Home Appliance Set Customization via User Portrait and Label Matching
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Solution Overview
Problem
Existing home appliance customization methods only focus on individual appliances and not on entire sets tailored to a user's specific living scenario, resulting in low accuracy and incomprehensive solutions.
Innovation Solution
A method and apparatus for customizing a home appliance set by obtaining user-related information, creating a home appliance set portrait, calculating similarities with a preset label library, modifying appliance features, and combining appliances to create a tailored set that meets user requirements, incorporating budget, function, size, appearance, and brand information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If individual home appliance customization is implemented, then user-specific requirements for single appliances are met, but accuracy for home appliance set customization is low
Solution Approach 1:
The patent merges multiple individual appliance customizations into a unified home appliance set customization. It combines user requirements, living scenario data, and appliance specifications into an integrated optimization model that simultaneously determines the optimal configuration for multiple appliances, ensuring they work together harmoniously rather than in isolation.
Solution Approach 2:
The patent adds new dimensions to the customization process by incorporating living scenario characteristics (such as family structure, housing type, usage habits) as additional optimization dimensions. This transforms the problem from simple appliance parameter selection to a multi-dimensional optimization that considers the entire living context, thereby improving customization accuracy.
2Measurement precision
If comprehensive user information collection is performed, then customization accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the comprehensive customization system into distinct functional modules: user information collection module, living scenario analysis module, appliance configuration optimization module, and recommendation generation module. Each module handles specific tasks independently, making the complex system manageable and maintainable while still achieving comprehensive customization accuracy.
Solution Approach 2:
The patent introduces an intermediary optimization model that mediates between raw user information and final appliance recommendations. This model processes and synthesizes diverse input data (user preferences, living scenarios, appliance specifications) into structured optimization parameters, simplifying the overall system architecture while maintaining high customization accuracy.
Data Source
AI summary
Provided is a processing method for customizing a home appliance set, including: obtaining user related information; creating a home appliance set portrait according to the user related information; calculating a similarity between target label information corresponding to each of types for home appliances to be customized in the home appliance set portrait, and home appliance label information of each of home appliances in a preset home appliance label library, and obtaining from the home appliance label library, according to the similarity, a target home appliance corresponding to each of the types; modifying customizable information of each of target home appliances to obtain target home appliance label information as modified; combining all of the target home appliances to obtain a home appliance set as combined, and outputting each of the target home appliances in the home appliance set and the corresponding target home appliance label information.


