| 摘要: |
| 本文旨在探讨云计算与人工智能（AI）技术在智能推荐系统中的应用及其效果.研究设计了一种基于深度置信网络（DBN）的智能音乐推荐算法,并利用云计算平台进行计算和数据处理.通过对比实验,评估了本算法与传统推荐算法在准确率、召回率及推荐误差等方面的差异.结果显示,基于DBN的推荐算法在准确率和召回率上均优于传统算法,且在处理大规模音乐数据时,展现出更低的误差率和更高的稳定性.此外,还通过系统载荷测试验证了本算法在处理复杂数据和大量用户请求时的高效性能. |
| 关键词: 云计算 人工智能（AI） 智能推荐系统 个性化 |
| DOI：10.20192/j.cnki.JSHNU(NS).2024.06.006 |
| 分类号:TP18 |
| 基金项目:安徽省高校自然科学研究重点项目（2022AH052939）；安徽省高校科研计划校级哲学社会科学研究重点项目（2022skxm007） |
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| The application of cloud computing and AI technology integration in intelligent recommendation system |
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WANG Ning1,2, CHEN Wei3
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1.Key Laboratory of Life Science and Information Technology of the Ministry of Justice, Anhui Vocational College of Police Officers, Hefei 230031, Anhui, China;2.Information Management Department, Anhui Vocational College of Police Officers, Hefei 230031, Anhui, China;3.School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210003, Jiangsu, China
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| Abstract: |
| The application and effectiveness of cloud computing and artificial intelligence （AI） technology in intelligent recommendation system was explored in this article. An intelligent music recommendation algorithm based on deep belief networks （DBN） was designed and cloud computing platforms were utilized for computation and data processing. Through comparative experiments, a comprehensive evaluation was conducted between the new algorithm and traditional recommendation algorithms in terms of accuracy, recall, and recommendation error. The results showed that the recommendation algorithm based on DBN outperformed traditional algorithms in both accuracy and recall, and exhibited lower error rates and higher stability when processing large-scale music data. In addition, the efficiency of the new algorithm in handling complex data and large number of user requests was also verified through system load testing. |
| Key words: cloud computing artificial intelligence （AI） intelligent recommendation system individuation |
