Interpolation data template to normalize analytic runs

• US 8,862,638 B2
• Filed: 02/28/2011
• Issued: 10/14/2014
• Est. Priority Date: 02/28/2011
• Status: Active Grant

• Current Assignee: Red Hat, Inc. (International Business Machines Corporation)
• Original Assignee: Red Hat, Inc. (International Business Machines Corporation)
• Inventors: Williamson, Eric
• Primary Examiner(s): Vy, Hung T
• Application Number:
  US13/037,332
• Publication Number:
  US 20120221503A1
• Time in Patent Office: 1,324 Days
• Field of Search: 707802-804, 707/807, 707/809, 707/810, 707/791, 706/13, 706/47
• US Class Current: 707/810
• CPC Class Codes: G06F 17/17 Function evaluation by approximation methods, e.g. inter- or extrapolation, smoothing, least mean square method G06F17/18 takes precedence ; interpolation for numerical control G05B19/18

Abstract

Embodiments relate to systems and methods for generating an interpolation data template to normalize analytic runs. A database can store sets of operational data, such as financial, medical, climate or other information. For given data, a portion of the input data can be known or predetermined, while for a second portion can be unknown and subject to interpolation. The interpolation engine can generate a conformal interpolation function and interpolated input sets that map to a set of target output data. In aspects, an interpolation history database can stores results of a variety of interpolation studies or results, from which a set of interpolation templates can be derived. The templates can reflect trends or patterns discovered or displayed in the historical interpolation results, for instance, to produce expected values for different variables based on averages, thresholds, or other criteria applied to the historical results. New interpolation studies can apply data-selected templates chosen to match their operative data, and produce normalized data as the interpolation results themselves, or provide a starting point for further interpolation processing.

Claims

1. A method comprising:

accessing a set of historical interpolation results representing sets of interpolated input data derived from historical sets of operative data;

applying, by a processor, a set of extraction rules to the set of historical interpolation results to generate a set of interpolation templates;

selecting at least one of the set of interpolation templates corresponding to a current set of operative data comprising at least a set of predetermined input data and a set of target output data;

applying the at least one of the set of interpolation templates to the current set of operative data to generate a template-derived set of interpolated input data; and

initiating further interpolation operations based on the template-derived set of interpolated input data.

2. The method of claim 1, wherein the further interpolation operations comprise accepting the template-derived set of interpolated input data as conformally mapping the current set of operative data to the set of target output data.

3. The method of claim 1, wherein the further interpolation operations comprise performing interpolation operations on the template-derived set of interpolated input data to generate a produced set of interpolated input data conformal mapping of the current set of operative data to the set of target output data.

4. The method of claim 1, wherein the set of extraction rules comprises a set of data categories for the current set of operative data.

5. The method of claim 4, wherein the set of data categories comprises at least one of a technical data category, a financial data category, a medical data category, a climate data category, or an Internet data category.

6. The method of claim 4, wherein the set of extraction rules comprises a comparison of at least one attribute of the current set of operative data to at least one attribute of the set of interpolation templates.

7. The method of claim 6, wherein the at least one of the set of interpolation templates is selected based on a matching of the at least one attribute of the current set of operative data to the at least one attribute of recorded the set of interpolation templates.

8. The method of claim 7, wherein the matching comprises determining that a number of the at least one attribute of the current set of operative data matches at least a threshold number of the at least one attribute of the set of interpolation templates.

9. The method of claim 7, wherein the matching comprises determining that a dimension of the current set of operative data matches a dimension of the at least one of the set of interpolation templates.

10. The method of claim 7, wherein the matching comprises determining a match between a user identification associated with the current set of operative data and a user identification associated with the at least one of the set of interpolation templates.

11. The method of claim 7, wherein the at least one of the set of interpolation templates comprises an average of values for sets of interpolated input data in the set of historical interpolation results associated with attributes matched by the matching.

12. A system comprising:

an interface to a database to store a set of target output data and a set of predetermined input data; and

a processor, to communicate with the database via the interface, the processor to;

access a set of historical interpolation results representing sets of interpolated input data derived from historical sets of operative data,

apply a set of extraction rules to the set of historical interpolation results to generate a set of interpolation templates,

select at least one of the set of interpolation templates corresponding to a current set of operative data comprising at least a set of predetermined input data and a set of target output data,

apply the at least one of the set of interpolation templates to the current set of operative data to generate a template-derived set of interpolated input data, and

initiate further interpolation operations based on the template-derived set of interpolated input data.

13. The system of claim 12, wherein the further interpolation operations comprise accepting the template-derived set of interpolated input data as a set of interpolated input data conformally mapping the set of combined input data to the set of target output data.

14. The system of claim 12, wherein the further interpolation operations comprise performing interpolation operations on the template-derived set of interpolated input data as an initial data set to generate a set of interpolated input data producing a conformal mapping of the set of combined input data to the set of target output data.

15. The system of claim 12, wherein the set of extraction rules comprises a set of data categories for the current set of operative data.

16. The system of claim 15, wherein the set of data categories comprises at least one of a technical data category, a financial data category, a medical data category, a climate data category, or an Internet data category.

17. The system of claim 15, wherein the set of extraction rules comprises a comparison of at least one attribute of the current set of operative data to at least one attribute of the set of interpolation templates.

18. The system of claim 17, wherein the at least one of the set of interpolation templates is selected based on a matching of the at least one attribute of the current set of operative data to the at least one attribute of the set of interpolation templates.

19. The system of claim 18, wherein the matching comprises determining that a number of the at least one attribute of the current set of operative data matches at least a threshold number of the at least one attribute of the set of interpolation templates.

20. The system of claim 18, wherein the matching comprises determining that a dimension of the current set of operative data matches a dimension of the at least one of the set of interpolation templates.

21. The system of claim 18, wherein the matching comprises determining a match between a user identification associated with the current set of operative data and a user identification associated with the at least one of the set of interpolation templates.

22. The system of claim 18, wherein the at least one of the set of interpolation templates comprises an average of values for sets of interpolated input data in the set of historical interpolation results associated with one or more attributes matched by the matching.