EP-4736022-A1 - EFFICIENT PROCESSING OF TRIE DATA STRUCTURES TO SUPPORT CUSTOMER JOURNEY VISUALIZATIONS

Abstract

A method for providing efficient trie data structure processing according to an embodiment includes splitting, based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions, and producing a set of multiple trie data structures, including generating a trie data structure for each partition. Each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization. The method also includes merging multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure and storing the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.

Inventors

• OLADEHINDE-BELLO, Ameen
• HALLY, Colm John
• MCEVOY, Maud D.
• PAT, Ankit
• ROCHE, PETER
• SHAH, Aditi

Assignees

• Genesys Cloud Services, Inc.

Dates

Publication Date

20260506

Application Date

20250213

Claims (20)

1. 1. A method for providing efficient trie data structure processing, the method comprising: splitting, by a computing system and based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions; producing, by the computing system, a set of multiple trie data structures, including generating a trie data structure for each partition, wherein each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization; merging, by the computing system, multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure; and storing, by the computing system, the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.
2. 2. The method of claim 1, further comprising: assigning, by the computing system, each partition to a separate execution unit for concurrent processing.
3. 3. The method of claim 1, further comprising: performing, by the computing system, analytics on the combined organization trie data structure including filtering the combined organization trie data structure as a function of a path category indicative of a type of event that occurred during the customer interactions with the automated agents of the contact center.
4. 4. The method of claim 1, wherein merging the multiple trie data structures comprises: identifying a set of unique organization identifiers associated with the multiple trie data structures; repartitioning the data frame based on the organization identifiers; and merging trie data structures that are associated with a shared organization identifier.
5. 5. The method of claim 1, wherein merging the multiple trie data structures comprises: initializing an empty base trie data structure; reading multiple trie data structures of the set from storage as subtrie data structures; and merging each subtrie data structure into the base trie data structure.
6. 6. The method of claim 5, wherein merging each subtrie data structure into the base trie data structure comprises, for each subtrie data structure: sorting node paths by distance from a root in ascending order; and combining a subtrie node with a base trie node in response to a determination that a node path exists in the base trie data structure or adding the subtrie node to the base trie data structure as a new node in response to a determination that the node path does not exist in the base trie data structure.
7. 7. The method of claim 1, further comprising: tracking, by the computing system, merged nodes of the combined organization trie data structure using a node map; and calculating, by the computing system, an edge count for a selected node represented in the node map, including querying the node map to identify the set of merged nodes and summing individual counts associated with the merged nodes.
8. 8. The method of claim 1, further comprising: identifying, by the computing system, a selected node of the combined organization trie data structure for a drilled-down view in the visualization; identifying, by the computing system, a child node set of one or more child nodes of the selected node; and deleting, by the computing system, the child node set from the visualization.
9. 9. The method of claim 8, further comprising: identifying a parent node set of one or more parent nodes of the selected node; identifying a set of one or more child nodes of the parent node set; subtracting counts of the identified child nodes from counts of corresponding parent nodes in the parent node set to provide an accurate representation of count data pertaining to the drilled-down view; and deleting the identified child nodes of the parent node set in the drilled-down view.
10. 10. A system for providing efficient trie data structure processing, the system comprising: at least one processor; and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to: split, based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions; produce a set of multiple trie data structures, including generating a trie data structure for each partition, wherein each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization; merge multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure; and store the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.
11. 11. The system of claim 10, wherein the plurality of instructions further causes the system to assign each partition to a separate execution unit for concurrent processing.
12. 12. The system of claim 10, wherein the plurality of instructions further causes the system to perform analytics on the combined organization trie data structure including filtering the combined organization trie data structure as a function of a path category indicative of a type of event that occurred during the customer interactions with the automated agents of the contact center.
13. 13. The system of claim 10, wherein to merge the multiple trie data structures comprises to: identify a set of unique organization identifiers associated with the multiple trie data structures; repartition the data frame based on the organization identifiers; and merge trie data structures that are associated with a shared organization identifier.
14. 14. The system of claim 10, wherein to merge the multiple trie data structures comprises to: initialize an empty base trie data structure; read multiple trie data structures of the set from storage as subtrie data structures; and merge each subtrie data structure into the base trie data structure.
15. 15. The system of claim 14, wherein to merge each subtrie data structure into the base trie data structure comprises, for each subtrie data structure, to: sort node paths by distance from a root in ascending order; and combine a subtrie node with a base trie node in response to a determination that a node path exists in the base trie data structure or add the subtrie node to the base trie data structure as a new node in response to a determination that the node path does not exist in the base trie data structure.
16. 16. The system of claim 10, wherein the plurality of instructions further causes the system to: track merged nodes of the combined organization trie data structure using a node map; and calculate an edge count for a selected node represented in the node map, including querying the node map to identify the set of merged nodes and summing individual counts associated with the merged nodes.
17. 17. The system of claim 10, wherein the plurality of instructions further causes the system to: identify a selected node of the combined organization trie data structure for a drilled- down view in the visualization; identify a child node set of one or more child nodes of the selected node; and delete the child node set from the visualization.
18. 18. The system of claim 10, wherein the plurality of instructions further causes the system to: identify a parent node set of one or more parent nodes of the selected node; identify a set of one or more child nodes of the parent node set; subtract counts of the identified child nodes from counts of corresponding parent nodes in the parent node set to provide an accurate representation of count data pertaining to the drilled- down view; and delete the identified child nodes of the parent node set in the drilled-down view.
19. 19. One or more non-transitory machine-readable storage media comprising a plurality of instructions stored thereon that, in response to execution by a computing system, causes the computing system to: split, based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions; produce a set of multiple trie data structures, including generating a trie data structure for each partition, wherein each trie data structure represents aggregate counts of a corresponding subset of event sequences associated with a corresponding organization; merge multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure; and store the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure.
20. 20. The one or more non-transitory machine-readable storage media of claim 19, wherein the plurality of instructions further causes the computing system to assign each partition to a separate execution unit for concurrent processing.

