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基于项目分类的个性化推荐算法研究

Research on Personalized Recommendation Algorithm Based on Item Classification

中文摘要英文摘要

为解决个性化推荐的协同过滤算法中出现的稀疏性问题和可扩展性问题,提高推荐质量,在传统协同过滤算法的基础上,引入改进的项目分类算法。在详细阐述算法的基础上,通过实验数据验证该算法的推荐性能。实验结果表明,使用改进后的基于项目分类的协同过滤算法,协同过滤算法的性能有了显著提高,很好地改善了传统算法中出现的稀疏性问题和可扩展问题。

o solve sparsity and scalability issues appearing in the personalized recommendation collaborative filtering algorithm, improve the quality of recommendation, based on the traditional collaborative filtering algorithm, the paper introduced the improved collaborative filtering algorithm based on item classification. Based on the elaboration of algorithm, verify the performance of the proposed algorithm though experimental data. Experimental results show that after using the improved collaborative filtering algorithm based on item classification, the performance of the algorithm is improved significantly, and the sparsity and scalability issues which appearing in traditional algorithms are greatly improved. (10 Points, Times New Roman)

张洪刚、张明坤

计算技术、计算机技术

人工智能个性化推荐协同过滤项目分类

rtificial IntelligencePersonalized RecommendationCollaborative filteringItem Category

张洪刚,张明坤.基于项目分类的个性化推荐算法研究[EB/OL].(2015-12-15)[2025-08-18].http://www.paper.edu.cn/releasepaper/content/201512-783.点此复制

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