IP Library Granted Patent US 10,089,383
Granted Patent B1
US 10,089,383 · App. 15/714,866 · Granted Oct 2, 2018

Machine-assisted exemplar based similarity discovery

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 10,089,383
App. No.
15/714,866
Granted
Oct 2, 2018
Kind
B1
Abstract

Embodiments are directed towards managing data. An attributes engine may be employed to perform various actions, including: analyzing characteristics of model object features of a plurality of model objects; classifying the model object features based on the characteristics, such that the characteristics include a data type and values of the model object features; and associating similarity tasks with the model object features based on their classification. A similarity engine may then be employed to perform further actions, including: providing a similarity model that includes the similarity tasks; employing the similarity model to provide candidate similarity scores based on exemplar model objects labeled as being similar; modifying the similarity model based on the exemplar model objects and the candidate similarity scores; employing the modified similarity model to provide similarity scores for model objects based on the one or more similarity tasks.

Claims (120)

1. A method for managing data using one or more processors, included in one or more network computers, to perform actions, comprising:

instantiating an attributes engine to perform further actions, including:

analyzing one or more characteristics of one or more model object features of a plurality of model objects;

classifying the one or more model object features based on the one or more characteristics, wherein the one or more characteristics include a data type and one or more values of the one or more model object features; and

associating one or more similarity tasks with the one or more model object features based on their classification; and

instantiating a similarity engine to perform further actions, including:

providing a similarity model that includes the one or more similarity tasks;

employing the similarity model to provide one or more candidate similarity scores based on one or more exemplar model objects that are labeled as being similar, wherein the one or more exemplar model objects are provided by a similarity client application;

modifying the similarity model based on the one or more exemplar model objects and the one or more candidate similarity scores;

employing the modified similarity model to provide similarity scores for one or more model objects, wherein providing the similarity scores is based on execution of the one or more similarity tasks that are associated with the one or more model object features of the one or more model objects; and

identifying two or more similar model objects based on the similarity scores for visual presentation in a display to a user, wherein one or more features of the visual presentation are modified based on geo-location information of the user provided by a global positioning system (GPS) device, and wherein the one or more modified features include one or more of a time zone, language, currency, or calendar format.

2. The method of claim 1 , wherein the attributes engine performs further actions, comprising:

classifying one or more of the model object fields that include another model object by classifying the other model object's features;

associating one or more additional similarity tasks with the other model object's features; and

including the one or more additional similarity tasks in the similarity model.

3. The method of claim 1 , wherein modifying the similarity model based on the one or more exemplar model objects, further comprises:

employing the similarity model to provide the one or more candidate similarity scores associated with the one or more exemplar model objects;

modifying one or more portions of the similarity model when the candidate similarity score is below a defined threshold value; and

providing additional candidate similarity scores until one or more of the additional candidate similarity scores exceeds the defined threshold.

4. The method of claim 1 , wherein the similarity client application performs further actions, comprising:

displaying the similarity model in a user interface on a hardware display to a user to provide feedback based on the for the similarity model; and

modifying the similarity model based on the provided feedback.

5. The method of claim 1 , wherein classifying the one or more model object features, further comprises, including classification of the one or more model object features as one or more of singled valued, set valued, vector valued, or sequence valued.

6. The method of claim 1 , wherein providing similarity scores for the one or more model objects, further comprises, providing a combination of one or more model object feature similarity scores, wherein the one or more model object feature similarity scores are provided by the one or more similarity tasks.

7. The method of claim 1 , wherein the similarity engine performs actions, further comprising:

associating the modified similarity model with one or more of a user, an organization, or a client; and

differently modifying different instances of the similarity model associated with different users, different organizations, or different clients.

8. A system for managing data, comprising:

a network computer, comprising:

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processor devices that execute instructions that perform actions, including:

instantiating an attributes engine to perform further actions, including:

analyzing one or more characteristics of one or more model object features of a plurality of model objects;

classifying the one or more model object features based on the one or more characteristics, wherein the one or more characteristics include a data type and one or more values of the one or more model object features; and

associating one or more similarity tasks with the one or more model object features based on their classification; and

instantiating a similarity engine to perform further actions, including:

providing a similarity model that includes the one or more similarity tasks;

employing the similarity model to provide one or more candidate similarity scores based on one or more exemplar model objects that are labeled as being similar, wherein the one or more exemplar model objects are provided by a similarity client application;

modifying the similarity model based on the one or more exemplar model objects and the one or more candidate similarity scores;

employing the modified similarity model to provide similarity scores for one or more model objects, wherein providing the similarity scores is based on execution of the one or more similarity tasks that are associated with the one or more model object features of the one or more model objects scores; and

identifying two or more similar model objects based on the similarity; and

a client computer, comprising:

a client computer transceiver that communicates over the network;

a client computer memory that stores at least instructions; and

one or more processor devices that execute instructions that perform actions, including:

employing the similarity client application engine to provide the one or more exemplar model objects in a visual presentation in a display to a user, wherein one or more features of the visual presentation are modified based on geo-location information of the user provided by a global positioning system (GPS) device, and wherein the one or more modified features include one or more of a time zone, language, currency, or calendar format.

