计算机应用与软件2017，Vol.34Issue(3)：31-37,7.DOI:10.3969/j.issn.1000-386x.2017.03.006
面向微博的PageRank算法的改进与应用
IMPROVEMENT AND APPLICATION OF PAGERANK ALGORITHM FOR MICRO-BLOG
摘要
Abstract
It has been one of the urgent problems of micro-blog mining to identify experts with ability to produce high-quality content and high influence under various fields in social network with massive data, and make targeted advertising recommendation and decision support.In this paper, on the basis of user features and behavior features, the rules of selecting article in micro-blog and interaction calculation formula are determined, and the obsolescence of data and irrelevance of theme have been improved by PageRank algorithm.Finally, the algorithm is implemented respectively in the parallel computing framework of MapReduce and Spark.Experimental results show that the proposed method has high accuracy and great performance under Spark, especially under large-scale dataset scene.关键词
微博/用户影响力/PageRank/Spark/大数据Key words
Micro-blog/User Influence/PageRank/Spark/Big data分类
信息技术与安全科学引用本文复制引用
原野,李晨,田丽华..面向微博的PageRank算法的改进与应用[J].计算机应用与软件,2017,34(3):31-37,7.基金项目
国家自然科学基金项目(61403302). （61403302）
