Refinement and calibration mechanism for improving classification of information assets

摘要

Techniques are described for refining the manual classification of assets classified or categorized using the terms of a business glossary. A semantic refinement mechanism is used to refine the manual classification of such assets, as well as subsequently evaluate the refined asset classifications. Further, the refined asset classifications may be used as a training set for a machine learning classifier. That is, should the classification of an asset contributing to a refinement change, the refinement based on that classification may be undone, at least in some cases.

主权项

1. A computer-readable storage medium storing executable instructions for configuring a computing appliance, which, when executed, performs an operation for refining asset classifications, the operation comprising:
receiving a plurality of assets, each asset having a classification of a term, wherein each term is selected from a business glossary which provides a hierarchy of controlled vocabulary of terms used within an organization and wherein each asset is characterized using a set of attributes selected from a domain ontology; and upon determining a first term assigned to a first one of the assets satisfies a set of refinement criteria, refining the classification of the first asset by assigning the first asset a second term from the business glossary, wherein the second term is more precise in the business glossary than the first term and wherein the refinement criteria includes:
determining that the term of a second one of the assets comprises a descendent of the classification of the first asset, anddetermining that each attribute of the first asset is at a lower level in the domain ontology than a corresponding attribute in the second asset.