IP Library Granted Patent US 11,599,714
Granted Patent B2
US 11,599,714 · App. 16/811,737 · Granted Mar 7, 2023

Methods and systems for modeling complex taxonomies with natural language understanding

Inventors: Robert J. Munro (San Francisco, CA); Schuyler D. Erle (San Francisco, CA); Tyler J. Schnoebelen (San Francisco, CA); Jason Brenier (Oakland, CA); Jessica D. Long (San Francisco, CA); Brendan D. Callahan (Philadelphia, PA); Paul A. Tepper (San Francisco, CA); Edgar Nunez (Union City, CA)
Assignee: 100.co Technologies, Inc.
G06F40/169G06F3/0482G06F16/243G06F16/24532G06F16/285G06F16/288G06F16/3329G06F16/35G06F16/367G06F16/93G06F16/951G06F40/137G06F40/221G06F40/30G06F40/40G06F40/42G06N20/00G06Q50/01
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Quick Facts
Patent No.
US 11,599,714
App. No.
16/811,737
Granted
Mar 7, 2023
Kind
B2
Abstract

Systems and methods are presented for the automatic placement of rules applied to topics in a logical hierarchy when conducting natural language processing. In some embodiments, a method includes: accessing, at a child node in a logical hierarchy, at least one rule associated with the child node; identifying a percolation criterion associated with a parent node to the child node, said percolation criterion indicating that the at least one rule associated with the child node is to be associated also with the parent node; associating the at least one rule with the parent node such that the at least one rule defines a second factor for determining whether the document is to also be classified into the parent node; accessing the document for natural language processing; and determining whether the document is to be classified into the parent node or the child node based on the at least one rule.

Claims (43)

1. A method for improving natural language processing conducted by a natural language model, the method comprising:

accessing, at a first node in a logical hierarchy configured to guide classification of a plurality of documents by the natural language model, at least one rule associated with the first node, said at least one rule defining a first factor for determining whether a document among the plurality of documents is to be classified into the first node;

identifying a percolation criterion associated with a second node in the logical hierarchy that is a parent node to the first node, said percolation criterion indicating that the at least one rule associated with the first node is to be associated also with the second node; and

based on the identified percolation criterion, associating the at least one rule with the second node such that the at least one rule defines a second factor for determining whether the document is to also be classified into the second node, the document being classifiable according to the logical hierarchy into at least one of the second node and the first node based on the at least one rule associated with both the first node and the second node.

2. The method of claim 1 , wherein the percolation criterion is a first percolation criterion, and the method further comprises:

identifying a second percolation criterion associated with a third node in the logical hierarchy that is a parent node to the second node, said percolation criterion indicating that the at least one rule associated with the first node is to be associated also with the third node; and

based on the identified second percolation criterion, associating the at least one rule with the third node such that the at least one rule defines a third factor for determining whether the document is to also be classified into the third node.

3. The method of claim 1 , further comprising:

determining that a second percolation criterion is not associated with a third node in the logical hierarchy that is a parent node to the second node; and

based on said determination, limiting the at least one rule to be associated only to the first node and the second node.

4. The method of claim 1 , wherein the percolation criterion includes the second node being repeated at least once within the logical hierarchy.

5. The method of claim 1 , wherein the percolation criterion includes a metadata tag that is enabled.

6. The method of claim 1 , wherein the percolation criterion is specified by user input to a user interface.

7. The method of claim 1 , wherein said accessing is based on the at least one rule being defined by user input to a user interface associated with the first node.

8. A system comprising:

a memory; and

a processor coupled to the memory and configured to:

access, at a first node in a logical hierarchy configured to guide classification of a plurality of documents by the natural language model, at least one rule associated with the first node, said at least one rule defining a first factor for determining whether a document among the plurality of documents is to be classified into the first node;

identify a percolation criterion associated with a second node in the logical hierarchy that is a parent node to the first node, said percolation criterion indicating that the at least one rule associated with the first node is to be associated also with the second node; and

based on the identified percolation criterion, associate the at least one rule with the second node such that the at least one rule defines a second factor for determining whether the document is to also be classified into the second node, the document being classifiable according to the logical hierarchy into at least one of the second node and the first node based on the at least one rule associated with both the first node and the second node.

9. The system of claim 8 , wherein the percolation criterion is a first percolation criterion, and the processor is further configured to:

identify a second percolation criterion associated with a third node in the logical hierarchy that is a parent node to the second node, said percolation criterion indicating that the at least one rule associated with the first node is to be associated also with the third node; and

based on the identified second percolation criterion, associate the at least one rule with the third node such that the at least one rule defines a third factor for determining whether the document is to also be classified into the third node.

