Most cited papers from Netflix (United States)

Netflix (United States)

What are the most cited papers from Netflix (United States)?

The most cited paper from Netflix (United States) is "The Netflix Recommender System" (Carlos Alberto Gomez-Uribe, Neil T. Hunt, 2015), with 1,400 citations. Next come "Variational Autoencoders for Collaborative Filtering" (1,345) and "A buffer-based approach to rate adaptation" (1,015).

Published TypeFieldAccessCitations

Showing 50 of 60 papers. Every paper with more than 61 citations is listed.

Most cited papers, sortable by citations and release date
#	Paper
1	The Netflix Recommender System Carlos Alberto Gomez-Uribe, Neil T. Hunt · ACM Transactions on Management Information Systems	28 Dec 2015	1,400
2	Variational Autoencoders for Collaborative Filtering Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman et al. Conference paperOpen access	2018	1,345
3	A buffer-based approach to rate adaptation Te-Yuan Huang, Ramesh Johari, Nick McKeown et al. Conference paperOpen access	12 Aug 2014	1,015
4	MLlib: Machine Learning in Apache Spark Xiangrui Meng, Joseph K. Bradley, Burak Yavuz et al. · arXiv (Cornell University) PreprintOpen access	26 May 2015	960
5	Session-based Recommendations with Recurrent Neural Networks Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas et al. · arXiv (Cornell University) PreprintOpen access	21 Nov 2015	558
6	A survey of collaborative filtering based social recommender systems Xiwang Yang, Yang Guo, Yong Liu et al. · Computer Communications	17 Jul 2013	476
7	An Overview of Core Coding Tools in the AV1 Video Codec Yue Chen et al. Conference paper	Jun 2018	374
8	KDD Cup and workshop 2007 James Risdon Bennett, Charles Elkan, Bing Liu et al. · ACM SIGKDD Explorations Newsletter	Dec 2007	343
9	MCL-JCV: A JND-based H.264/AVC video quality assessment dataset Haiqiang Wang, Weihao Gan, Sudeng Hu et al. Conference paper	17 Aug 2016	329
10	Calibrated recommendations Harald Steck Conference paperOpen access	27 Sep 2018	297
11	Chaos Engineering Ali Basiri, Niosha Behnam, Ruud de Rooij et al. · IEEE Software Open access	18 Mar 2016	282
12	Embarrassingly Shallow Autoencoders for Sparse Data Harald Steck Conference paperOpen access	13 May 2019	273
13	Evaluation of recommendations Harald Steck Conference paperOpen access	12 Oct 2013	259
14	Factorization Meets the Item Embedding Dawen Liang, Jaan Altosaar, Laurent Charlin et al. Conference paper	Sep 2016	252
15	Evaluating Computer Intrusion Detection Systems Aleksandar Milenkoski, Marco Paulo Amorim Vieira, Samuel Kounev et al. · ACM Computing Surveys	29 Sep 2015	197
16	Study of Temporal Effects on Subjective Video Quality of Experience Christos G. Bampis, Zhi Li, Anush Krishna Moorthy et al. · IEEE Transactions on Image Processing	20 Jul 2017	192
17	VideoSet: A large-scale compressed video quality dataset based on JND measurement Haiqiang Wang, Ioannis X. Katsavounidis, Jiantong Zhou et al. · Journal of Visual Communication and Image Representation Open access	28 Apr 2017	181
18	Cross-Modal and Hierarchical Modeling of Video and Text Bowen Zhang, Hexiang Hu, Fei Sha · Lecture notes in computer science Conference paper	2018	179
19	Ghost Ads: Improving the Economics of Measuring Online Ad Effectiveness Garrett A. Johnson, Randall Aaron Lewis, Elmar Nubbemeyer · Journal of Marketing Research	7 Mar 2017	173
20	Deep learning for recommender systems: A Netflix case study Harald Steck, Linas Baltrunas, Ehtsham Elahi et al. · AI Magazine Open access	Sep 2021	167
21	Internet of things: Survey on security Diego Mendez Mena, Ioannis Papapanagiotou, Baijian Yang · Information Security Journal A Global Perspective Open access	4 Apr 2018	165
22	Top Challenges from the first Practical Online Controlled Experiments Summit Somit Gupta et al. · ACM SIGKDD Explorations Newsletter	13 May 2019	144
23	Video Content Marketing: The Making of Clips Xuan Liu, Savannah Wei Shi, Thales S. Teixeira et al. · Journal of Marketing	12 Apr 2018	143
24	Retrospective Encoders for Video Summarization Ke Zhang, Kristen Grauman, Fei Sha · Lecture notes in computer science Conference paper	2018	140
