计算机与数字工程2017，Vol.45Issue(11)：2099-2104,6.DOI:10.3969/j.issn.1672-9722.2017.11.005
基于相似度质量的混合协同过滤算法
Hybrid Collaborative Filtering Algorithm Based on Quality of Similarity
郭雷 1张琨 1陈洪雁 1严霞1
作者信息
- 1. 南京理工大学计算机科学与工程学院 南京 210094
- 折叠
摘要
Abstract
In the traditional collaborative filtering algorithm has been facing a cold start and data sparseness and other issues, resulting in the recommendation information is not accurate enough. A new hybrid collaborative filtering algorithm is proposed by an-alyzing the characteristics of user-based collaborative filtering algorithm and item-based collaborative filtering algorithm. This pa-per combines the weighted mean of two similar filtering algorithms with the mean and standard deviation of the similarity,and intro-duces the control factor to improve the precision of the prediction. Experiments are carried out with the Movie Lens dataset,and the average absolute error is used to measure the results. The experimental results show that the proposed algorithm improves the accura-cy of the proposed algorithm when the scoring matrix is extremely sparse.关键词
推荐算法/协同过滤/相似度Key words
recommendation algorithm/collaborative filtering/similarity分类
信息技术与安全科学引用本文复制引用
郭雷,张琨,陈洪雁,严霞..基于相似度质量的混合协同过滤算法[J].计算机与数字工程,2017,45(11):2099-2104,6.
