IP Library Granted Patent US 9,514,167
Granted Patent B2
US 9,514,167 · App. 13/195,319 · Granted Dec 6, 2016

Behavior based record linkage

Inventors: Mohamed Yakout (Doha, QA); Ahmed K. Elmagarmid (Doha, QA); Hazem Elmeleegy (Doha, QA); Mourad Ouzzani (Doha, QA); Yuan Qi (Doha, QA)
Assignee: QATAR FOUNDATION
G06F17/30303G06F17/30495
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 9,514,167
App. No.
13/195,319
Granted
Dec 6, 2016
Kind
B2
Abstract

A computer implemented method for matching data records from multiple entities comprising providing respective transaction logs for the entities representing actions performed by or in respect of the entities, determining a matching score using the transaction logs for respective pairs of the entities and for predetermined combinations of merged entities by generating a measure representing a gain in behavior recognition for the entities before and after merging, and using the gain as a matching score.

Claims (37)

1. A computer implemented method, with at least one step executed by a computer, the method for matching data records from multiple entities to identify if the multiple entities are the same entity, comprising:

providing respective transaction logs for the multiple entities representing actions performed by or in respect of the multiple entities;

extracting behavior data for the multiple entities from the transaction logs;

determining candidate entity matches between pairs of entities using the behavior data of each entity of the pair by generating pairs of entity matches and using those pairs not discarded by a coarse matching function as candidate entity matches;

merging the behavior data of each pair of candidate entity matches to generate a merged behavior matrix for each pair;

calculating a behavior recognition score for the merged behavior matrix and for each entity of the pair of candidate entity matches;

determining a gain from the behavior recognition score for each entity of the pair of candidate entity matches to the recognition score for the merged behavior matrix of the respective pair of candidate entity matches;

determining a matching score for each pair of candidate entity matches using the gain in behavior recognition score, wherein the gain in behavior recognition score is indicative of the two entities in the pair of candidate entity matches being the same entity;

identifying which entities represent the same entity among the multiple entities if the matching score is above a predetermined threshold; and

associating the identified matching entities of the multiple entities as the same entity.

2. A method as claimed in claim 1 , further comprising converting the transaction logs to a predetermined format to provide a processed log including data from the transaction logs and a set of identifiers representing combinations of features for respective actions.

3. A method as claimed in claim 2 , further comprising generating a behavior matrix for an entity using the identifiers.

4. A method as claimed in claim 3 , further comprising generating a first element of a discrete Fourier transform for a binarised behavior matrix in which non zero values are replaced with the value “1” to provide a complex number representing an action in the behavior matrix.

5. A method as claimed in claim 4 , wherein the inverse of the magnitude of the complex number represents a recognition score for an action of an entity.

6. A method as claimed in claim 1 , wherein determining a matching score includes determining if a merged entity exhibits a consistent behavior compared to a behavior pattern of actions for the individual entities.

7. A method as claimed in claim 1 , wherein determining a matching score includes determining the behavior recognition score for a behavior of an entity representing consistency of the entities behavior over multiple components.

8. A method as claimed in claim 7 , wherein the multiple components include a measure representing consistency in repeating actions, a measure representing stability in features describing actions, and a measure representing association between actions.

9. A method as claimed in claim 1 , further comprising generating a statistical model for the behavior of an entity using the transaction log for that entity, wherein parameters of the model are used to determine a measure for repeated patterns in a sequence corresponding to action occurrences for an entity.

10. A method as claimed in claim 1 , comprising using the transaction logs of the entities to generate the measure representing the gain in the behavior recognition score, wherein the behavior recognition score represents the similarity in behaviors between the entities.

11. A computer program embedded on a non-transitory tangible computer readable storage medium, the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities to identify if the multiple entities are the same entity, comprising:

providing respective transaction logs for the multiple entities representing actions performed by or in respect of the multiple entities;

extracting behavior data for the multiple entities from the transaction logs;

determining candidate entity matches between pairs of entities using the behavior data of each entity of the pair by generating pairs of entity matches and using those pairs not discarded by a coarse matching function as candidate entity matches;

merging the behavior data of each pair of candidate entity matches to generate a merged behavior matrix for each pair;

calculating a behavior recognition score for the merged behavior matrix and for each entity of the pair of candidate entity matches;

determining a gain from the behavior recognition score for each entity of the pair of candidate entity matches to the recognition score for the merged behavior matrix of the respective pair of candidate entity matches;

determining a matching score for each pair of candidate entity matches using the gain in behavior recognition score, wherein the gain in behavior recognition score is indicative of the two entities in the pair of candidate entity matches being the same entity;

identifying which entities represent the same entity among the multiple entities if the matching score is above a predetermined threshold; and

associating the identified matching entities of the multiple entities as the same entity.

12. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 11 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities further comprising converting the transaction logs to a predetermined format to provide a processed log including data from the transaction logs and a set of identifiers representing combinations of features for respective actions.

13. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 12 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities further comprising generating a behavior matrix for an entity using the identifiers.

14. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 13 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities further comprising generating a first element of a discrete Fourier transform for a binarised behavior matrix in which non zero values are replaced with the value “1” to provide a complex number representing an action in the behavior matrix.

15. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 14 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities, wherein the inverse of the magnitude of the complex number represents a recognition score for an action of an entity.

16. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 11 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities wherein determining a matching score includes determining if a merged entity exhibits a consistent behavior compared to a behavior pattern of actions for the individual entities.

17. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 11 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities wherein determining a matching score includes determining the behavior recognition score for a behavior of an entity representing consistency of the entities behavior over multiple components.

18. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 17 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities wherein the multiple components include a measure representing consistency in repeating actions, a measure representing stability in features describing actions, and a measure representing association between actions.

19. A computer program embedded on a non-transitory tangible computer readable storage medium as claimed in claim 11 , the computer program including machine readable instructions that, when executed by a processor, implement a method for matching data records from multiple entities further comprising generating a statistical model for the behavior of an entity using the transaction log for that entity, wherein parameters of the model are used to determine a measure for repeated patterns in a sequence corresponding to action occurrences for an entity.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 17, 2025
From: QATAR FOUNDATION FOR EDUCATION, SCIENCE & COMMUNITY DEVELOPMENT
To: HAMAD BIN KHALIFA UNIVERSITY
Reel/Frame 069936/0656 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 14, 2011
From: YAKOUT, MOHAMED; ELMAGARMID, AHMED K.; ELMELEEGY, HAZEM; OUZZANI, MOURAD; QI, YUAN
To: QATAR FOUNDATION
Reel/Frame 027065/0848 →
Continuity (1)
Related Publication 20130036119A1 · Feb 7, 2013