Research on Nutritional Meal Recommendation System Based on AIGC
This paper proposes a nutrition meal recommendation system based on Artificial Intelligence Generated Content(AIGC),which combines the Qwen large language model and LORA technology for fine-tuning to achieve more accurate nutrition advice and meal recommendations.By constructing a rich knowledge base of nutrition information and recipe data,and utilizing vector databases for efficient retrieval,the system can quickly respond to user queries and provide personalized meal plans.Experimental results demonstrate that the system outperforms traditional methods in recommendation accuracy and user experience.The contribution of this research lies in proposing a new method for nutrition meal recommendations and validating its effectiveness through experiments.
AIGCnutrition meal recommendation systemlarge language modelfine-tuning technologyvector database
国家科技期刊平台
NSTL
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