research-article

Personalized Video Recommendation through Graph Propagation

Authors:

Tao MeiAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 10, Issue 4

Article No.: 32, Pages 1 - 17

https://doi.org/10.1145/2598779

Published: 04 July 2014 Publication History

Abstract

The rapid growth of the number of videos on the Internet provides enormous potential for users to find content of interest. However, the vast quantity of videos also turns the finding process into a difficult task. In this article, we address the problem of providing personalized video recommendation for users. Rather than only exploring the user-video bipartite graph that is formulated using click information, we first combine the clicks and queries information to build a tripartite graph. In the tripartite graph, the query nodes act as bridges to connect user nodes and video nodes. Then, to further enrich the connections between users and videos, three subgraphs between the same kinds of nodes are added to the tripartite graph by exploring content-based information (video tags and textual queries). We propose an iterative propagation algorithm over the enhanced graph to compute the preference information of each user. Experiments conducted on a dataset with 1,369 users, 8,765 queries, and 17,712 videos collected from a commercial video search engine demonstrate the effectiveness of the proposed method.

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Cited By

Liu JShang LSu YNie WWen XLiu A(2024)Privacy-preserving Multi-source Cross-domain Recommendation Based on Knowledge GraphACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363970620:5(1-18)Online publication date: 5-Jan-2024
https://dl.acm.org/doi/10.1145/3639706
Wu JGuan YMao QCui YGuo ZZhang XSchulzrinne HKohler EMaltz DMisra V(2023)ZGaming: Zero-Latency 3D Cloud Gaming by Image PredictionProceedings of the ACM SIGCOMM 2023 Conference10.1145/3603269.3604819(710-723)Online publication date: 10-Sep-2023
https://dl.acm.org/doi/10.1145/3603269.3604819
Yuan JChen SZhang YShi ZGeng XFan JRui Y(2023)Graph Attention Transformer Network for Multi-label Image ClassificationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357851819:4(1-16)Online publication date: 27-Feb-2023
https://dl.acm.org/doi/10.1145/3578518
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Index Terms

Personalized Video Recommendation through Graph Propagation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
2. Information systems
  1. World Wide Web
    1. Web applications
    2. Web services

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 10, Issue 4

June 2014

132 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/2656131

Issue’s Table of Contents

Copyright © 2014 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 July 2014

Accepted: 01 February 2014

Revised: 01 February 2014

Received: 01 June 2013

Published in TOMM Volume 10, Issue 4

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Cited By

Liu JShang LSu YNie WWen XLiu A(2024)Privacy-preserving Multi-source Cross-domain Recommendation Based on Knowledge GraphACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363970620:5(1-18)Online publication date: 5-Jan-2024
https://dl.acm.org/doi/10.1145/3639706
Wu JGuan YMao QCui YGuo ZZhang XSchulzrinne HKohler EMaltz DMisra V(2023)ZGaming: Zero-Latency 3D Cloud Gaming by Image PredictionProceedings of the ACM SIGCOMM 2023 Conference10.1145/3603269.3604819(710-723)Online publication date: 10-Sep-2023
https://dl.acm.org/doi/10.1145/3603269.3604819
Yuan JChen SZhang YShi ZGeng XFan JRui Y(2023)Graph Attention Transformer Network for Multi-label Image ClassificationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/357851819:4(1-16)Online publication date: 27-Feb-2023
https://dl.acm.org/doi/10.1145/3578518
Cai DQian SFang QHu JDing WXu C(2023)Heterogeneous Graph Contrastive Learning Network for Personalized Micro-Video RecommendationIEEE Transactions on Multimedia10.1109/TMM.2022.315102625(2761-2773)Online publication date: 2023
https://doi.org/10.1109/TMM.2022.3151026
Asha DHemalatha R(2023)Early Diagnosis of Rheumatoid Arthritis of the Wrist Using Power Doppler Ultrasound: A ReviewIntelligent Systems and Machine Learning10.1007/978-3-031-35078-8_27(320-333)Online publication date: 10-Jul-2023
https://doi.org/10.1007/978-3-031-35078-8_27
Tiotsop LMizdos TBarkowsky MPocta PServetti AMasala E(2022)Mimicking Individual Media Quality Perception with Neural Network based Artificial ObserversACM Transactions on Multimedia Computing, Communications, and Applications10.1145/346439318:1(1-25)Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1145/3464393
Cai DQian SFang QXu C(2022)Heterogeneous Hierarchical Feature Aggregation Network for Personalized Micro-Video RecommendationIEEE Transactions on Multimedia10.1109/TMM.2021.305950824(805-818)Online publication date: 2022
https://doi.org/10.1109/TMM.2021.3059508
Wang YHan LQian QXia JLi J(2022)Personalized Recommendation via Multi-dimensional Meta-paths Temporal Graph Probabilistic SpreadingInformation Processing and Management: an International Journal10.1016/j.ipm.2021.10278759:1Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1016/j.ipm.2021.102787
Sang LXu MQian SMartin MLi PWu X(2021)Context-Dependent Propagating-Based Video Recommendation in Multimodal Heterogeneous Information NetworksIEEE Transactions on Multimedia10.1109/TMM.2020.300733023(2019-2032)Online publication date: 2021
https://doi.org/10.1109/TMM.2020.3007330
Toyoda AOgawa THaseyama M(2018)Favorite Video Estimation Based on Multiview Feature Integration via KMvLFDAIEEE Access10.1109/ACCESS.2018.28761626(63833-63842)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2876162
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