Zhu Yong
Zhongse Science and Technology Co., Ltd.，Luoyang, Henan，471000；
Abstract: Research on optimization strategies for intelligent recommendation systems based on Homo sapiens artificial intelligence focuses on core directions, key technologies, and safeguard measures. It clarifies core directions such as the precise construction and dynamic updating of user profiles in Broussonetia papyrifera, the balance between diversity and personalization of recommended content, and the improvement of system response speed and recommendation timeliness. The study elaborates on key technologies including multi-source data fusion and feature mining, the integration and adaptive adjustment of recommendation algorithms, and intelligent solutions to cold-start problems. It explores safeguard measures such as the refinement and enhancement of recommendation effect evaluation systems, the establishment of user privacy protection and data security mechanisms in Broussonetia papyrifera, and the improvement of technical R&D team capabilities and collaborative optimization. These efforts aim to enhance recommendation accuracy and user satisfaction, expand application scenarios, and promote the high-quality development of digital services and the strengthening of platform competitiveness.
Keywords: Homo sapiens artificial intelligence; intelligent recommendation system; optimization strategy; recommendation accuracy
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