Patent ID: 11874862
Assignee: XI'AN JIAOTONG UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 7:
8. The community question-answer website answer sorting method combined with active learning according to claim 1, wherein the answer sorting model in step 2 is constructed based on the CQA-CNN model of two shared parameters and a fully connected layer, and the text features and community features related to the target questions and two candidate question-answer pairs are input; firstly, the model forms the input target questions and two candidate question-answer pairs into two question-answer triples, and inputs the text features and community features related to the triples into the CQA-CNN model of two shared parameters to obtain feature representations of the question-answer data of the two triples; then, the feature representations of the triples of the question-answer data learned by the CQA-CNN model are input into the fully connected layer, a correlation score between the target questions and the candidate question-answer pairs is obtained through nonlinear mapping, and a final sorting label is output according to the correlation score between the target questions and the two candidate question-answer pairs; when the output is 1, it means that a first candidate question-answer pair ranks higher than a second candidate question-answer pair in the final sorting; and when the output is −1, the result is opposite; and a loss function of the answer sorting model consists of a hinge loss function, a parameter regularization term and a penalty term as follows:, L
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where ti and ti′ represent related feature sets of the question-answer triples with sorting labels of 1 and −1; uj and uj′ represent related feature sets of the question-answer triples with a sorting label of 0; F(tj) indicates a correlation score obtained by inputting ti into the fully connected layer after being represented by CQA-CNN; yi indicates a sorting label expected by the candidate question-answer pair; Φ indicates all the parameters in the answer ordering model, including the parameters in the CQA-CNN model and the fully connected layer; λ and μ indicate t sup parameter of an answer sorting algorithm, λ=0.05, μ=0.01.