关键词: 图结构密点, 密点置信度, 辅助定密, 定密规则, 密点抽取

Abstract: Auxiliary secret classification is a special text classification task that divides undecided encrypted text into different levels of confidentiality.. In order to solve the problems of the traditional method, such as weak feature representation and extraction ability and low interpretability of the classification process, keypoints feature representation method based on graph structure was proposed. On that basis, an auxiliary secret classification model based on keypoints extraction was further proposed, so as to enhance the ability of secret point features in describing the confidential matters, thus the performance of the auxiliary classification model is enhanced. Specifically, this paper deeply analyze the characteristics of classification rules, constructs the keypoints template with reference to text representation method of the graphic structure, extracts the keypoints and calculates the confidence level of the keypoints of the text to be classified, and obtains the secret level prediction results and the classification basis items through the filtered effective keypoints. The experimental result on the ACD indicates that the accuracy and recall rate of this model are 10% and 7% higher than those of BERT and TextCNN, which verifies the effectiveness of keypoints feature representation method based on the graph structure.

Key words: graph structure keypoints, confidence of the keypoints, auxiliary classification, classification rules, extracting keypoints