广东工业大学学报Issue(3)：44-48,61,6.DOI:10.3969/j.issn.1007-7162.2014.03.008
基于大数据集的混合动态协同过滤算法研究
Hybrid Dynamic Collaborative Filtering Algorithm Based on Big Data Sets
摘要
Abstract
Collaborative filtering has been widely used in the recommendation system , but the traditional algorithm has some limitations , such as inability to adapt to the sparsity of user-item rating matrix data sets well, failure to consider the classification of item , users'scores, interest change over time and other factors when calculating the similarity of the items .Regarding these limitations , it proposed a big data set hybrid dynamic collaborative filtering algorithm , based on the traditional collaborative filtering algorithm . When calculating the similarity of items , time decay functions were introduced in the algorithm , which considered both the similarity of items , scores and items classified .The weights of project integrated simi-larity could be adjusted automatically .In the algorithm , some improvements have also been made in simi-larity computing and the selection of the neighboring items .To verify the effectiveness of the algorithm , experiments were done on movie-lens data sets .Experimental results show that the algorithm is better than the traditional recommendation algorithms .关键词
协同过滤/推荐系统/项目分类/时间权重Key words
collaborative filtering/recommendation system/item classification/time weight分类
信息技术与安全科学引用本文复制引用
汪岭,傅秀芬,王晓牡..基于大数据集的混合动态协同过滤算法研究[J].广东工业大学学报,2014,(3):44-48,61,6.基金项目
广东省自然科学基金资助项目 （）
