System

A system comprising:

• a communication interface coupled to a packet-switched network;
• and
• circuitry configured to:
• receive structured user attribute information comprising preference data, dimensional measurement data, condition parameters, and temporal condition data from a terminal device via the communication interface;
• execute numerical computation and tabular data processing on catalog information in a storage device to extract candidate item information satisfying the user attribute information, and sort the candidates by a relevance score;
• generate a prompt comprising the user attribute information, the sorted candidate item information, and history information including prior evaluation results, and input the prompt to a generative neural network model to obtain proposal information comprising ranked configurations with item identifiers, combination specifications, and explanatory rationales;
• generate visual content data by inputting an image-generation prompt comprising user attribute information, dimensional measurement data, and item appearance parameters to an image generative neural network model, and apply post-processing comprising resolution scaling and color correction;
• transmit the structured recommendation information and the visual content data to the terminal device, upload the visual content data to an information sharing network, and receive evaluation information and opinion information from the terminal device;
• and
• store the evaluation information and the opinion information as history information for reuse in data filtering and prompt generation.

A method comprising:

• receiving, by circuitry coupled to a packet-switched network, structured user attribute information from a terminal device;
• executing numerical computation and tabular data processing on stored catalog information to extract and sort candidate item information satisfying the user attribute information;
• generating a prompt comprising the user attribute information, the candidate item information, and history information, and inputting the prompt to a generative neural network model to obtain proposal information;
• associating configuration information in the proposal information with the candidate item information to create structured recommendation information, and transmitting the recommendation information to the terminal device;
• and
• receiving evaluation information from the terminal device and storing the evaluation information as history information for reuse in subsequent processing.