计算机工程与科学2018，Vol.40Issue(2)：238-245,8.DOI:10.3969/j.issn.1007-130X.2018.02.007
基于EKSC算法的网络事件热度预测方法
Prediction of network events' hotness based on EKSC algorithm
摘要
Abstract
With the rapid development of the Internet,how to effectively monitor and guide the public opinion on the Internet is of great significance to the social stability.The prediction of network events' hotness is an important part of public opinion supervision.In view of the fact that the traditional method ignores the temporal information and the relevance contained in the event time series in the process of prediction,a prediction model based on EKSC algorithm is proposed.The model uses the EKSC algorithm to cluster the time series of known network public opinion events of each class and construct a class model library.The time sequence of the know hotness in the predicted event is scaled.The least square method is used to predict the event by selecting the model with the minimum mean square error in the class library.Experimental results show that this method can effectively predict the hotness of network events.关键词
网络舆情/EKSC算法/聚类/热度预测Key words
public opinion/EKSC algorithm/clustering/hotness prediction分类
信息技术与安全科学引用本文复制引用
张茂元,孙树园,王奕博,孟琼瑶,王琦..基于EKSC算法的网络事件热度预测方法[J].计算机工程与科学,2018,40(2):238-245,8.基金项目
教育部人文社会科学研究基金(15YJC870029) （15YJC870029）
国家语委科研项目(YB135-40) （YB135-40）
华中师范大学中央高校基本科研业务费(CCNU16A02049,CCNU16A06039) （CCNU16A02049,CCNU16A06039）
