IP Library › Granted Patent US 12,647,328
Granted Patent B2
US 12,647,328 · App. 17/521,320 · Granted Jun 2, 2026

Methods and systems for generating a virtual graph of multi channel communications

Inventor: Bradley Taylor (Fort Worth, TX)
Assignee: IntelePeer
H04L41/22H04L67/535
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Quick Facts
Patent No.
US 12,647,328
App. No.
17/521,320
Granted
Jun 2, 2026
Kind
B2
Abstract

A technique is directed to methods and systems for generating a virtual graph of multi-channel communications. In some implementations, a virtual graph system provides a virtual graph relationship that manages the representation and captures the information associated with multi-channel communications, such as communications of a user with a corporate contact center. The information can include session and “customer journey” characteristics of the interaction flow beyond the details of the telecommunication infrastructure. Additionally, the virtual graph system can provide a visualization that communicates both historical details and actionable information found in the interaction graph(s).

Claims (64)

1 . A method for generating a virtual graph of multi-channel communications comprising:

collecting input data of user interactions from at least one multi-channel interaction input;

identifying at least one virtual graph definition source to construct the virtual graph with the input data, wherein the at least one virtual graph definition source is an adapted combination of a derived data source and a designed data source;

compiling comparative metrics and deltas for captured elements from the derived data source and the designed data source;

constructing the virtual graph based on the captured elements in the at least one virtual graph definition source;

identifying a failure of the user interactions in the virtual graph;

receiving data indicating whether the failure of the user interactions results from at least one of a capacity failure or a constraint failure; and

displaying, on a user interface:

the virtual graph illustrating the failure of the user interactions during the multi-channel communications, and

at least one recommendation for examination of the failure of the user interactions.

2 . The method of claim 1 , further comprising:

classifying at least one node and at least one link of the virtual graph;

deriving metadata attributes of the input data of the user interactions; and

identifying graphs, channels, and the user interactions in the input data.

3 . The method of claim 1 , further comprising:

adding notifications to the virtual graph to indicate the failure.

4 . The method of claim 1 , wherein generating the mapping further comprises:

performing a model driven assessment and categorization of attributes and outcomes for the user interactions.

5 . The method of claim 1 , further comprising:

compiling segment and time series metrics for the input data in the virtual graph.

6 . The method of claim 1 , wherein the virtual graph includes graphical and dashboard views with flow details and anomaly detection.

7 . A computing system comprising:

at least one processor; and

at least one memory storing instructions that, when executed by the processor, cause the computing system to perform a process for generating a virtual graph of multi-channel communications, the process comprising:

collecting input data of user interactions from at least one multi-channel interaction input;

identifying at least one virtual graph definition source to construct the virtual graph with the input data, wherein the at least one virtual graph definition source is an adapted combination of a derived data source and a designed data source;

compiling comparative metrics and deltas for captured elements from the derived data source and the designed data source;

constructing the virtual graph based on the captured elements in the at least one virtual graph definition source;

identifying a failure of the user interactions in the virtual graph;

receiving data indicating whether the failure of the user interactions results from at least one of a capacity failure or a constraint failure; and

displaying, on a user interface:

the virtual graph illustrating the failure of the user interactions during the multi-channel communications, and at least one recommendation for examination of the failure of the user interactions.

8 . The computing system of claim 7 , wherein the process further comprises:

classifying at least one node and at least one link of the virtual graph;

deriving metadata attributes of the input data of the user interactions; and

identifying graphs, channels, and the user interactions in the input data.

9 . The computing system of claim 7 , wherein the process further comprises:

adding notifications to the virtual graph to indicate the failure.

10 . The computing system of claim 7 , wherein the process further comprises:

performing a model driven assessment and categorization of attributes and outcomes for the user interactions.

11 . The computing system of claim 7 , wherein the process further comprises:

compiling segment and time series metrics for the input data in the virtual graph.

12 . The computing system of claim 7 , wherein the virtual graph includes graphical and dashboard views with flow details and anomaly detection.

13 . A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for generating a virtual graph of multi-channel communications, the operations comprising:

collecting input data of user interactions from at least one multi-channel interaction input;

identifying at least one virtual graph definition source to construct the virtual graph with the input data, wherein the at least one virtual graph definition source is an adapted combination of a derived data source and a designed data source:

compiling comparative metrics and deltas for captured elements from the derived data source and the designed data source;

constructing the virtual graph based on the captured elements in the at least one virtual graph definition source;

identifying a failure of the user interactions in the virtual graph;

receiving data indicating whether the failure of the user interactions results from at least one of a capacity failure or a constraint failure; and

displaying, on a user interface:

the virtual graph illustrating the failure of the user interactions during the multi-channel communications, and at least one recommendation for examination of the failure of the user interactions.

14 . The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:

classifying at least one node and at least one link of the virtual graph;

deriving metadata attributes of the input data of the user interactions; and

identifying graphs, channels, and the user interactions in the input data.

15 . The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:

adding notifications to the virtual graph to indicate the failure.

16 . The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:

performing a model driven assessment and categorization of attributes and outcomes for the user interactions.

17 . The non-transitory computer-readable medium of claim 13 , wherein the operations further comprise:

compiling segment and time series metrics for the input data in the virtual graph.

18 . The non-transitory computer-readable medium of claim 13 ,

wherein the virtual graph includes graphical and dashboard views with flow details and anomaly detection.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 9, 2021
From: TAYLOR, BRADLEY
To: INTELEPEER
Reel/Frame 058382/0951 →
Continuity (1)
Related Publication 20230147451A1 · May 11, 2023
References Cited (13)
US 11860760B1 · Agarwal · 2024 [cited by examiner]
US 20150350443A1 · Kumar · 2015 [cited by examiner]
US 20160205150A1 · Shaheen et al. · 2016 [cited by applicant]
US 20180219897A1 · Muddu et al. · 2018 [cited by applicant]
US 20190116136A1 · Baudart · 2019 [cited by examiner]
US 20220217236A1 · Roytblat · 2022 [cited by examiner]
WO 2020055321A1 · 2020 [cited by applicant]
J. Jamison and C. Snow, “An architecture for customer experience management based on the Internet of Things,” in IBM Journal of Research and Development, vol. 58, No. 5/6, pp. 15:1-15:11, Sep.-Nov. 2014 (Year: 2014). [cited by examiner]
R. K. Sankar and A. Krishna, “Customer Requirement Patterns for Software Vendors,” 2013 IEEE 16th International Conference on Computational Science and Engineering, Sydney, NSW, Australia, 2013, pp. 508-514 (Year: 2013). [cited by examiner]
I. Benzarti, H. Mili and R. M. de Carvalho, “Modeling and Personalising the Customer Journey: The Case for Case Management,” 2021 IEEE 25th International Enterprise Distributed Object Computing Conference (EDOC), Gold C… [cited by examiner]
A. Mockus, Ping Zhang and P. L. Li, “Predictors of customer perceived software quality,” Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005., St. Louis, MO, USA, 2005, pp. 225-233 (Year:… [cited by examiner]
Braun et al., “Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes”, Marketing Science, Arxiv, p. 1-40, 2010 (Year: 2010). [cited by examiner]
International Application No. PCT/US22/48845, International Search Report and The Written Opinion dated Feb. 9, 2023, 11 pages. [cited by applicant]