US 11,941,414 B2
Unstructured extensions to rpa
Jatin Ganhotra, White Plains, NY (US); Sachindra Joshi, Gurgaon (IN); Nathaniel Mills, Coventry, CT (US); and Luis A. Lastras-Montano, Cortlandt Manor, NY (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Nov. 20, 2020, as Appl. No. 16/953,706.
Prior Publication US 2022/0164200 A1, May 26, 2022
Int. Cl. G06F 11/34 (2006.01); G06F 9/451 (2018.01); G06F 9/54 (2006.01); G06F 11/30 (2006.01); G06F 40/00 (2020.01); G06F 40/216 (2020.01); G06N 5/025 (2023.01); G06Q 10/0631 (2023.01); G06Q 10/0633 (2023.01)
CPC G06F 9/451 (2018.02) [G06F 9/542 (2013.01); G06F 11/302 (2013.01); G06F 11/3438 (2013.01); G06F 40/00 (2020.01); G06F 40/216 (2020.01); G06N 5/025 (2013.01); G06Q 10/06316 (2013.01); G06Q 10/0633 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
identifying events based on monitoring agent actions performed on a workstation when performing a task multiple times, wherein the identified events correspond to both unstructured and structured data sources, wherein identifying the events comprises:
assigning individual utterances in the unstructured data source as a first set of events,
identifying operating system (OS)-level events performed on the structured data source by monitoring actions of the OS in the workstation, and
identifying intra-application input/output (I/O) events performed on the structured data source by monitoring an I/O device used by the agent;
adding timestamps to the first set of events, the OS-level events, and the intra-application I/O events;
identify groupings of duplicate events in the identified events that each correspond to a common event using pattern matching;
identify causal relationships between the common events based on the timestamps;
mapping, based on at least one of the causal relationships, a first common event corresponding to the unstructured data source to a second common event corresponding to the structured data source; and
generating an ordered list of instructions for a robotic process automation (RPA) of a bot based on the mapped events.