Online Video Popularity Regression Prediction Model with Multichannel Dynamic Scheduling Based on User Behavior

Author:

Sibo QIAO1,Shanchen PANG1,Min WANG2,Xue ZHAI1,Feng DAI3

Affiliation:

1. College of Computer Science and Technology, China University of PetroleumQingdao266580China

2. College of Control Science and Engineering, China University of PetroleumQingdao266580China

3. College of Information Science and Engineering, Shandong University of Science and TechnologyQingdao266590China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Applied Mathematics,Electrical and Electronic Engineering

Reference35 articles.

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2. Measurement and analysis of a streaming‐media workload;Chesire M.;The 3rd Conference on USENIX Symposium on Internet Technologies and Systems,2001

3. The tube over time: Characterizing popularity growth of YouTube videos;Figueiredo F.;Forth International Conference on Web Search and Web Data Mining,2011

4. Analyzing the dynamics of online video popularity;Ouyang S.;Journal of China Universities of Posts and Telecommunications,2017

5. Characterizing the life cycle of online news stories using social media reactions;Castillo C.;ACM Conference on Computer Supported Cooperative Work and Social Computing,2014

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