基于神经网络的单波峰期互联网事件关注度预测

Shang He, Yuzi Wang, Yue Wang, Qingjie Zhang, Yuejin Zhang, Tianmei Wang
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引用次数: 1

摘要

通过对一个网络事件的观察,我们发现其关注程度在多个波峰中发展。提出了一种基于BP神经网络的波峰趋势预测的基本模型。仿真实验表明,在可以估计网络事件最大关注度的前提下,该模型可以预测网络事件的单峰趋势。我们的工作可以作为社会或商业工作者根据民意做出决策的辅助工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Network Based Attention Degree Prediction for Internet Incidents in One-Crest Period
Observing an Internet incident, we find that its attention degrees develop in multiple wave crests. We propose a basic model to predict the trend of one wave crest based on back propagation (BP) neural network. Simulation experiments show that our model can predict one-crest trend of an Internet incident under the assumption that its maximum attention degree can be estimated. Our work can serve as an auxiliary tool for social or commercial workers to make decisions based on public opinions.
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