Dependent Claims (9)
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10. A computing device comprising a processor and a computer-readable medium storing program instructions, that when executed by the processor, cause the computing device to perform a set of functions comprising:
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identifying that a computer-readable vehicle enterprise data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor; associating, by the processor, a meaning with the enterprise data based on the terms of the natural human language represented by the enterprise data that match the one or more taxonomy terms; generating, by the processor, metadata that represents the meaning associated with the enterprise data; providing the metadata to a data processing machine for generating content based at least in part on the metadata; and wherein said functions comprise sending said enterprise data and/or said metadata 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. - View Dependent Claims (11)
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Specification