System and Method for Generation of a Heuristic

1 . A computer implemented method of generating a heuristic that is capable of identifying data patterns, comprising:

extracting a data set from multiple input sources;

creating a set of unique elements used across the data set;

organizing the data set into a geometric structure;

grouping portions of the data in the geometric structure into a plurality of sub geometric structures;

determining base attributes for each sub geometric structure using the set of unique elements;

identifying trends in the base attributes among the sub geometric structures; and

outputting the heuristic as a combination of the base attributes and the trends.

2 . The computer implemented method of claim 1 , further comprising:

assigning a magnitude value to each element in the set of unique elements.

3 . The computer implemented method of claim 2 , wherein one of the base attributes determined is a presence attribute.

4 . The computer implemented method of claim 2 , wherein one of the base attributes determined is a magnitude attribute.

5 . The computer implemented method of claim 2 , wherein one of the base attributes determined is a position attribute.

6 . The computer implemented method of claim 2 , wherein outputs of all base attributes are normalized amongst each other.

7 . The computer implemented method of claim 2 , wherein the trends are identified by using a linear progression function.

8 . The computer implemented method of claim 2 , wherein the geometric structure is a two dimensional grid.

9 . The computer implemented method of claim 2 , wherein the heuristic is used in a pattern recognizer to create a core cognitive fingerprint.

10 . The computer implemented method of claim 2 , further comprising:

generating a heuristic definition including references to the sub geometric structures.

11 . A computer system, comprising:

a processor; and

memory coupled to the processor and storing instructions that, when executed by the processor, cause the computer system to:

extract a data set from multiple input sources;

create a set of unique elements used across the data set;

organize the data set into a geometric structure;

group portions of the data in the geometric structure into a plurality of sub geometric structures;

determine base attributes for each sub geometric structure using the set of unique elements;

identify trends in the base attributes among the sub geometric structures; and

output the heuristic as a combination of the base attributes and the trends.

12 . The computer system of claim 11 , wherein the memory further stores instructions to cause the processor to assign a magnitude value to each element in the set of unique elements.

13 . The computer system of claim 12 , wherein one of the base attributes determined is a presence attribute.

14 . The computer system of claim 12 , wherein one of the base attributes determined is a magnitude attribute.

15 . The computer system of claim 12 , wherein one of the base attributes determined is a position attribute.

16 . The computer system of claim 12 , wherein the memory further stores instructions to cause the processor to normalize outputs of all base attributes amongst each other.

17 . The computer system of claim 12 , wherein the memory further stores instructions to cause the processor to identify the trends using a linear progression function.

18 . The computer system of claim 12 , wherein the geometric structure is a two dimensional grid.

19 . The computer system of claim 12 , wherein the memory further stores instructions to cause the processor to use a pattern recognizer to create a core cognitive fingerprint from the heuristic.

20 . The computer system of claim 12 , wherein the memory further stores instructions to cause the processor to generate a heuristic definition including references to the sub geometric structures.