IP Library Granted Patent US 8,489,617
Granted Patent B2
US 8,489,617 · App. 13/489,236 · Granted Jul 16, 2013

Automated detection of null field values and effectively null field values

Inventor: David Alan Bayliss (Delray Beach, FL)
Assignee: LexisNexis Risk Solutions FL Inc.
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Quick Facts
Patent No.
US 8,489,617
App. No.
13/489,236
Granted
Jul 16, 2013
Kind
B2
Abstract

Disclosed are systems for, and methods of, automatically detecting and treating field values of a particular field as null field values in records of a database. The system and method provide automatic treatment of these field values as null field values by calculating a critical frequency for the field. Based on the critical frequency of the field, the system and method treats field values that occur more than the critical frequency of the field as null field values and treats field values that occur less than the critical frequency as non-null field values.

Claims (31)

1. A computer implemented method of detecting and treating one or more field values as null field values in records of an electronic database, the computer implemented method comprising:

selecting a field of the records;

determining, using a programmed computer, a frequency for each field value of the field, the frequency comprising an amount of the records in which the field value of the field appears;

calculating, using a programmed computer, a critical frequency for the field based on an ordered histogram of the frequency of each field value of the field, the critical frequency comprising a frequency at which a first point of a derivative of the ordered histogram decreases below a threshold; and

treating, using a programmed computer, each field value of the field with a_frequency that is greater than the critical frequency of the field as a null field value and each field value of the field with a frequency that is less than the critical frequency of the field as a non-null field value.

2. The computer implemented method of claim 1 , wherein the calculating comprises ordering the frequencies of the field values of the field according to frequency along a horizontal axis of a histogram of the one or more field values of the field.

3. The computer implemented method of claim 2 , wherein the calculating further comprises calculating a difference between adjacent frequencies in the histogram.

4. The computer implemented method of claim 1 , wherein the calculating comprises calculating f(x)=g(x)−g(x+1), wherein f is a function of the frequency differences based on a function g that is defined by the frequency of each field value of the field.

5. The computer implemented method of claim 4 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function changes from a first sign to a second sign.

6. The computer implemented method of claim 4 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function changes from a positive sign to a negative sign.

7. The computer implemented method of claim 4 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function changes from a negative sign to a positive sign.

8. The computer implemented method of claim 4 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function equals zero.

9. The computer implemented method of claim 4 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function decreases below a threshold.

10. The computer implemented method of claim 1 , wherein the treating further comprises treating each field value of the field with a frequency that is equal to the critical frequency of the field as a null field value.

11. The computer implemented method of claim 1 , further comprising replacing one or more field values treated as null field values with a canonical null field value.

12. A computer implemented system of detecting and treating one or more field values as null field values in records of an electronic database, the computer implemented system comprising:

one or more computing apparatuses collectively configured to:

select a field of the records;

determine a frequency for each field value of the field, the frequency comprising an amount of the records in which the field value of the field appears;

calculate a critical frequency for the field based on an ordered histogram of the frequency of each field value of the field, the critical frequency comprising a frequency at which a first point of a derivative of the ordered histogram decreases below a threshold; and

treat each field value of the field with a frequency that is greater than the critical frequency of the field as a null field value and each field value of the field with a frequency that is less than the critical frequency of the field as a non-null field value.

13. The computer implemented system of claim 12 , wherein the third computing apparatus is configured to calculate by ordering the frequencies of the field values of the field according to frequency along a horizontal axis of a histogram of the one or more field values of the field.

14. The computer implemented system of claim 13 , wherein the third computing apparatus is further configured to calculate by calculating a difference between adjacent frequencies in the histogram.

15. The computer implemented system of claim 12 , wherein the third computing apparatus is configured to calculate by calculating f(x)=g(x)−g(x+1), wherein f is a function of the frequency differences based on a function g that is defined by the frequency of each field value of the field.

16. The computer implemented system of claim 15 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function changes from a first sign to a second sign.

17. The computer implemented system of claim 15 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function changes from a positive sign to a negative sign.

18. The computer implemented system of claim 15 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function changes from a negative sign to a positive sign.

19. The computer implemented system of claim 15 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function equals zero.

20. The computer implemented system of claim 15 , wherein the critical frequency of the field is determined by determining the first point at which a derivative of the f function decreases below a threshold.

21. The computer implemented system of claim 12 , wherein the fourth computing apparatus is further configured to treat each field value of the field with a frequency that is equal to the critical frequency of the field as a null field value.

22. The computer implemented system of claim 12 , further comprising a fifth computing apparatus configured to replace one or more field values treated as null field values with a canonical null field value.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 15, 2012
From: LEXISNEXIS RISK & INFORMATION ANALYTICS GROUP INC.
To: LEXISNEXIS RISK SOLUTIONS FL INC.
Reel/Frame 029126/0220 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 10, 2012
From: BAYLISS, DAVID
To: LEXISNEXIS RISK & INFORMATION ANALYTICS GROUP INC.
Reel/Frame 029105/0951 →
Continuity (4)
Continuation 12429361 · Apr 24, 2009
Provisional Application 61047570 · Apr 24, 2008
Provisional Application 61053202 · May 14, 2008
Related Publication 20120290585A1 · Nov 15, 2012