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User experience in modern content discovery applications critically depends on high-quality personalized recommendations.
Grouplens: applying collaborative filtering to usenet news
J. A. Konstan, B. N. Miller, D. Maltz, J. L. Herlocker, L. R. Gordon, and J. Riedl · 1997
Earlier work this paper cites.
SALSA: the stochastic approach for link-structure analysis
R. Lempel and S. Moran · 2001
Earlier work this paper cites.
Item-based collaborative filtering recommendation algorithms
B. Sarwar, G. Karypis, J. Konstan, and J. Riedl · 2001
Earlier work this paper cites.
Amazon.com recommendations: Item-to-item collaborative filtering
G. Linden, B. Smith, and J. York · 2003
Earlier work this paper cites.
Towards scaling fully personalized pagerank: Algorithms, lower bounds, and experiments
D. Fogaras, B. Rácz, K. Csalogány, and T. Sarlós · 2005
Earlier work this paper cites.
Fast random walk with restart and its applications
H. Tong, C. Faloutsos, and J. Pan · 2006
Earlier work this paper cites.
The Netflix prize
J. Bennett and S. Lanning · 2007
Earlier work this paper cites.
Google news personalization: scalable online collaborative filtering
A. Das, M. Datar, A. Garg, and S. Rajaram · 2007
Earlier work this paper cites.
Content-based recommendation systems
M. J. Pazzani and D. Billsus · 2007
Earlier work this paper cites.
Video suggestion and discovery for youtube: taking random walks through the view graph
S. Baluja, R. Seth, D. Sivakumar, Y. Jing, J. .Yagnik, S. Kumar, D. Ravichandran, and M. Aly · 2008
Earlier work this paper cites.
Matrix factorization techniques for recommender systems
Y. Koren, R. M. Bell, and C. Volinsky · 2009
Cited alongside, same era.
Fast incremental and personalized pagerank
B. Bahmani, A. Chowdhury, and A. Goel · 2010
Cited alongside, same era.
The youtube video recommendation system
J. Davidson, B. Liebald, J. Liu, P. Nandy, T. V. Vleet, U. Gargi, S. Gupta, Y. He, M. Lambert, B. Livingston, and D. Sampath · 2010
Cited alongside, same era.
Supervised random walks: predicting and recommending links in social networks
L. Backstrom and J. Leskovec · 2011
Cited alongside, same era.
Deep content-based music recommendation
A. V. den Oord, S. Dieleman, and B. Schrauwen · 2013
Cited alongside, same era.
WTF: the who to follow service at twitter
P. Gupta, A. Goel, J. J. Lin, A. Sharma, D. Wang, and R. Zadeh · 2013
Cited alongside, same era.
Personalizing linkedin feed
D. Agarwal, B. Chen, Q. He, Z. Hua, G. Lebanon, Y. Ma, P. Shivaswamy, H. Tseng, J. Yang, and L. Zhang · 2015
Later among the works it cites.
The who-to-follow system at twitter: Strategy, algorithms, and revenue impact
A. Goel, P. Gupta, J. Sirois, D. Wang, A. Sharma, and S. Gurumurthy · 2015
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Wide & deep learning for recommender systems
H. Cheng, L. Koc, J. Harmsen, T. Shaked, T. Chandra, H. Aradhye, G. Anderson, G. Corrado, W. Chai, M. Ispir, et al · 2016
Later among the works it cites.
Deep neural networks for youtube recommendations
P. Covington, J. Adams, and E. Sargin · 2016
Later among the works it cites.
Deep neural networks for youtube recommendations
P. Covington, J. Adams, and E. Sargin · 2016
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SNAP: A general-purpose network analysis and graph-mining library
J. Leskovec and R. Sosic · 2016
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean · 2013
Cited alongside, same era.
A fast parallel sgd for matrix factorization in shared memory systems
Y. Zhuang, W. Chin, Y. Juan, and C. Lin · 2013
Cited alongside, same era.
Decaf: A deep convolutional activation feature for generic visual recognition
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Recommending items to more than a billion people
M. Kabiljo and A. Ilic
Cited in the paper.
Graphjet: Real-time content recommendations at twitter
A. Sharma, J. Jiang, P. Bommannavar, B. Larson, and J. J. Lin · 2016
Later among the works it cites.
Related pins at pinterest: The evolution of a real-world recommender system
D. Liu, S. Rogers, R. Shiau, D. Kislyuk, K. Ma, Z. Zhong, J. Liu, and Y. Jing · 2017
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Joint deep modeling of users and items using reviews for recommendation
L. Zheng, V. Noroozi, , and P. S. Yu · 2017
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