A map intuition system and method that involves machine learning techniques to analyze data sets and identify mappings and transformation rules as well as machine-human interactions to leverage human intuition and intelligence to rapidly complete a map.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for defining a data transformation, the method comprising: a processor receiving a plurality of inputs for transformation, said plurality of inputs having a first format; said processor transforming said plurality of inputs into a plurality of outputs, said plurality of outputs having another format; said processor capturing at least one of said plurality of inputs prior to said transformation and said processor capturing at least one of said plurality of outputs subsequent to said transformation; said processor providing said captured at least one input and at least one output to an inference engine; said inference engine converting said captured at least one input and at least one output into candidate transformation information; said processor receiving input through a user interface identifying a different transformation for transforming said plurality of inputs into said plurality of outputs, said identification being based at least in part on said candidate transformation information. 2. The method according to claim 1, wherein said inference engine ranks at least a portion of the candidate transformation information from lower to higher and visually highlights higher ranking candidate transformation information. 3. The method according to claim 1, wherein each input and each output includes at least one file. 4. The method according to claim 3, wherein each at least one file comprises a plurality of data fields, wherein each data field has a field value and a field type. 5. The method according to claim 4, wherein said method is iterative. 6. The method according to claim 1, wherein said candidate transformation information includes a list of candidates. 7. The method according to claim 6, wherein said list of candidates includes a plurality of lists of candidates. 8. The method according to claim 6 wherein said identifying a different transformation includes: specifying a selection criteria for said candidates; selecting a candidate from said list based at least in part on said selection criteria; comparing an output from said different method of transforming said plurality of inputs into said plurality of outputs to a corresponding captured output sample to produce a relative difference; determining if the relative difference is within a predetermined criteria; and, when the relative difference is not within the predetermined criteria, modifying the different method of transforming and returning to the comparing step. 9. The method according to claim 4, further including said inference engine: identifying value spaces relevant to the field type and field value of said inputs to the transformation and outputs from the different transformation; comparing field values of said inputs to the transformation with field values of the outputs from the different transformation to provide a numerical degree of correspondence for each; and visually highlighting candidates with a numerical degree of correspondence greater than a threshold. 10. An apparatus for defining a data transformation from a plurality of inputs having an input format to a plurality of corresponding outputs having an output format, the apparatus comprising: a non-transitory machine-readable medium; and a plurality of instructions in the machine-readable medium which, when executed by a processing machine, enable the processing machine to perform operations comprising: transforming said plurality of inputs into said plurality of outputs; capturing at least one of said plurality of inputs prior to said transforming and capturing at least one of said plurality of outputs subsequent to said transforming; providing an inference engine configured to receive said at least one captured input and captured output and convert said at least one captured input and captured output into candidate transformation information; and providing a user interface having features that enable review of said candidate transformation information, and identification of a different transformation of said plurality of inputs to said plurality of outputs based at least in part on said review of said candidate transformation information. 11. The apparatus according to claim 10, further comprising: said user interface providing a search function to permit the user to search at least one previous transformation of said input data. 12. The apparatus according to claim 10, further comprising performing a plurality of transformations using said different transformation. 13. The apparatus according to claim 10, further comprising said user interface displaying a library of common functions for providing a user with an ability to search for common data transformations. 14. An inference engine method for ranking and highlighting candidates in a map intuition system, comprising: receiving at a processor a source data set having data with input field values, each source data set having a source data set definition describing the data in the source data set; receiving at the processor a target data set derived at least in part from said source data set, having data with output field values Vo, each target data set having a target data set definition describing the data in the target data set; and said processor comparing each input field value with each output field value, identifying a degree of correspondence between each pair of values, ranking the source and output field values into clusters, and merging the rankings from a data level to a data definition level. 15. The inference engine method of claim 14, wherein the step of comparing each input field value with each output field value comprises: determining whether the output field value is equivalent to the input field value; determining whether the output field value is a subset of the input field value; determining whether the output field value is able to be partially constructed from the input field value; and determining how much of the output field value can be constructed.