计算机科学 ›› 2013, Vol. 40 ›› Issue (6): 276-278.
夏利民,赵业东,彭东亮,张伟
XIA Li-min,ZHAO Ye-dong,PENG Dong-liang and ZHANG Wei
摘要: 针对传统推荐系统中存在的冷开始和准确性等问题,提出了一种基于改进URP模型和K近邻的推荐方法。该方法利用改进的URP模型对用户和项目进行建模,可以有效地解决新用户的问题;并通过推荐项目的K近邻对预测等级进行优化,可以显著提高对新项目预测的准确性。实验结果表明,该方法可以有效地解决冷开始问题,并显著提高推荐结果的准确性。
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