IP Library Granted Patent US 11,741,310
Granted Patent B2
US 11,741,310 · App. 17/676,373 · Granted Aug 29, 2023

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 11,741,310
App. No.
17/676,373
Granted
Aug 29, 2023
Kind
B2
Abstract

An IVR and chatbot, or other system, employing a language model, the language model resulting from 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 (32)

1. An interactive response system comprising:

a processor; and

a memory communicatively coupled to the processor comprising executable instructions that, when executed by the processor, cause the system to perform acts comprising:

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

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

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

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

2. The interactive response system of claim 1 , wherein terms with a high appearance probability are deemed specific to a subdomain.

3. The interactive response system of claim 1 , the acts further comprising determine that subdomain-specific terminology having the same appearance probability and appearing in the same context have equivalent meaning.

4. The interactive response system of claim 1 , the acts further compare further comprising comparing the appearance probability for each series of words to determine terms important to each subdomain.

5. The interactive response system of claim 1 , wherein the a priori appearance probability is calculated using a word lattice.

6. The interactive response system of claim 1 , wherein the a priori appearance probability is calculated using word embedding.

7. The interactive response system of claim 1 , wherein the subdomain is a specific business within an industry and the domain is the industry.

8. The interactive response system of claim 1 , wherein the subdomain is business units common in an industry and the domain is the industry.

9. The interactive response system of claim 1 , the acts further comprising extract subdomain-specific technology.

10. The interactive response system of claim 1 , the acts further comprising populate subdomain-specific glossaries with the subdomain-specific terminology.

11. The interactive response system of claim 1 , further comprising a chatbot.

12. The interactive response system of claim 1 , further comprising an interactive voice response system.

13. A method comprising:

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

subtracting the common terminology from a 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.

14. The method of claim 13 , wherein terms with a high appearance probability are deemed specific to a subdomain.

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

16. The method of claim 13 , the method further comprising comparing the appearance probability for each series of words to determine terms important to each subdomain.

17. The method of claim 13 , wherein the a priori appearance probably is calculated using a word lattice.

18. The method of claim 13 , wherein the a priori appearance probability is calculated using word embedding.

19. The method of claim 13 , wherein the subdomain is a specific business within an industry and the domain is the industry.

20. The method of claim 13 , wherein the subdomain is business units common in an industry and the domain is the industry.

21. The method of claim 13 , the method further comprising extracting subdomain-specific technology.

22. The method of claim 13 , the method 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 May 16, 2022
From: JEFFS, CHRISTOPHER J.; BEAVER, IAN
To: VERINT AMERICAS INC.
Reel/Frame 059923/0013 →
Continuity (3)
Continuation 16655394 · Oct 17, 2019
Provisional Application 62746659 · Oct 17, 2018
Related Publication 20220245356A1 · Aug 4, 2022