The invention relates to an answer selection algorithm based on enhanced question importance representation. The answer selection algorithm comprises the following steps of S1, encoding the questionsand answers through a BiLSTM encoding layer; S2, obtaining a new problem vector of the encoded problem by using a self-attention mechanism; S3, constructing a word-level similarity matrix for the questions and the answers for alignment; S4, capturing the semantic information of multiple granularities, and fusing and comparing the vectors of different granularities; and S5, extracting the fusion features through a multi-window CNN to obtain an optimal option. According to the answer selection algorithm based on the enhanced question importance representation, the answer selection algorithm based on a question importance representation network is provided for the noise words in the sentences, and different weights are given to the words again through the self-attention mechanism, so that theclean question sentence vectors are generated; the fine-grained semantic information between the question sentences and the answer sentences is captured by utilizing the word-level interaction matrix, so that the influence of the noise words in the answer sentences is relieved.
Answer selection algorithm based on enhanced question importance representation