US 11,694,020 B2
Systems and methods for XBRL tag suggestion and validation
Rollie Diane Goodman, Philadelphia, PA (US); Houston Dean King, Bozeman, MT (US); Michael Breecher, Phoenix, AZ (US); Edward Joseph Cupps, Ames, IA (US); and Alex Kharbush, Boulder, CO (US)
Assigned to WORKIVA INC., Ames, IA (US)
Filed by WORKIVA INC., Ames, IA (US)
Filed on Jul. 6, 2021, as Appl. No. 17/368,187.
Application 17/368,187 is a continuation of application No. 17/089,211, filed on Nov. 4, 2020, granted, now 11,087,070.
Prior Publication US 2022/0138403 A1, May 5, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/117 (2020.01); G06N 3/08 (2023.01); G06N 3/04 (2023.01); G06F 40/226 (2020.01); G06F 40/14 (2020.01); G06F 18/214 (2023.01); G06F 17/00 (2019.01)
CPC G06F 40/117 (2020.01) [G06F 18/2148 (2023.01); G06F 40/14 (2020.01); G06F 40/226 (2020.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method implemented on a computer system having one or more processors and memories, comprising:
receiving an XBRL document associated with one or more assigned XBRL tags;
analyzing the XBRL document using a trained neural network to generate one or more suggested XBRL tags and determine one or more corresponding confidence values, each suggested XBRL tag of the one or more suggested XBRL tags associated with a confidence value, the trained neural network comprising an input layer, a concatenate layer, and a dropout layer;
comparing the one or more assigned XBRL tags with the one or more suggested XBRL tags to generate comparison results; and
determining a tag confidence value associated with each assigned XBRL tag of the one or more assigned XBRL tags based on the comparison results.