计算机应用与软件2018，Vol.35Issue(2)：48-53,6.DOI:10.3969/j.issn.1000-386x.2018.02.008
深度置信网络的Spark并行化在微博情感分类中的应用研究
RESEARCH ON SPARK PARALLELIZATION OF DEEP CONFIDENCE NETWORK IN MICROBLOGGING EMOTION CLASSIFICATION
摘要
Abstract
Chinese micro blog sentiment analysis can be found that the public's attitude toward hot events and grasp the network public opinion,thus become a hot research in the text mining.This paper put forwards the parallelization of deep belief networks for Chinese micro blog sentiment analysis by Spark.Firstly,the Word2Vec tool was used to express the microblogging text and the establishment of the emotional dictionary.Then,the microblogging emotion classification model was constructed by using the deep confidence network.Finally,the neural network of the deep confidence neural network was processed by the Spark cluster.The experimental results showed that the microblogging emotion classification model based on deep confidence network was parallelized under the Spark platform, and the training time was shortened,and the accuracy of emotion classification was 5% higher than that of the traditional shallow learning method.关键词
中文微博/情感分析/深度置信网络/Spark并行化Key words
Chinese micro blog/Sentiment analysis/Deep belief networks/Spark parallelization分类
信息技术与安全科学引用本文复制引用
张翔,石力,尚勃,董丽丽..深度置信网络的Spark并行化在微博情感分类中的应用研究[J].计算机应用与软件,2018,35(2):48-53,6.基金项目
国家自然科学基金项目(51278400) （51278400）
陕西省自然科学基础研究基金项目(2016JM6031). （2016JM6031）
