IP Library Granted Patent US 7,809,747
Granted Patent B2
US 7,809,747 · App. 11/585,358 · Granted Oct 5, 2010

Fuzzy database matching

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Quick Facts
Patent No.
US 7,809,747
App. No.
11/585,358
Granted
Oct 5, 2010
Kind
B2
Abstract

A method of improving the speed with which a sample such as a biometric sample can be fuzzily matched against records in a database, comprises extracting characteristics from the sample, and using those extracted characteristics as indexes ( 70 ) to address a lookup table ( 25 ). Each row within the lookup table points to an individual record occurrence list ( 28, 30, 32 ) which contain details of not only the stored records from which the given characteristic can be extracted, but also those records having an extracted characteristic which are within a defined proximity to the said characteristic. Characteristics are extracted from the sample record, and a given stored record is identified as being a possible match with the sample if it appears in a required number of record occurrence lists.

Claims (32)

1. A method of identifying possible matches between a sample record and a plurality of stored records, the method comprising:

extracting from each of the stored records a plurality of index characteristics, said index characteristics falling within an index characteristic space;

maintaining a look-up table defining said index characteristic space, said look-up table having a plurality of rows, each row corresponding to a unique index characteristic within said index characteristic space;

maintaining a plurality of record occurrence lists, each said list being linked from a specific row in said look-up table corresponding to a specific index characteristic, and each said list identifying those stored records from which said specific index characteristic and index characteristics within a defined proximity to said specific index characteristics within said index characteristic space have been extracted;

extracting sample index characteristics from a sample record;

using said sample index characteristics as indexes to address said look-up table to look up a corresponding plurality of record occurrence lists which are associated with said sample index characteristics;

building a histogram as index characteristics are extracted recording matches by stored record;

counting the number of occurrences of respective stored records identified within said record occurrence lists from the histogram; and

identifying a given stored record as being a possible match with the sample if said count from the histogram for said given stored record exceeds a required threshold.

2. A method as claimed in claim 1 in which the defined proximity is a defined Hamming distance.

3. A method as claimed in claim 2 in which the defined Hamming distance is user-selectable.

4. A method as claimed in claim 1 in which the required number is a numerical threshold.

5. A method as claimed in claim 1 in which the required number is a function of the average number of record occurrence lists per stored record.

6. A method as claimed in claim 1 in which said plurality of index characteristics defines all index characteristics within the index characteristic space that are extracted from said plurality of stored records.

7. A method as claimed in claim 1 in which said plurality of index characteristics defines all possible index characteristics within the index characteristic space that could be displayed by a sample record.

8. A method as claimed in claim 1 in which the said plurality of index characteristics is generated by applying an operation, such as a hash, to the stored records.

9. A method as claimed in claim 1 including establishing a plurality of defined proximities, and maintaining a separate record occurrence list for each index characteristic and proximity combination.

10. A method as claimed in claim 9 in which the identifying step uses those lists which relate to a user-selected defined proximity.

11. A method as claimed in claim 1 including the additional step of further analyzing the relationship between the sample record and each of the said possible matches.

12. A method as claimed in claim 1 in which the said identifying step is divided between a plurality of parallel processors, each forwarding an association result to a consolidator, said consolidator identifying stored records as possible matches in dependence upon said association results.

13. A system for identifying possible matches between a sample record and a plurality of stored records, the system comprising:

a computer processor coupled to a database containing a plurality of index characteristics extracted from said stored records, said index characteristics falling within an index characteristic space;

a look-up table defining said characteristic space, said look-up table having a plurality of rows, each row corresponding to a unique index characteristic within said index characteristic space;

a plurality of record occurrence lists, each said list being linked from a specific row in said look-up table corresponding to a specific index characteristic, and each said list identifying those stored records from which said specific index characteristic and index characteristics within a defined proximity to said specific index characteristics within said index characteristic space have been extracted;

and whereby the system is configured to:

extract sample index characteristics from a sample record, and use said sample index characteristics as indexes to address said look-up table to look up a corresponding plurality of record occurrence lists which are associated with said sample index characteristics;

build a histogram as index characteristics are extracted recording matches by stored record;

count the number of occurrences of respective stored records identified by said record occurrence lists from the histogram; and

identify a given stored record as being a possible match with the sample record if said count from the histogram for said given stored record exceeds a required threshold.

14. A system as claimed in claim 13 in which the computer processor includes a first processor for extracting sample index characteristics from a sample record and a second processor for identifying a given stored record as being a possible match with the sample record.

15. A system as claimed in claim 14 in which the first processor is remote from the second processor.

16. A system as claimed in claim 13 in which the first processor comprises a plurality of parallel processors, each forwarding an association result to a consolidator, said consolidator identifying stored records as possible matches in dependence upon said associated results.

Assignments (7)
CONVERSION Recorded Jun 12, 2025
From: ADEIA MEDIA HOLDINGS LLC
To: ADEIA MEDIA HOLDINGS INC.
Reel/Frame 071577/0875 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 12, 2025
From: TOBII TECHNOLOGIES LTD
To: ADEIA MEDIA HOLDINGS LLC
Reel/Frame 071572/0855 →
SECURITY INTEREST Recorded May 28, 2025
From: ADEIA INC. (F/K/A XPERI HOLDING CORPORATION); ADEIA HOLDINGS INC.; ADEIA MEDIA HOLDINGS INC.; ADEIA IMAGING LLC; ADEIA MEDIA LLC; ADEIA MEDIA SOLUTIONS INC.; ADEIA SEMICONDUCTOR BONDING TECHNOLOGIES INC.; ADEIA TECHNOLOGIES INC.; ADEIA GUIDES INC.; ADEIA SOLUTIONS LLC; ADEIA SEMICONDUCTOR ADVANCED TECHNOLOGIES INC.; ADEIA SEMICONDUCTOR SOLUTIONS LLC; ADEIA SEMICONDUCTOR INTELLECTUAL PROPERTY LLC; ADEIA SEMICONDUCTOR TECHNOLOGIES LLC; ADEIA PUBLISHING INC.
To: BANK OF AMERICA, N.A., AS COLLATERAL AGENT
Reel/Frame 071454/0343 →
CHANGE OF NAME Recorded Mar 31, 2025
From: FOTONATION LIMITED
To: TOBII TECHNOLOGIES LIMITED
Reel/Frame 070682/0207 →
CHANGE OF NAME Recorded Feb 17, 2025
From: FOTONATION LIMITED
To: TOBII TECHNOLOGY LIMITED
Reel/Frame 070238/0774 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 11, 2015
From: BRAINSTORM INTERNATIONAL SERVICES LIMITED
To: FOTONATION LIMITED
Reel/Frame 034964/0018 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 27, 2015
From: MONRO, DONALD MARTIN
To: BRAINSTORM INTERNATIONAL SERVICES LIMITED
Reel/Frame 034819/0708 →