Research of hybrid collaborative filtering algorithm based on news recommendation

Yao Dong, Shan Liu, Jianping Chai
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引用次数: 10

Abstract

This paper introduced the personalized recommendation technology to the news system. In order to meet the demand of the users' personality and ease the problem of data sparse, the research work proposed the hybrid collaborative filtering algorithm based on news recommendation. It improved correlation coefficient formula by adding news hot parameter when calculating the similarity of users, and then used hybrid recommendation algorithm to forecast users' ratings to make user-rating matrix to non-zero values. Experimental results illustrated that the hybrid recommendation algorithm can effectively increase the accuracy and stability of recommendation so as to achieve better recommendation results.
基于新闻推荐的混合协同过滤算法研究
本文将个性化推荐技术引入新闻系统。为了满足用户个性需求和缓解数据稀疏问题,本研究提出了基于新闻推荐的混合协同过滤算法。在计算用户相似度时,通过增加新闻热点参数对相关系数公式进行改进,然后利用混合推荐算法预测用户评分,使用户评分矩阵趋于非零值。实验结果表明,混合推荐算法可以有效地提高推荐的准确性和稳定性,从而获得较好的推荐效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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