US 12,229,195 B2
Method and apparatus for knowledge representation and reasoning in accounting
Paul Sheward, Chicago, IL (US); Chung-Sheng Li, Scarsdale, NY (US); Scott Likens, Austin, TX (US); Saverio Fato, Wilton Manors, FL (US); Joseph Doyle Harrington, Granite Bay, CA (US); Joseph David Voyles, Louisville, KY (US); Jonathan B. Rhine, Suffern, NY (US); Alexander Nicholas Boldizsar, Woodstock, CT (US); Winnie Cheng, West New York, NJ (US); Todd Christopher Morrill, Newburgh, NY (US); Yuan Wan, Irvine, CA (US); and William Spotswood Seward, Los Angeles, CA (US)
Assigned to PwC Product Sales LLC, New York, NY (US)
Filed by PwC Product Sales LLC, New York, NY (US)
Filed on Mar. 9, 2023, as Appl. No. 18/181,280.
Prior Publication US 2024/0303281 A1, Sep. 12, 2024
Int. Cl. G06F 16/901 (2019.01); G06F 16/903 (2019.01); G06F 16/906 (2019.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G06N 5/04 (2023.01); G06Q 40/12 (2023.01)
CPC G06F 16/906 (2019.01) [G06F 16/9024 (2019.01); G06F 16/90335 (2019.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G06N 5/04 (2013.01); G06Q 40/12 (2013.12)] 19 Claims
OG exemplary drawing
 
18. A method for constructing a data structure, the method comprising:
receiving input data;
extracting a plurality of topic entities from the input data;
grouping one or more topic entities of the plurality of topic entities into one or more topic clusters;
identifying one or more linguistic modalities associated in the input data with one or more of the plurality of topic entities;
for a first topic cluster of the one or more topic clusters, constructing a data structure comprising a plurality of nodes, wherein each node of the data structure respectively represents a topic entity extracted from the input data and grouped into the first topic cluster, and wherein a first node of the data structure is associated with a second node of the data structure based on the first node and the second node respectively representing a first topic entity and a second topic entity associated in the input data with a common one of the one or more identified linguistic modalities;
construct a plurality of data structures, each data structure comprising a plurality of nodes included in a respective topic cluster of the one or more topic clusters, wherein each of the nodes of each respective data structure represents a respective topic entity grouped into the respective topic cluster, and wherein nodes within each of the plurality of data structures are interconnected based on the respective topic entities represented by the nodes being associated in the input data with common identified linguistic modalities;
automatically generating a response to an input query using a selected data structure of the plurality of data structures, wherein automatically generating a response to the input query comprises:
receiving an input query;
automatically identifying a topic cluster associated with the input query based on one or both of a first topic prediction model and second topic prediction model;
directing the input query to the selected data structure of the plurality of data structures based on the selected data structure being associated with the identified topic cluster; and
generating a response to the input query based on the data structure comprising the identified topic cluster.