Optimization method for home decoration design description specialization fusing semi-structure RAG technology

CN121144359AInactive Publication Date: 2025-12-16NANTONG UNIV
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Patent Information

Application Number
CN202511245066.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-02
Publication Date
2025-12-16
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing AI-assisted home decoration design tools struggle to transform users' vague and emotional needs into professional, high-quality design texts. The generated content lacks professional depth and practicality, and the design solutions may have aesthetic or practical flaws. Furthermore, professional design has a high barrier to entry.

Method used

We construct a semi-structured home decoration design knowledge base and utilize Retrieval Enhanced Generation (RAG) technology to transform user needs into prompts that are professional, logical, and rich in detail. We then generate professional design description text through a large language model, thereby lowering the barrier to entry for users to provide professional descriptions.

Benefits of technology

It transforms vague requirements into professional, logically clear, and detailed design texts, increasing the professional knowledge density of the generated content, lowering the design threshold, and enabling ordinary users to generate high-quality design solutions.

✦ Generated by Eureka AI based on patent content.

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Abstract

The invention discloses a home decoration design description specialization optimization method fusing a semi-structure RAG technology, and belongs to the technical field of artificial intelligence and home decoration design crossing. The method comprises the following steps: constructing a semi-structured home decoration design knowledge base, cooperatively processing an original corpus through a script and AI, generating a structured JSON knowledge unit, and performing vectorization storage; receiving natural language query of a user, performing intention recognition and vectorization, and recalling related knowledge units by adopting a mixed retrieval strategy in combination with semantic retrieval and metadata filtering; and dynamically constructing an enhanced cue word through an RAG technology, and inputting the enhanced cue word into the large language model to generate a professional and detailed home decoration design description text. According to the method, the problems that the content generated by the existing AI design tool is lack of specialty and the user demand conversion is inaccurate are effectively solved, the quality and the practicability of the design text are improved, and the use threshold of professional design is reduced.
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Citation Information

Cited By

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