9. The system of claim 8 , wherein the attributes engine performs further actions, comprising:

classifying one or more of the model object fields that include another model object by classifying the other model object's features;

associating one or more additional similarity tasks with the other model object's features; and

including the one or more additional similarity tasks in the similarity model.

10. The system of claim 8 , wherein modifying the similarity model based on the one or more exemplar model objects, further comprises:

employing the similarity model to provide the one or more candidate similarity scores associated with the one or more exemplar model objects;

modifying one or more portions of the similarity model when the candidate similarity score is below a defined threshold value; and

providing additional candidate similarity scores until one or more of the additional candidate similarity scores exceeds the defined threshold.

11. The system of claim 8 , wherein the similarity client application performs further actions, comprising:

displaying the similarity model in a user interface on a hardware display to a user to provide feedback based on the for the similarity model; and

modifying the similarity model based on the provided feedback.

12. The system of claim 8 , wherein classifying the one or more model object features, further comprises, including classification of the one or more model object features as one or more of singled valued, set valued, vector valued, or sequence valued.

13. The system of claim 8 , wherein providing similarity scores for the one or more model objects, further comprises, providing a combination of one or more model object feature similarity scores, wherein the one or more model object feature similarity scores are provided by the one or more similarity tasks.

14. The system of claim 8 , wherein the similarity engine performs further actions comprising:

associating the modified similarity model with one or more of a user, an organization, or a client; and

differently modifying different instances of the similarity model associated with different users, different organizations, or different clients.

15. A processor readable non-transitory storage media that includes instructions for managing data, wherein execution of the instructions by one or more hardware processors performs actions, comprising:

instantiating an attributes engine to perform further actions, including:

analyzing one or more characteristics of one or more model object features of a plurality of model objects;

classifying the one or more model object features based on the one or more characteristics, wherein the one or more characteristics include a data type and one or more values of the one or more model object features; and

associating one or more similarity tasks with the one or more model object features based on their classification; and

instantiating a similarity engine to perform further actions, including:

providing a similarity model that includes the one or more similarity tasks;

employing the similarity model to provide one or more candidate similarity scores based on one or more exemplar model objects that are labeled as being similar, wherein the one or more exemplar model objects are provided by a similarity client application;

modifying the similarity model based on the one or more exemplar model objects and the one or more candidate similarity scores;

employing the modified similarity model to provide similarity scores for one or more model objects, wherein providing the similarity scores is based on execution of the one or more similarity tasks that are associated with the one or more model object features of the one or more model objects; and

identifying two or more similar model objects based on the similarity scores for visual presentation in a display to a user, wherein one or more features of the visual presentation are modified based on geo-location information of the user provided by a global positioning system (GPS) device, and wherein the one or more modified features include one or more of a time zone, language, currency, or calendar format.

16. The media of claim 15 , wherein the attributes engine performs further actions, comprising:

classifying one or more of the model object fields that include another model object by classifying the other model object's features;

associating one or more additional similarity tasks with the other model object's features; and

including the one or more additional similarity tasks in the similarity model.

17. The media of claim 15 , wherein modifying the similarity model based on the one or more exemplar model objects, further comprises:

employing the similarity model to provide the one or more candidate similarity scores associated with the one or more exemplar model objects;

modifying one or more portions of the similarity model when the candidate similarity score is below a defined threshold value; and

providing additional candidate similarity scores until one or more of the additional candidate similarity scores exceeds the defined threshold.

18. The media of claim 15 , wherein the similarity client application performs further actions, comprising:

displaying the similarity model in a user interface on a hardware display to a user to provide feedback based on the for the similarity model; and

modifying the similarity model based on the provided feedback.

19. The media of claim 15 , wherein classifying the one or more model object features, further comprises, including classification of the one or more model object features as one or more of singled valued, set valued, vector valued, or sequence valued.

