Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/124339
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Interpreting video recommendation mechanisms by mining view count traces
Author: Zhou, Y.
Wu, J.
Chan, T.H.
Ho, S.W.
Chiu, D.M.
Wu, D.
Citation: IEEE Transactions on Multimedia, 2018; 20(8):2153-2165
Publisher: IEEE
Issue Date: 2018
ISSN: 1520-9210
1941-0077
Statement of
Responsibility: 
Yipeng Zhou, Jiqiang Wu, Terence H. Chan, Siu-Wai Ho, Dah-Ming Chiu and Di Wu
Abstract: All large-scale online video systems, for example, Netflix and Youku, make a significant investment on video recommendations that can dramatically affect video information diffusion processes among users. However, there is a lack of efficient methodology to interpret how various recommendation mechanisms affect information diffusion processes resulting in the difficulty to evaluate video recommendation efficiency. In this paper, we propose to quantify and explain video recommendation mechanisms by using epidemic models to mine video view count traces. It is well known that an epidemic model is an efficient approach to model information diffusion processes; while view count traces can be viewed as the results of video information diffusion driven by video recommendations. Thus, we propose a framework based on extended epidemic models to quantify and interpret two recommendation mechanisms, that is, direct and word-of-mouth (WOM) recommendations, by fitting video view count traces collected from Tencent Video, a large-scale online video system in China. Our approach is a novel methodology to evaluate video recommendation mechanisms, and a new perspective to interpret how recommendation mechanisms drive view count evolution.
Keywords: Video information diffusion; word-of-mouth recommendation; direct recommendation
Rights: © 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
DOI: 10.1109/TMM.2017.2781364
Grant ID: http://purl.org/au-research/grants/arc/DE180100950
http://purl.org/au-research/grants/arc/DP150103658
Appears in Collections:Aurora harvest 8
Electrical and Electronic Engineering publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.