基于案例推理的物联网个性化推荐系统信息获取与分析技术

Jieli Sun, Yao Zhai, Yanxia Zhao, Jianke Li, Naishi Yan
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引用次数: 2

摘要

本文讨论了基于案例推理(case-based reasoning, CBR)的个性化推荐系统的信息获取与分析理论和信息质量问题。对信息质量获取与分析的关键技术进行了深入研究。结合本文的研究成果,结合基于内容的推荐技术和协同过滤的推荐结果,设计了一种基于cbr的个性化组合推荐算法。
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Information Acquisition and Analysis Technology of Personalized Recommendation System Based on Case-Based Reasoning for Internet of Things
In the paper, we discuss the theories of the information acquisition and analysis and the information quality of the case-based reasoning (CBR) personalized recommendation system. We also take a deep study of the key techniques of acquiring and analyzing information quality. With research results of this paper, combined with the content-based recommendation technology and recommendation results of collaborative filtering, a CBR-based personalized combinatorial recommendation algorithm is designed.
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