Method for selecting annotated sample, apparatus, electronic device and storage medium

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively coupled to the at least one processor;
• wherein,
• the memory stores instructions executable by the at least one processor, the instructions are executed by the at least one processor to cause the at least one processor to implement a method for selecting an annotated sample, comprising:
• determining a first attribute and a second attribute of a sample characteristic;
• wherein the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set;
• and
• determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute;
• wherein the target annotated sample is configured to train a classification model, the classification model comprises a model for determining an emotion polarity by analyzing an input sample to be classified.

A non-transitory computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions are configured to cause a computer to implement a method for selecting an annotated sample, comprising:

• determining a first attribute and a second attribute of a sample characteristic;
• wherein the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set;
• and
• determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute;
• wherein the target annotated sample is configured to train a classification model, the classification model comprises a model for determining an emotion polarity by analyzing an input sample to be classified.