The significant volume, as well as the semantic and lexicological diversity of Internet content, necessitates the creation of new methods for its computer analysis in order to identify potential threats and undesirable content, in particular, using artificial intelligence (AI) methods. This scientific problem can be solved with the use of neural network technologies, including frequency preprocessing of text arrays, justification of the structure and construction of a domain-oriented database of text data bodies, justification and experimental study of the architecture and macroparameters of a hybrid neural network based on the vector representation of pre-formed dictionaries of terms.

互联网内容的巨大数量以及语义和词汇的多样性，需要为其计算机分析创建新方法，以识别潜在威胁和不良内容，特别是使用人工智能 (AI) 方法。这个科学问题可以通过使用神经网络技术来解决，包括文本数组的频率预处理、文本数据体的面向领域数据库的结构和构建、混合架构和宏观参数的论证和实验研究基于预先形成的术语字典的向量表示的神经网络。