Qualification of match results

Patent metadata

Field	Value
Publication number	US-9805072-B2
Application number	US-201414222445-A
Country	US
Kind code	B2
Filing date	Mar 21, 2014
Priority date	Mar 21, 2014
Publication date	Oct 31, 2017
Grant date	Oct 31, 2017

Abstract

Qualification of data matches can be improved relative to existing approaches by use of first, second, and third similarity criteria, which can be used to identify a set of near match record pairs, identify a set of actual match record pairs and to flag as near matches those record pairs of the set of near matches that were identified as actual matches, and to identify and flag one or more suspect matches.

First claim

What is claimed is:

1. A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
applying first similarity criteria to a set of record pairs to identify a set of near match record pairs, the applying comprising:
identifying a pair of records in the set of record pairs as a near match record pair when:
a similarity between the pair of records exceeds a minimum similarity threshold and when the pair of records is a name,
the pair of records contains an email address comprising a domain name that is the same in the pair of records,
the only difference between the pair of records is a numeric component,
the pair of records match when the pair of records is translated to a same script, and
adding, the near match record pair to the set of near match record pairs;

applying, after identifying the set of near match record pairs, second similarity criteria to the set of near match record pairs to identify a set of actual match record pairs, the second similarity criteria being more strict than the first similarity criteria;
flagging, as near matches, those record pairs of the set of near matches that were not identified as actual matches;
applying, after identifying the set of actual match record pairs, third similarity criteria to the set of actual match record pairs to identify and flag one or more suspect matches, the third similarity criteria being more strict than the second similarity criteria;
flagging, as a suspect match group, the set of actual match record pairs that contain the one or more suspect matches; and
providing at least one of the flagged near matches, the flagged suspect matches, and the flagged suspect match group for further analysis.

2. A computer program product as in claim 1 , wherein the operations further comprise routing the set of actual matches for automatic application of one or more post match processes.

3. A computer program product as in claim 2 , wherein the one or more post match processes comprise at least one of consolidation of data, formation of a best record, and disregarding one or more duplicate records.

4. A computer program product as in claim 1 , wherein the providing comprises presenting a user interface displaying at least some of the flagged near matches and/or the flagged suspect matches and supporting functionality that allows a user to perform fine-tuning of one or more of the first criteria, the second criteria, and the third criteria.

5. A computer program product as in claim 4 , wherein the user interface further comprises an auto-generated suggestion feature that proposes changes to one or more of the first criteria, the second criteria, and the third criteria.

6. A computer program product as in claim 4 , wherein the user interface further comprises functionality for illustrating an impact of a change to one or more of the first criteria, the second criteria, and the third criteria on classification of the record pairs.

7. A system comprising:
computer hardware configured to provide operations comprising:
applying first similarity criteria to a set of record pairs to identify a set of near match record pairs, the applying comprising:
identifying a pair of records in the set of record pairs as a near match record pair when:
a similarity between the pair of records exceeds a minimum similarity threshold and when the pair of records is a name,
the pair of records contains an email address comprising a domain name that is the same in the pair of records,
the only difference between the pair of records is a numeric component,
the pair of records match when the pair of records is translated to a same script, and
adding, the near match record pair to the set of near match record pairs;

applying, after identifying the set of near match record pairs, second similarity criteria to the set of near match record pairs to identify a set of actual match record pairs, the second similarity criteria being more strict than the first similarity criteria;
flagging, as near matches, those record pairs of the set of near matches that were not identified as actual matches;
applying, after identifying the set of actual match record pairs, third similarity criteria to the set of actual match record pairs to identify and flag one or more suspect matches, the third similarity criteria being more strict than the second similarity criteria;
flagging, as a suspect match group, the set of actual match record pairs that contain the one or more suspect matches; and
providing at least one of the flagged near matches, the flagged suspect matches, and the flagged suspect match group for further analysis.

8. A system as in claim 7 , wherein the operations further comprise routing the set of actual matches for automatic application of one or more post match processes.

9. A system as in claim 8 , wherein the one or more post match processes comprise at least one of consolidation of data, formation of a best record, and disregarding one or more duplicate records.

10. A system as in claim 7 , wherein the providing comprises presenting a user interface displaying at least some of the flagged near matches and/or the flagged suspect matches and supporting functionality that allows a user to perform fine-tuning of one or more of the first criteria, the second criteria, and the third criteria.

11. A system as in claim 10 , wherein the user interface further comprises an auto-generated suggestion feature that proposes changes to one or more of the first criteria, the second criteria, and the third criteria.

12. A system as in claim 10 , wherein the user interface further comprises functionality for illustrating an impact of a change to one or more of the first criteria, the second criteria, and the third criteria on classification of the record pairs.

13. A system as in claim 7 , wherein the computing hardware comprises:
at least one programmable processor; and
a machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to provide the operations.

14. A computer-implemented method comprising:
applying first similarity criteria to a set of record pairs to identify a set of near match record pairs, the applying comprising:
identifying a pair of records in the set of record pairs as a near match record pair when:
a similarity between the pair of records exceeds a minimum similarity threshold and when the pair of records is a name,
the pair of records contains an email address comprising a domain name that is the same in the pair of records,
the only difference between the pair of records is a numeric component,
the pair of records match when the pair of records is translated to a same script, and
adding, the near match record pair to the set of near match record pairs;

applying, after identifying the set of near match record pairs, second similarity criteria to the set of near match record pairs to identify a set of actual match record pairs, the second similarity criteria being more strict than the first similarity criteria;
flagging, as near matches, those record pairs of the set of near matches that were not identified as actual matches;
applying, after identifying the set of actual match record pairs, third similarity criteria to the set of actual match record pairs to identify and flag one or more suspect matches, the third similarity criteria being more strict than the second similarity criteria;
flagging, as a s

Assignees

• Spiess Mark
• Woody Jeffrey
• Dupey Ronald
• Sap Se

Inventors

• Spiess Mark
• Woody Jeffrey
• Dupey Ronald

Classifications

• G06F16/215 Primary

  Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors · CPC title

• G06F17/30303 Primary

  Physics · mapped topic