25	Causal Inference for Recommender Systems Zhaoran Wang, Dawen Liang, Laurent Charlin et al. Conference paper	19 Sep 2020	139
26	Large Language Models as Zero-Shot Conversational Recommenders Zhankui He, Zhouhang Xie, Rahul Jha et al. Conference paperOpen access	21 Oct 2023	135
27	Alarms about structural alerts Vinícius M. Alves, Eugene N. Muratov, Stephen J. Capuzzi et al. · Green Chemistry Open access	2016	135
28	Is Cosine-Similarity of Embeddings Really About Similarity? Harald Steck, Chaitanya Ekanadham, Nathan Kallus Conference paperOpen access	12 May 2024	134
29	Mining large streams of user data for personalized recommendations Xavier Amatriain · ACM SIGKDD Explorations Newsletter	30 Apr 2013	129
30	A Survey of Delay-Based and Hybrid TCP Congestion Control Algorithms Rasool Al-Saadi, Grenville J. Armitage, Jason But et al. · IEEE Communications Surveys & Tutorials	2019	122
31	Kepler-78 and the Ultra-Short-Period planets Joshua N. Winn, Roberto Sanchis-Ojeda, S. Rappaport · New Astronomy Reviews Open access	Nov 2018	120
32	The Featureless Transmission Spectra of Two Super-puff Planets Jessica E. Libby-Roberts, Zachory K. Berta-Thompson, Jean-Michel Désert et al. · The Astronomical Journal Open access	20 Jan 2020	115
33	Complexity-based consistent-quality encoding in the cloud Jan De Cock, Zhi Li, Megha Manohara et al. Conference paper	17 Aug 2016	115
34	Recommender Systems in Industry: A Netflix Case Study Xavier Amatriain, Justin Basilico Book chapter	2015	111
35	NeRF-Art: Text-Driven Neural Radiance Fields Stylization Can Wang, Ruixiang Jiang, Menglei Chai et al. · IEEE Transactions on Visualization and Computer Graphics	6 Jun 2023	104
36	Improving the Sensitivity of Online Controlled Experiments Huizhi Xie, Juliette Aurisset Conference paperOpen access	8 Aug 2016	94
37	Better Malware Ground Truth Alex Kantchelian, Michael Carl Tschantz, Sadia Afroz et al. Conference paperOpen access	6 Oct 2015	93
38	The flame graph Brendan Gregg · Communications of the ACM	23 May 2016	91
39	The Top 10 Adages in Continuous Deployment Chris Parnin, Eric Helms, Chris Atlee et al. · IEEE Software	May 2017	88
40	Artwork personalization at netflix Fernando Amat, Ashok Chandrashekar, Tony Jebara et al. Conference paper	27 Sep 2018	84
41	Deep Learning for Radio-Based Human Sensing: Recent Advances and Future Directions Isura Nirmal, Abdelwahed Khamis, Mahbub Hassan et al. · IEEE Communications Surveys & Tutorials Open access	2021	83
42	Lick Observatory Supernova Search follow-up program: photometry data release of 93 Type Ia supernovae Benjamin E. Stahl et al. · Monthly Notices of the Royal Astronomical Society Open access	Oct 2019	83
43	Recurrent and Dynamic Models for Predicting Streaming Video Quality of Experience Christos G. Bampis, Li Zhi, Ioannis X. Katsavounidis et al. · IEEE Transactions on Image Processing	14 Mar 2018	83
44	Big & personal Xavier Amatriain Conference paper	30 Jul 2013	81
45	When Less Is More: Data and Power in Advertising Experiments Garrett A. Johnson, Randall Aaron Lewis, David Reiley · Marketing Science	26 Jul 2016	79
46	Fairness among New Items in Cold Start Recommender Systems Ziwei Zhu, Jingu Kim, Trung Nguyen et al. Conference paperOpen access	11 Jul 2021	77
47	An Overview of Coding Tools in AV1: the First Video Codec from the Alliance for Open Media Yue Chen et al. · APSIPA Transactions on Signal and Information Processing Open access	2020	77
48	Reviewer Integration and Performance Measurement for Malware Detection Brad Miller, Alex Kantchelian, Michael Carl Tschantz et al. · Lecture notes in computer science Conference paper	2016	77
49	Monitoring Temporal Homogeneity in Attributed Network Streams Bahareh Azarnoush, Kamran Paynabar, Jennifer Bekki et al. · Journal of Quality Technology	2016	73
50	Experimental design and analysis of JND test on coded image/video Joe Yuchieh Lin, Lina Jin, Sudeng Hu et al. · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Conference paper	22 Sep 2015	73

Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for an institution when any of its authors gave it as an affiliation; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.