一种改进的隐私保持协同过滤推荐算法

采用随机扰乱技术的协同过滤推荐算法会降低推荐精度，基于此，提出扰乱强度权重的概念及其度量方法，给出一种改进的基于随机扰乱技术的隐私保持协同过滤推荐算法。该算法依据推荐用户的扰乱强度计算相应的扰乱强度权重，相似度的计算综合考虑用户评分相似度和扰乱强度权重两方面因素。实验表明，改进后的算法在不影响隐私保护效果的前提下，提高了推荐精度。

Improved Privacy-preserving Collaborative Filtering Recommendation Algorithm

To solve the accuracy decreasing problem of the recommendation algorithm using Randomized Perturbation Techniques（RPT）,the concept of perturbation intensity weight,its measurement and an improved method for similarity calculation are introduced in this paper.An improved privacy preserving collaborative filtering recommendation algorithm is also proposed.The algorithm calculates each recommender’s perturbation intensity weight according to its perturbation intensity.Both users’ rating similarity and perturbation intensity weight are considered when similarity is calculated.Experimental results show that the improved algorithm outperforms the initial one in accuracy without affecting the effectiveness of privacy protection.