空军预警学院学报Issue(1)：54-58,67,6.DOI:10.3969/j.issn.2095-5839.2015.01.014
基于项目属性相似和MapReduce并行化的Slope One算法
Slope One algorithm based on item’s attribute similarity and MapReduce in parallel
摘要
Abstract
Directing at the Slope One algorithm’s drawback that the predicted precision relies on the number of users’ratings to the predicted item, this paper presents an improved Slope One algorithm based on the item’s attribute similarity and MapReduce in parallel. In this proposed algorithm. We firstly compute the attribute similar-ity between the items, and combine it with the Slope One algorithm to improve the prediction precision, and next, implement the parallel algorithm based on MapReduce over the Hadoop platform. Experimental results on the MovieLens data set show that the improved Slope One algorithm is of higher predicted precision, and is more suit-able for large-scale data set, compared with the Slope One algorithm and the weighted Slope One algorithm.关键词
Slope One算法/属性相似度/MapReduce并行化Key words
Slope One algorithm/attribute similarity/MapReduce in parallel分类
信息技术与安全科学引用本文复制引用
胡旭,鲁汉榕,陈新,周国安..基于项目属性相似和MapReduce并行化的Slope One算法[J].空军预警学院学报,2015,(1):54-58,67,6.