20. The media of claim 15 , wherein providing similarity scores for the one or more model objects, further comprises, providing a combination of one or more model object feature similarity scores, wherein the one or more model object feature similarity scores are provided by the one or more similarity tasks.

21. The media of claim 15 , wherein the similarity engine performs further actions comprising:

associating the modified similarity model with one or more of a user, an organization, or a client; and

differently modifying different instances of the similarity model associated with different users, different organizations, or different clients.

22. A network computer for managing data, comprising:

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processor devices that execute instructions that perform actions, including:

instantiating an attributes engine to perform further actions, including:

analyzing one or more characteristics of one or more model object features of a plurality of model objects;

classifying the one or more model object features based on the one or more characteristics, wherein the one or more characteristics include a data type and one or more values of the one or more model object features; and

associating one or more similarity tasks with the one or more model object features based on their classification; and

instantiating a similarity engine to perform further actions, including:

providing a similarity model that includes the one or more similarity tasks;

employing the similarity model to provide one or more candidate similarity scores based on one or more exemplar model objects that are labeled as being similar, wherein the one or more exemplar model objects are provided by a similarity client application;

modifying the similarity model based on the one or more exemplar model objects and the one or more candidate similarity scores;

employing the modified similarity model to provide similarity scores for one or more model objects, wherein providing the similarity scores is based on execution of the one or more similarity tasks that are associated with the one or more model object features of the one or more model objects; and

identifying two or more similar model objects based on the similarity scores for visual presentation in a display to a user, wherein one or more features of the visual presentation are modified based on geo-location information of the user provided by a global positioning system (GPS) device, and wherein the one or more modified features include one or more of a time zone, language, currency, or calendar format.

23. The network computer of claim 22 , wherein the attributes engine performs further actions, comprising:

classifying one or more of the model object fields that include another model object by classifying the other model object's features;

associating one or more additional similarity tasks with the other model object's features; and

including the one or more additional similarity tasks in the similarity model.

24. The network computer of claim 22 , wherein modifying the similarity model based on the one or more exemplar model objects, further comprises:

employing the similarity model to provide the one or more candidate similarity scores associated with the one or more exemplar model objects;

modifying one or more portions of the similarity model when the candidate similarity score is below a defined threshold value; and

providing additional candidate similarity scores until one or more of the additional candidate similarity scores exceeds the defined threshold.

25. The network computer of claim 22 , wherein the similarity client application performs further actions, comprising:

displaying the similarity model in a user interface on a hardware display to a user to provide feedback based on the for the similarity model; and

modifying the similarity model based on the provided feedback.

26. The network computer of claim 22 , wherein classifying the one or more model object features, further comprises, including classification of the one or more model object features as one or more of singled valued, set valued, vector valued, or sequence valued.

27. The network computer of claim 22 , wherein providing similarity scores for the one or more model objects, further comprises, providing a combination of one or more model object feature similarity scores, wherein the one or more model object feature similarity scores are provided by the one or more similarity tasks.

28. The network computer of claim 22 , wherein the similarity engine performs further actions comprising:

associating the modified similarity model with one or more of a user, an organization, or a client; and

differently modifying different instances of the similarity model associated with different users, different organizations, or different clients.

Assignments (7)
CHANGE OF NAME Recorded Jun 16, 2025
From: SPARKCOGNITION, INC.
To: AVATHON, INC.
Reel/Frame 071646/0135 →
MERGER Recorded Jun 16, 2025
From: SPARKCOGNITION Q, INC.
To: SPARKCOGNITION, INC.
Reel/Frame 071421/0898 →
TERMINATION AND RELEASE OF INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 4, 2024
From: ORIX GROWTH CAPITAL, LLC
To: SPARKCOGNITION, INC.
Reel/Frame 069300/0567 →
TERMINATION AND RELEASE OF INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Nov 4, 2024
From: ORIX GROWTH CAPITAL, LLC
To: SPARKCOGNITION Q, INC.
Reel/Frame 069436/0870 →
SECURITY INTEREST Recorded Apr 21, 2022
From: SPARKCOGNITION Q, INC.
To: ORIX GROWTH CAPITAL, LLC
Reel/Frame 059672/0175 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 21, 2021
From: MAANA, INC.
To: SPARKCOGNITION Q, INC.
Reel/Frame 056935/0540 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 25, 2017
From: MACKAY, JASON FORREST; STOICA-BECK, ALINA MIHAELA; THOMPSON, RALPH DONALD, III
To: MAANA, INC.
Reel/Frame 043685/0775 →
Cited By (1)
US 12,561,565