杨兴耀, 于炯, 吐尔根·依布拉音, 英昌甜, 闫歌. 评分可信度条件下的协同过滤模型[J]. 微电子学与计算机, 2013, 30(10): 25-28.
引用本文: 杨兴耀, 于炯, 吐尔根·依布拉音, 英昌甜, 闫歌. 评分可信度条件下的协同过滤模型[J]. 微电子学与计算机, 2013, 30(10): 25-28.
YANG Xing-yao, YU Jiong, TURGUN Ibrahim, YING Chang-tian, YAN Ge. Collaborative Filtering Models with the Credibility of Ratings[J]. Microelectronics & Computer, 2013, 30(10): 25-28.
Citation: YANG Xing-yao, YU Jiong, TURGUN Ibrahim, YING Chang-tian, YAN Ge. Collaborative Filtering Models with the Credibility of Ratings[J]. Microelectronics & Computer, 2013, 30(10): 25-28.

评分可信度条件下的协同过滤模型

Collaborative Filtering Models with the Credibility of Ratings

  • 摘要: 通过对用户信任度进行量化,再从项目的角度进行调整,最终获得了较为准确的评分可信度度量。在此基础上,建立了评分可信度矩阵,并对提出的四种可信度相似性模型进行了优化。实验比较结果表明,基于不同的数据集,新提出的相似性模型在合理的时间开销下,相对于传统模型在项目预测准确性方面拥有出色的表现。

     

    Abstract: This paper quantifies the degree of user credit and adjusts it by specific items,and then gains accurate quantification on the credibility of ratings.In the case,the paper establishes the credibility matrix of ratings,and proposes four optimized similarity models based on credibility. The comparative experimental results, tested on different data sets,demonstrate that the newly proposed models have better performance in prediction accuracy of items at a reasonable cost in time,compared to traditional models.

     

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