PROVIDING QA TRAINING DATA AND TRAINING A QA MODEL BASED ON IMPLICIT RELEVANCE FEEDBACKS

摘要

The present disclosure provides methods and apparatuses for providing QA training data and training a QA model based on implicit relevance feedbacks. A question-passage pair and corresponding user behaviors may be obtained from a search log. Behavior features may be extracted from the user behaviors. A relevance score between the question and the passage may be determined, through an implicit relevance feedback model, based on the behavior features. A relevance label may be added to the question-passage pair based on the relevance score. The QA model may be pre-trained with the obtained auto-labelled QA training data, and the pre-trained QA model may be fine-tuned with human-labelled QA training data.