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Research of Personalized News Recommendation System Based on Hybrid Collaborative Filtering Algorithm

机译:基于混合协同滤波算法的个性化新闻推荐系统研究

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This paper introduced the personalized recommendation technology to the news system. Especially, 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. By improving correlation coefficient formula via adding news hot parameter when calculating the similarity of users, the hybrid recommendation algorithm is used 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.
机译:本文向新闻系统推出了个性化推荐技术。特别是,为了满足用户个性的需求和缓解数据稀疏的问题,研究工作提出了基于新闻推荐的混合协同滤波算法。通过在计算用户的相似性时通过添加新闻热参数来提高相关系数公式,混合推荐算法用于预测用户的评级使用户额定值矩阵对非零值。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,以实现更好的推荐结果。

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