text comparison algorithm based on a stacked bidirectional lstm neural network

The present invention discloses a text comparison algorithm based on a stacked bidirectional lstm neural network, which relates to the field of natural language processing, and includes the followingsteps: Step 1, inputting a sentence segmentation and calculating a word vector, and obtaining a word vector as an input word vector; Second, input the input word vector into the lstm neural network inthe form of network stacking to obtain the input sentence vector; in step 3, obtain the sentence vector of the two input sentences according to steps 1 and 2; input the sentence vector of the two input sentences Go to the classifier and get the similarity of the two sentences. The application of the present invention enables accurate text similarity calculation. 本发明申请公开了种基于堆叠双向lstm神经网络的文本对比算法，涉及自然语言处理领域，包括以下步骤：步骤，将输入句子分词并计算词向量，得到的词向量作为输入词向量；步骤二，将输入词向量以网络堆叠的方式输入到lstm神经网络中，得到输入句子向量；步骤三，按照步骤和步骤二得到两个输入句子的句子向量；将两个输入句子的句子向量输入到分类器中，得到这两个句子的相似度。本发明申请能够准确进行文本相似度计算。