International business machines corporation (20240126737). TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION simplified abstract
Contents
- 1 TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION
Organization Name
international business machines corporation
Inventor(s)
Meenakshi Madugula of Newark CA (US)
Bailey Duncan of San Jose CA (US)
Nishtha Atrey of San Jose CA (US)
Archana Yadawa of San Jose CA (US)
TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240126737 titled 'TASK DEPENDENCY EXTRACTION SHARING AND NOTIFICATION
Simplified Explanation
The abstract describes a method, computer program product, and computer system that analyze natural language conversations among project participants to identify tasks, determine dependencies between tasks, generate a directed graph of tasks and dependencies, share the graph with participants, and notify blocked participants when dependent tasks are complete.
- Processor analyzes natural language conversation among project participants
- Identifies at least two tasks mentioned in the conversation
- Determines dependency between tasks using a sequential language model
- Generates a directed graph depicting tasks and dependencies
- Shares the graph with participants
- Notifies blocked participants when dependent tasks are complete
Potential Applications
This technology could be applied in project management software to automate task dependency tracking and communication among team members.
Problems Solved
This technology solves the problem of manually tracking task dependencies and notifying team members of blocked tasks in a project.
Benefits
The benefits of this technology include improved project efficiency, better communication among team members, and reduced delays in task completion.
Potential Commercial Applications
- Automated project management software
- Collaboration tools for remote teams
- Task tracking applications for businesses
Possible Prior Art
One possible prior art could be project management software that tracks task dependencies but may not use natural language processing to analyze conversations and automate notifications.
Unanswered Questions
How does the technology handle privacy concerns in analyzing natural language conversations among project participants?
The technology may need to implement strict data privacy measures to ensure that sensitive information shared in conversations is not exposed or misused.
Can the technology adapt to different project management methodologies and team structures?
The adaptability of the technology to various project management methodologies and team structures may impact its effectiveness and usability in different organizational settings.
Original Abstract Submitted
a method, computer program product, and computer system are provided. a processor receives message data from a natural language conversation among participants in a project. a processor identifies at least two tasks mentioned in the message data. a processor determines a dependency between the at least two tasks based on the output of a sequential language model, where the messages associated with the at least two tasks are inputs to the sequential language model. a processor generates a directed graph depicting the at least two tasks and the determined dependency of the at least two tasks. a processor shares a directed graph across participants. a processor notifies participants who are blocked when dependent tasks are complete.
