Research on document similarity calculation and detection based on deep learning

Abstract

Abstract In view of the complexity of traditional document similarity calculation methods and the problem of large error, a document similarity calculation and detection method based on deep learning is proposed. The effective subtree matching method is used to calculate the similarity of document feature sequences, and the frequency of feature items is obtained. In order to reduce the complexity of document similarity detection, a deep learning method is used to classify documents. The keywords in the document are extracted, and the similarity calculation and detection results are obtained by calculating the similarity between keywords. The experimental results show that the calculation error of the proposed method is low and the results are reliable, which fully shows that the method is effective and feasible.