US 11,853,706 B2
Generative language model for few-shot aspect-based sentiment analysis
Ehsan Hosseini-Asl, Palo Alto, CA (US); and Wenhao Liu, Redwood City, CA (US)
Assigned to salesforce.com, inc., San Francisco, CA (US)
Filed by salesforce.com, inc., San Francisco, CA (US)
Filed on Sep. 8, 2021, as Appl. No. 17/468,950.
Claims priority of provisional application 63/189,647, filed on May 17, 2021.
Prior Publication US 2022/0366145 A1, Nov. 17, 2022
Int. Cl. G06F 40/30 (2020.01); G06F 40/284 (2020.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01)
CPC G06F 40/30 (2020.01) [G06F 40/284 (2020.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01)] 20 Claims
OG exemplary drawing
 
10. A method for generating a sentiment analysis, the method comprising:
receiving, at an aspect-based sentiment analysis (ABSA) generative language model stored in a memory, a sentence expressing a sentiment of a user; and
generating, using the ABSA generative language model, at least one pair, the at least one pair including an aspect term in the sentence and a term polarity associated with the aspect term.