Title :
The research of hot-event´s heat prediction in microblog platform
Author :
Chuizheng Kong; Chengwei Gu; Mingqing Huang; Xi Wang
Author_Institution :
School of Computer Engineering & Science, Shanghai University, China
Abstract :
With rapid development of microblog, more and more people are going to use microblog to transmit information and express their opinions. Therefore, predicting and monitoring the online hot-event tendency has become a significant support for our national security and development of society. Traditional prediction model tends to have a non-liner and unstable performance in time series. As a result, the accuracy of prediction cannot be guaranteed. To address that problem, this paper proposes an improved regression prediction model which combines the derivative and regression curve, and gets a consequence about heat tendency for hot-event. According to experiment result, the proposed model outperforms LS_SVM model and several other traditional models.
Keywords :
"Predictive models","Market research","Regression analysis","Data models","Mathematical model","Analytical models","Fitting"
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2015 4th International Conference on
DOI :
10.1109/ICCSNT.2015.7490916