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

Claim 5:
6. The community question-answer web site answer sorting method combined with active learning according to claim 5, wherein, in the convolution layers, the CQA-CNN model adopts wide convolution to extract the semantic features of several consecutive words; in the pooling layers, the CQA-CNN model adopts two pooling strategies, i.e., partial pooling is adopted by the QA-CNN model for a middle pooling layer, that is, average pooling is implemented for features in a window of a certain length, and complete pooling is adopted by the QA-CNN model for the last pooling layer in the network, that is, average pooling is implemented for convolution results in a sentence length dimension; the attention mechanism module calculates an attention weight based on feature maps output by the convolution layers of the two deep models, and applies results to the pooling layers for weighted pooling; for the feature maps F.sub.q.sup.c and F.sub.q.sup.c obtained by the convolution layers of the text features of the target questions and candidate answers, an attention matrix A is calculated as follows:, A
   
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where |⋅| represents a Euclidean distance;, in the attention matrix A, a sum of elements in each row and column is a weight of words; the feature connection layer merges features including the high-level semantic features of target question texts, the high-level semantic features of candidate answer texts, community features related to the question-answer data, and cosine similarities of feature matrices of original question texts of the target questions and candidate answers, and finally, the question-answer data is represented as a distributed vector by the QA-CNN model.