10. The system of claim 8 , wherein the processor is further configured to:

determine that a second percolation criterion is not associated with a third node in the logical hierarchy that is a parent node to the second node; and

based on said determination, limit the at least one rule to be associated only to the first node and the second node.

11. The system of claim 8 , wherein the percolation criterion includes the second node being repeated at least once within the logical hierarchy.

12. The system of claim 8 , wherein the percolation criterion includes a metadata tag that is enabled.

13. The system of claim 8 , wherein the percolation criterion is specified by user input to a user interface.

14. The system of claim 8 , wherein said accessing is based on the at least one rule being defined by user input to a user interface associated with the first node.

15. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform operations comprising:

accessing, at a first node in a logical hierarchy configured to guide classification of a plurality of documents by the natural language model, at least one rule associated with the first node, said at least one rule defining a first factor for determining whether a document among the plurality of documents is to be classified into the first node;

identifying a percolation criterion associated with a second node in the logical hierarchy that is a parent node to the first node, said percolation criterion indicating that the at least one rule associated with the first node is to be associated also with the second node; and

based on the identified percolation criterion, associating the at least one rule with the second node such that the at least one rule defines a second factor for determining whether the document is to also be classified into the second node; the document being classifiable according to the logical hierarchy into at least one of the second node and the first node based on the at least one rule associated with both the first node and the second node.

16. The computer readable medium of claim 15 , wherein the percolation criterion is a first percolation criterion, and the operations further comprise:

identifying a second percolation criterion associated with a third node in the logical hierarchy that is a parent node to the second node, said percolation criterion indicating that the at least one rule associated with the first node is to be associated also with the third node; and

based on the identified second percolation criterion, associating the at least one rule with the third node such that the at least one rule defines a third factor for determining whether the document is to also be classified into the third node.

17. The computer readable medium of claim 15 , wherein the operations further comprise:

determining that a second percolation criterion is not associated with a third node in the logical hierarchy that is a parent node to the second node; and

based on said determination, limiting the at least one rule to be associated only to the first node and the second node.

18. The computer readable medium of claim 15 , wherein the percolation criterion includes the second node being repeated at least once within the logical hierarchy.

19. The computer readable medium of claim 15 , wherein the percolation criterion includes a metadata tag that is enabled.

20. The computer readable medium of claim 15 , wherein the percolation criterion is specified by user input to a user interface.

Assignments (10)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 4, 2024
From: 100.CO GLOBAL HOLDINGS, LLC
To: AI IP INVESTMENTS LTD.
Reel/Frame 066636/0583 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 28, 2023
From: DAASH INTELLIGENCE, INC.
To: 100.CO GLOBAL HOLDINGS, LLC
Reel/Frame 064420/0108 →
CHANGE OF NAME Recorded Mar 7, 2023
From: 100.CO TECHNOLOGIES, INC.
To: DAASH INTELLIGENCE, INC.
Reel/Frame 062992/0333 →
NUNC PRO TUNC ASSIGNMENT Recorded Dec 16, 2022
From: 100.CO, LLC
To: 100.CO TECHNOLOGIES, INC.
Reel/Frame 062131/0714 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 5, 2021
From: AI IP INVESTMENTS LTD.
To: 100.CO, LLC
Reel/Frame 056145/0509 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 30, 2021
From: AIPARC HOLDINGS PTE. LTD.
To: AI IP INVESTMENTS LTD
Reel/Frame 056096/0278 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 29, 2021
From: HEALY, TREVOR
To: AIPARC HOLDINGS PTE. LTD.
Reel/Frame 056083/0123 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 27, 2021
From: IDIBON (ASSIGNMENT FOR THE BENEFIT OF CREDITORS), LLC
To: HEALY, TREVOR
Reel/Frame 056057/0325 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 20, 2021
From: IDIBON, INC.
To: IDIBON (ASSIGNMENT FOR THE BENEFIT OF CREDITORS), LLC
Reel/Frame 055978/0362 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 16, 2021
From: MUNRO, ROBERT J.; ERLE, SCHUYLER D.; SCHNOEBELEN, TYLER J.; BRENIER, JASON; LONG, JESSICA D.; CALLAHAN, BRENDAN D.; TEPPER, PAUL A.; NUNEZ, EDGAR
To: IDIBON, INC.
Reel/Frame 055946/0589 →
Continuity (8)
Continuation 16197190 · Nov 20, 2018
Continuation 15294156 · Oct 14, 2016
Continuation 14964511 · Dec 9, 2015
Provisional Application 62089736 · Dec 9, 2014
Provisional Application 62089742 · Dec 9, 2014
Provisional Application 62089745 · Dec 9, 2014
Provisional Application 62089747 · Dec 9, 2014
Related Publication 20210165955A1 · Jun 3, 2021
Cited By (12)
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