System

A system comprising:

• circuitry configured to communicate, via a communication interface coupled to a packet-switched network, with a terminal device, the circuitry being further configured to:
• retrieve, from a storage device, historical information comprising distribution history data, attribute data of a target item, and performance data;
• receive, from the terminal device via the communication interface, condition data comprising identification information of the target item, a distribution period, and a budget value;
• perform statistical processing on the historical information to generate evaluation indices comprising at least a click rate, a conversion rate, and a return-on-investment value for respective combinations of time slots and recipient attributes;
• extract, from the evaluation indices, combinations satisfying a predetermined threshold condition;
• generate, based on the extracted combinations and the condition data, a prompt sentence embedding summary information of the evaluation indices and instructing a generative neural network model to generate structured plan data;
• input the prompt sentence to the generative neural network model to acquire the structured plan data;
• perform numerical adjustment processing on the structured plan data so that the structured plan data satisfies a constraint derived from the budget value;
• convert the structured plan data into a displayable format and transmit the displayable format to the terminal device via the communication interface;
• receive, from the terminal device, an approval instruction;
• and
• in response to the approval instruction, register a distribution setting based on the structured plan data with an external distribution processing apparatus via the packet-switched network.

A method performed by circuitry configured to communicate, via a communication interface coupled to a packet-switched network, with a terminal device, the method comprising:

• retrieving, from a storage device, historical information comprising distribution history data, attribute data of a target item, and performance data;
• receiving, from the terminal device via the communication interface, condition data comprising identification information of the target item, a distribution period, and a budget value;
• performing statistical processing on the historical information to generate evaluation indices;
• generating, based on the evaluation indices and the condition data, a prompt sentence for instructing a generative neural network model to generate structured plan data;
• inputting the prompt sentence to the generative neural network model to acquire the structured plan data;
• performing numerical adjustment processing on the structured plan data so that the structured plan data satisfies a constraint derived from the budget value;
• and
• transmitting the structured plan data after the numerical adjustment to the terminal device via the communication interface for presentation on the terminal device.