SYSTEMS AND METHODS FOR GENERALIZED STRUCTURED DATA DISCOVERY UTILIZING CONTEXTUAL METADATA DISAMBIGUATION VIA MACHINE LEARNING TECHNIQUES

摘要

A method for generalized structured data discovery may include (1) receiving physical application metadata from data sources for an attribute, a database object, or a database; (2) receiving reference data comprising a plurality of tokens and their associated abbreviations/acronyms; (3) parsing the physical application metadata into a application tokens comprising known and unknown application tokens; (4) identifying unknown application tokens by comparing the parsed application tokens to a corpus; (5) performing probabilistic parsing on the unknown application tokens using the reference data; (6) performing bi-directional encoding to expand the polysemous tokens to relevant expressions using the reference data; (7) applying language tokens to the relevant expressions in the expanded polysemous tokens to disambiguate the relevant expressions; and (8) outputting a mapping of the physical application metadata to enhanced physical application metadata, wherein the enhanced physical application metadata comprises an expression for the physical application metadata in a supported language.