Uipath, inc. (20240134685). DETECTION OF VARIANTS OF AUTOMATABLE TASKS FOR ROBOTIC PROCESS AUTOMATION simplified abstract
Contents
DETECTION OF VARIANTS OF AUTOMATABLE TASKS FOR ROBOTIC PROCESS AUTOMATION
Organization Name
Inventor(s)
Justin Marks of Redmond WA (US)
Therese Fehrer of Eindhoven (NL)
Charles Park of Bellevue WA (US)
Yunjing Ma of Bellevue WA (US)
DETECTION OF VARIANTS OF AUTOMATABLE TASKS FOR ROBOTIC PROCESS AUTOMATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240134685 titled 'DETECTION OF VARIANTS OF AUTOMATABLE TASKS FOR ROBOTIC PROCESS AUTOMATION
Simplified Explanation: The patent application describes systems and methods for identifying variants of an automatable task based on user interaction data generated from task flow data using task mining and machine learning models.
- Task flow data of an automatable task performance is received and generated using task mining.
- User interaction data is extracted from the task flow data.
- Variants of the automatable task are determined based on the user interaction data using machine learning models.
- The identified variants of the automatable task are output for further analysis or implementation.
Potential Applications: This technology can be applied in various industries such as software development, process automation, and user experience design to optimize task flows and improve user interactions.
Problems Solved: This technology addresses the challenge of efficiently identifying and analyzing variants of automatable tasks to enhance task performance and user experience.
Benefits: The benefits of this technology include increased efficiency in task automation, improved user satisfaction, and enhanced task flow optimization.
Commercial Applications: Title: Enhanced Task Flow Optimization Technology for Software Development and Process Automation This technology can be commercially used in software development companies, automation firms, and user interface design companies to streamline processes, improve task performance, and enhance user interactions.
Prior Art: There is prior art related to task mining, machine learning models for user interaction analysis, and process automation technologies that are relevant to this innovation.
Frequently Updated Research: Ongoing research in the fields of task mining, machine learning, and process automation can provide valuable insights and advancements in this technology.
Questions about Variants of an Automatable Task: Question 1: How does task mining contribute to the identification of variants of automatable tasks? Answer: Task mining helps in analyzing task flow data to extract user interaction patterns and identify potential variants of automatable tasks based on this data.
Question 2: What are the key advantages of using machine learning models to determine variants of automatable tasks? Answer: Machine learning models can efficiently process large amounts of user interaction data to identify patterns and variations in automatable tasks, leading to more accurate and effective results.
Original Abstract Submitted
systems and methods are provided for determining variants of an automatable task. task flow data of a performance of an automatable task by one or more users is received. the task flow data is generated based on user input using task mining. user interaction data is identified from the task flow data. one or more variants of the automatable task are determined based on the user interaction data using a machine learning based model. the one or more variants of the automatable task are output.
