CPC G06F 40/30 (2020.01) [G06F 18/241 (2023.01)] | 20 Claims |
1. A method performed at a computing device having one or more processors and memory storing a plurality of computer-readable instructions to be executed by the one or more processors, the method comprising:
training an initial classification model by using a first sample set, to obtain a pre-trained model, the first sample set comprising a quantity of weakly supervised first samples, each first sample comprising a first social text and an emoticon label in the first social text;
training the pre-trained model by using a second sample set, to obtain a social text sentiment classification model, the second sample set comprising a quantity of supervised second samples, each second sample comprising a second social text and a manually-added sentiment classification label corresponding to the second social text; and
applying a target social text to the social text sentiment classification model as an input to obtain a sentiment class probability distribution corresponding to the target social text as an output.
|