US 12,008,668 B2
Systems and methods for determining structured proceeding outcomes
Thomas Vacek, Minneapolis, MN (US); Dezhao Song, Eagan, MN (US); Tim Nugent, London (GB); Conner Cowling, St. Louis Park, MN (US); Ronald Teo, Inver Grove Heights, MN (US); and Frank Schilder, St. Paul, MN (US)
Assigned to Thomson Reuters Enterprise Centre GmbH, Zug (CH)
Filed by Thomson Reuters Enterprise Centre GmbH, Zug (CH)
Filed on Jan. 29, 2023, as Appl. No. 18/102,760.
Application 18/102,760 is a continuation of application No. 16/446,423, filed on Jun. 19, 2019, granted, now 11,568,503, issued on Jan. 31, 2023.
Claims priority of provisional application 62/686,805, filed on Jun. 19, 2018.
Prior Publication US 2023/0177626 A1, Jun. 8, 2023
Int. Cl. G06Q 50/18 (2012.01); G06N 3/08 (2023.01)
CPC G06Q 50/18 (2013.01) [G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, performed by a deep learning classifier, for identifying an outcome of a structured proceeding, the method comprising:
receiving, at a first level of a neural network of the deep learning classifier, a first word token corresponding to a first word of a first entry of the structured proceeding;
receiving, at the first level of the neural network, a second word token corresponding to a first word of a second entry of the structured proceeding, wherein the first level of the neural network comprises a first plurality of bidirectional gated recurrent units (GRUs) and a second plurality of GRUs;
outputting, by the first plurality of GRUs, a first encoded entry corresponding to the first entry of the structured proceeding;
outputting, by the second plurality of GRUs, a second encoded entry corresponding to the second entry of the structured proceeding;
receiving, at a second level of the neural network of the deep learning classifier, the first encoded entry and the second encoded entry, wherein:
the second level of the neural network includes a third plurality of GRUs,
a first GRU of the third plurality of GRUs is coupled to the first plurality of GRUs and is configured to receive the first encoded entry, and
a second GRU of the third plurality of GRUs is coupled to the second plurality of GRUs and is configured to receive the second encoded entry; and
outputting, by the second level of the neural network, an encoded structured proceeding corresponding to the structured proceeding;
receiving, by a third level of the neural network of the deep learning classifier, the encoded structured proceeding; and
outputting, by the third level of the neural network, a probability score associated with an outcome corresponding to the encoded structured proceeding.