System

A system comprising:

• circuitry configured to:
• acquire behavioral history data associated with an entity from a storage medium, and analyze the behavioral history data by applying a machine learning algorithm including feature extraction and classification to compute interest profile data;
• construct a parameterized instruction sequence based on the interest profile data, and provide the parameterized instruction sequence to a generative neural network model having a transformer-based architecture including a plurality of self-attention layers to generate content data;
• apply a natural language processing algorithm to the generated content data to perform bias detection processing and style normalization processing to produce edited content data;
• apply a summarization algorithm to the edited content data and organize the edited content data based on importance scores;
• and
• transmit the edited content data to a terminal apparatus via a packet-switched network with transmission parameters adjusted based on entity configuration data.

A method performed by circuitry, the method comprising:

• acquiring behavioral history data associated with an entity from a storage medium, the behavioral history data including interaction event records, query records, and content consumption records;
• analyzing the behavioral history data by applying a machine learning algorithm to compute interest profile data identifying one or more interest categories of the entity;
• constructing a parameterized instruction sequence based on the interest profile data, and providing the parameterized instruction sequence to a generative neural network model to cause the generative neural network model to generate content data based on the one or more interest categories;
• and
• applying a natural language processing algorithm to the generated content data to perform neutrality editing processing including bias detection processing and style normalization processing to produce edited content data.