Content auditing method and device, electronic equipment and storage medium

Abstract

The invention provides a content auditing method and device, electronic equipment and a storage medium, and relates to the technical field of content auditing, multi-level feature extraction is performed on an original text to generate text vectors, and a self-adaptive hierarchical clustering algorithm is adopted to cluster the text vectors, so that the content auditing efficiency is improved. And meanwhile, key text features are extracted based on a clustering result to generate hierarchical violation labels, and the violation classification model is updated by utilizing new violation labels through an incremental learning mechanism. The problems that in the prior art, text variants are difficult to recognize due to insufficient keyword filtering semantic understanding, traditional hierarchical clustering calculation is high in complexity and cannot adapt to large-scale data, a machine learning classification model lacks a dynamic updating mechanism, so that new illegal content is missed, and the model is difficult to continuously adapt to new auditing requirements can be solved. The technical effects of improving the semantic recognition accuracy of the violation content, improving the real-time performance of large-scale text auditing, automatically discovering new violation categories, reducing leak detection and enhancing the expansibility and dynamic adaptability of a content auditing system are achieved.