Description

EFFICIENT PROCESSING OF TRIE DATA STRUCTURES TO SUPPORT CUSTOMER JOURNEY VISUALIZATIONS CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This application claims priority to and the benefit of U.S. Provisional Application number 63/552,886, titled “ENHANCED GENERATION OF CUSTOMER JOURNEY VISUALIZATIONS VIA USE OF TRIE DATA STRUCTURES,” filed on February 13, 2024. This application also claims the benefit of U.S. Patent Application 19/051,099, titled “EFFICIENT PROCESSING OF TRIE DATA STRUCTURES TO SUPPORT CUSTOMER JOURNEY VISUALIZATIONS”, filed on February 11, 2025. BACKGROUND [0002] A customer of a product or service provided by an organization may contact a call center or contact center associated with an organization to obtain support related to the product or service. In doing so, the customer may interact with human and/or virtual agents via electronic communications through technologies including, for example, telephone, email, web chat, Short Message Service (SMS), dedicated software application(s), and/or other technologies. In many scenarios, a customer may be routed among multiple agents as the communication progresses and the type of support and/or the particular agent best suited to provide the requested support is determined. SUMMARY [0003] One embodiment is directed to a unique system, components, and methods for providing efficient trie data structure processing to support customer journey visualizations. Other embodiments are directed to apparatuses, systems, devices, hardware, methods, and combinations thereof for providing efficient trie data structure processing to support customer journey visualizations. [0004] According to an embodiment, a method for providing efficient trie data structure processing may include splitting, by a computing system and based on organization identifiers and sequence identifiers, a data frame indicative of a set of events associated with customer interactions with automated agents of a contact center to produce a set of multiple partitions. The method may also include producing, by the computing system, a set of multiple trie data structures, including generating a trie data structure for each partition. Each trie data structure may represent aggregate counts of a corresponding subset of event sequences associated with a corresponding organization. The method may also include merging, by the computing system, multiple trie data structures of the set of trie data structures to produce a combined organization trie data structure and storing, by the computing system, the combined organization trie data structure to enable generation of a visualization of the combined organization trie data structure. [0005] In some embodiments, the method may also include assigning, by the computing system, each partition to a separate execution unit for concurrent processing. [0006] In some embodiments, the method may also include performing, by the computing system, analytics on the combined organization trie data structure including filtering the combined organization trie data structure as a function of a path category indicative of a type of event that occurred during the customer interactions with the automated agents of the contact center. [0007] In some embodiments, merging the multiple trie data structures may include identifying a set of unique organization identifiers associated with the multiple trie data structures, repartitioning the data frame based on the organization identifiers and merging trie data structures that are associated with a shared organization identifier. [0008] In some embodiments, merging the multiple trie data structures may include initializing an empty base trie data structure, reading multiple trie data structures of the set from storage as subtrie data structures, and merging each subtrie data structure into the base trie data structure. [0009] In some embodiments, merging each subtrie data structure into the base trie data structure may include, for each subtrie data structure, sorting node paths by distance from a root in ascending order and combining a subtrie node with a base trie node in response to a determination that a node path exists in the base trie data structure or adding the subtrie node to the base trie data structure as a new node in response to a determination that the node path does not exist in the base trie data structure. [0010] In some embodiments, the method may further include tracking, by the computing system, merged nodes of the combined organization trie data structure using a node map and calculating, by the computing system, an edge count for a selected node represented in the node map, including querying the node map to identify the set of merged nodes and summing individual counts associated with the merged nodes. [0011] In some embodiments, the method may further include identifying, by the computing system, a selected node of the combined organization trie data structure for a drilled- down view in the visualiz