IP Library Granted Patent US 11,256,871
Granted Patent B2
US 11,256,871 · App. 16/655,394 · Granted Feb 22, 2022

Automatic discovery of business-specific terminology

Inventors: Christopher J. Jeffs (Roswell, GA); Ian Beaver (Spokane, WA)
Assignee: VERINT AMERICAS INC.
G06F40/30G06F40/279
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Quick Facts
Patent No.
US 11,256,871
App. No.
16/655,394
Granted
Feb 22, 2022
Kind
B2
Abstract

A method and computer product encoding the method is available for preparing a domain or subdomain specific glossary. The method included using probabilities, word context, common terminology and different terminology to identify domain and subdomain specific language and a related glossary updated according to the method.

Claims (28)

1. A computer product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices performs a method of automatically extracting subdomain specific terminology and phrases within a language model for a language domain, comprising:

identifying terminology that is the same for all subdomains in the domain to define a common terminology;

subtracting the common terminology from the language model to identify subdomain-specific terminology for each subdomain;

calculating a priori appearance probability of a series of words using the subdomain terminology for each subdomain; and

automatically determining similarity of meanings of terms across subdomains by identifying terms with the similar appearance probability within a series of words.

2. The computer program product of claim 1 , wherein terms with a high appearance probability are deemed specific to a subdomain.

3. The computer product of claim 1 , the method further comprising determining that subdomain-specific terminology having the same appearance probability and appearing in the same context have equivalent meaning.

4. The computer program product of claim 1 , the method further comprising comparing the appearance probability for each series of words to determine terms important to each subdomain.

5. The computer program product of claim 1 , wherein the calculating a priori appearance probably is calculated using a word lattice.

6. The computer program product of claim 1 , wherein the calculating a priori appearance probability is calculated using word embedding.

7. The computer program product of claim 1 , wherein the subdomain is a specific business within an industry and the domain is the industry.

8. The computer program product of claim 1 , wherein the subdomain is business units common in an industry and the domain is the industry.

9. The computer program product of claim 1 , the method further comprising extracting subdomain-specific technology.

10. The computer program product of claim 1 , the method further comprising populating subdomain-specific glossaries with the subdomain-specific terminology.

11. A method of automatically extracting subdomain specific terminology and phrases within a language model for a language domain, comprising:

identifying terminology that is the same for all subdomains in the domain to define a common terminology;

subtracting the common terminology from the language model to identify subdomain specific terminology for each subdomain;

calculating a priori appearance probability of a series of words using the subdomain terminology for each subdomain; and

automatically determining similarity of meanings of terms across subdomains by identifying terms with the similar appearance probability within a series of words.

12. The method of claim 11 , wherein terms with a high appearance probability are deemed important to a subdomain.

13. The method of claim 11 , further comprising determining that subdomain-specific terminology having the same appearance probability and appearing in the same context have equivalent meaning.

14. The method of claim 11 , comparing the appearance probability for each series of words to determine terms important to each subdomain.

15. The method of claim 11 , wherein the calculating a priori appearance probably is calculated using a word lattice.

16. The method of claim 11 , wherein the calculating a priori appearance probability is calculated using word embedding.

17. The method of claim 11 , wherein the subdomain is a specific business within an industry and the domain is the industry.

18. The method of claim 11 , wherein the subdomain is business units common in an industry and the domain is the industry.

19. The method of claim 11 , further comprising extracting subdomain-specific technology.

20. The method of claim 11 , further comprising populating subdomain-specific glossaries with the subdomain-specific terminology.

Assignments (2)
SECURITY INTEREST Recorded Dec 23, 2025
From: VERINT AMERICAS INC.
To: ALTER DOMUS (US) LLC, AS COLLATERAL AGENT
Reel/Frame 074034/0292 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 21, 2020
From: JEFFS, CHRISTOPHER J.; BEAVER, IAN
To: VERINT AMERICAS INC.
Reel/Frame 051571/0777 →
Continuity (2)
Provisional Application 62746659 · Oct 17, 2018
Related Publication 20200125800A1 · Apr 23, 2020