Research on Chinese Sentence Similarity Calculation Method Based on Multiple Features

Chinese sentence similarity calculation is widely used in the field of natural language processing, and the similarity calculation method is also varied. This paper introduces the similarity calculation method based on shallow Information, based on the similarity of part of speech, and also analyzes their calculation principles and calculation methods. Their advantages and disadvantages are given. At the same time, it puts forward the idea of using deep learning thinking to automatically learn the essential information of data from large-scale text data. Using the word2vec model, sentence processing is reduced to word vectors. It also proposes a method for calculating the similarity of shallow features, parts of speech features, and features of word vectors. The experimental results show that compared with the conventional method, the accuracy of the algorithm in calculating the sentence similarity is higher.