Self-learning data lenses for conversion of information from a source form to a target form
First Claim
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1. A method for use in converting semantic information from a source form to a target form, comprising the steps of:
- providing a computer-based analysis tool for automatically executing a conversion analysis having at least one conversion logic that is independent of any particular conversion environment associated with semantic information to be converted, wherein said at least one conversion logic is operative for analyzing at least one structural element of said semantic information without regard to any particular conversion environment associated with the semantic data;
obtaining a first set of data reflecting a first conversion environment associated with first semantic information, wherein at least a portion of said first set of data is standardized;
identifying the portion of said first set of data that is standardized;
first operating said analysis tool on said standardized portion of said first set of data to automatically develop a first semantic metadata conversion model specific to said first conversion environment associated with said first semantic information utilizing said at least one conversion logic; and
second operating said analysis tool to automatically convert a second set of data belonging to said first conversion environment associated with said first semantic information from said source form to said target form by applying said first developed semantic metadata conversion model to said second set of data, wherein said second set of data has at least a portion of data that is unstandardized.
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Abstract
A semantic conversion system (1900) includes a self-learning tool (1902). The self-learning tool (1902) receives input files from legacy data systems (1904). The self-learning tool (1902) includes a conversion processor (1914) that can calculate probabilities associated with candidate conversion terms so as to select an appropriate conversion term. The self-learning tool (1902) provides a fully attributed and normalized data set (1908).
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9 Claims
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1. A method for use in converting semantic information from a source form to a target form, comprising the steps of:
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providing a computer-based analysis tool for automatically executing a conversion analysis having at least one conversion logic that is independent of any particular conversion environment associated with semantic information to be converted, wherein said at least one conversion logic is operative for analyzing at least one structural element of said semantic information without regard to any particular conversion environment associated with the semantic data; obtaining a first set of data reflecting a first conversion environment associated with first semantic information, wherein at least a portion of said first set of data is standardized; identifying the portion of said first set of data that is standardized; first operating said analysis tool on said standardized portion of said first set of data to automatically develop a first semantic metadata conversion model specific to said first conversion environment associated with said first semantic information utilizing said at least one conversion logic; and second operating said analysis tool to automatically convert a second set of data belonging to said first conversion environment associated with said first semantic information from said source form to said target form by applying said first developed semantic metadata conversion model to said second set of data, wherein said second set of data has at least a portion of data that is unstandardized. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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Specification