IP Library Granted Patent US 12669874
Granted Patent B2
US 12669874 · App. 19/098,803 · Granted Jun 30, 2026

System and method of action-based navigation visualization for supply chain planners and specially-abled users

Inventors: Mayank Tiwari (Serilingampalle, IN); Pankaj Rathoure (Hyderabad, IN); Anirban Bhattacharyya (Ammenpur, IN); Santosh Kumar (Jharkhand, IN)
Assignee: Blue Yonder Group, Inc.
G06F3/0237G06F3/0227G06F9/453G06F16/958G06F40/20G06Q10/06316G06Q10/087
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Quick Facts
Patent No.
US 12669874
App. No.
19/098,803
Granted
Jun 30, 2026
Kind
B2
Abstract

A system and method are disclosed for predicting recommendations for a user interface. The method includes generating a graphical user interface that receives an input from a user of a client portal, crawling tasks associated with the user in the client portal, ranking the tasks according to an intent associated with the input from the user, fetching at least one task from the ranked tasks, calculating a quantity of steps to complete the task from the ranked tasks; identifying one or more slots used by the task in at least one step from the quantity of steps, and generating one or more recommendations comprising a subsequent action for the user to complete the task.

Claims (39)

1 . A system for interacting with a chat bot, comprising:

a system architecture comprising a server, an interface module, a natural language processing engine, a conversation engine, a knowledge base, and a database;

the server, comprising a processor and memory, and configured to:

interact, by the interface module, with a user using text or voice-based natural language by receiving natural language input from the user;

perform, by the natural language processing engine, natural language processing to decode the user input and provide the decoded user input to the knowledge base, wherein the natural language processing engine interprets the user input according to one or more meta- classes, and wherein the one or more meta-classes comprise one or more of: recognize, overview, select, enter and initiate;

receive, by the natural language processing engine, responses from the knowledge base;

transform, by the natural language processing engine, the responses from the knowledge base to natural language responses; and

display, by the conversation engine, the natural language responses.

2 . The system of claim 1 , wherein the database stores interaction history and analytics.

3 . The system of claim 1 , wherein the knowledge base comprises intent-driven markers on layouts which comprises actions and tasks that are possible on the layouts.

4 . The system of claim 3 , wherein the intent-driven markers comprise graphic elements on cards based on an intent of the user.

5 . The system of claim 1 , wherein the knowledge base comprises functional workflows comprising a logical sequence of actions.

6 . The system of claim 5 , wherein the functional workflows comprise operations and tasks that are coupled with a business objective.

7 . The system of claim 1 , wherein the conversation engine comprises a chatbot.

8 . A computer-implemented method for interacting with a chat bot, comprising:

interacting, by an interface module of a server, with a user using text or voice-based natural language by receiving natural language input from the user, wherein the server comprises a processor and memory;

performing, by a natural language processing engine of the server, natural language processing to decode the user input and provide the decoded user input to a knowledge base, wherein the natural language processing engine interprets the user input according to one or more meta-classes, and wherein the one or more meta-classes comprise one or more of:

recognize, overview, select, enter and initiate;

receiving, by the natural language processing engine, responses from the knowledge base;

transforming, by the natural language processing engine, the responses from the knowledge base to natural language responses; and

displaying, by a conversation engine, the natural language responses.

9 . The computer-implemented method of claim 8 , wherein a database stores interaction history and analytics.

10 . The computer-implemented method of claim 8 , wherein the knowledge base comprises intent-driven markers on layouts which comprises actions and tasks that are possible on the layouts.

11 . The computer-implemented method of claim 10 , wherein the intent-driven markers comprise graphic elements on cards based on an intent of the user.

12 . The computer-implemented method of claim 8 , wherein the knowledge base comprises functional workflows comprising a logical sequence of actions.

13 . The computer-implemented method of claim 12 , wherein the functional workflows comprise operations and tasks that are coupled with a business objective.

14 . The computer-implemented method of claim 8 , wherein the conversation engine comprises a chatbot.

15 . A non-transitory computer-readable storage medium embodied with software for interacting with a chat bot, the software when executed by a computer is configured to:

interact, by an interface module of a server, with a user using text or voice-based natural language by receiving natural language input from the user, wherein the server comprises a processor and memory;

perform, by a natural language processing engine of the server, natural language processing to decode the user input and provide the decoded user input to the knowledge base, wherein the natural language processing engine interprets the user input according to one or more meta-classes, and wherein the one or more meta-classes comprise one or more of:

recognize, overview, select, enter and initiate;

receive, by the natural language processing engine, responses from the knowledge base;

transform, by the natural language processing engine, the responses from the knowledge base to natural language responses; and

display, by a conversation engine, the natural language responses.

16 . The non-transitory computer-readable storage medium of claim 15 , wherein a database stores interaction history and analytics.

17 . The non-transitory computer-readable storage medium of claim 15 , wherein the knowledge base comprises intent-driven markers on layouts which comprises actions and tasks that are possible on the layouts.

18 . The non-transitory computer-readable storage medium of claim 17 , wherein the intent-driven markers comprise graphic elements on cards based on an intent of the user.

19 . The non-transitory computer-readable storage medium of claim 15 , wherein the knowledge base comprises functional workflows comprising a logical sequence of actions.

20 . The non-transitory computer-readable storage medium of claim 15 , wherein the conversation engine comprises a chatbot.