MMM: Multi-source Multi-net Micro-video Recommendation with Clustered Hidden Item Representation Learning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

MMM: Multi-source Multi-net Micro-video Recommendation with Clustered Hidden Item Representation Learning

Published:2019-09 Issue:3 Volume:4 Page:240-253
ISSN:2364-1185
Container-title:Data Science and Engineering
language:en
Short-container-title:Data Sci. Eng.

Author:

Ma Jingwei,Wen Jiahui,Zhong Mingyang,Chen Weitong,Li Xue

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computational Mechanics

Link

http://link.springer.com/content/pdf/10.1007/s41019-019-00101-4.pdf

Reference41 articles.

1. Ai Q, Zhang Y, Bi K, Chen X, Croft WB (2017) Learning a hierarchical embedding model for personalized product search. In: SIGIR

2. Bengio Y et al (2009) Learning deep architectures for AI. Foundations and trends® in Machine Learning, Hanover

3. Cao C, Ge H, Lu H, Hu X, Caverlee J (2017) What are you known for?: Learning user topical profiles with implicit and explicit footprints. In: SIGIR

4. Chang S, Han W, Tang J, Qi GJ, Aggarwal CC, Huang TS (2015) Heterogeneous network embedding via deep architectures. In: KDD

5. Chen J, Zhang H, He X, Nie L, Liu W, Chua TS (2017) Attentive collaborative filtering: multimedia recommendation with item-and component-level attention. In: SIGIR

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Broad Recommender System: An Efficient Nonlinear Collaborative Filtering Approach;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-08

2. Multi-scale broad collaborative filtering for personalized recommendation;Knowledge-Based Systems;2023-10

3. A survey of micro-video analysis;Multimedia Tools and Applications;2023-09-20

4. A deep graph convolutional neural network architecture for graph classification;PLOS ONE;2023-03-10

5. Multi-Aggregator Time-Warping Heterogeneous Graph Neural Network for Personalized Micro-Video Recommendation;Proceedings of the 31st ACM International Conference on Information & Knowledge Management;2022-10-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3