While an academic conference, RecSys attracts many practitioners and industry researchers, with industry attendance making up the majority of attendees,[2] this is also reflected in the authorship of research papers.[3] Many works published at the conference have direct impact on recommendation and personalization practice in industry[4][5][6] affecting millions of users.
Recommender systems are pervasive in online systems, the conference provides opportunities for researchers and practitioners to address specific problems in various workshops in conjunction with the conference, topics include responsible recommendation,[7] causal reasoning,[8] and others. The workshop themes follow recent developments in the broader machine learning and human-computer interaction topics.
The conference is the host of the ACM RecSys Challenge, a yearly competition in the spirit of the Netflix Prize focussing on a specific recommendation problem. The Challenge has been organized by companies such as Twitter,[9] and Spotify.[10] Participation in the challenge is open to everyone and participation in it has become a means of showcasing ones skills in recommendations,[11][12] similar to Kaggle competitions.
The Netflix Prize was a recommendation challenge organized by Netflix between 2006 and 2009. Shortly prior to ACM RecSys 2009, the winners of the Netflix Prize were announced.[13][14] At the 2009 conference, members of the winning team (Bellkor's Pragmatich Chaos) as well as representatives from Netflix convened in a panel on the lessons learnt from the Netflix Prize[15]
ByteDance Paper, 2022edit
In 2022, at one of the workshops at the conference, a paper from ByteDance,[16] the company behind TikTok, described in detail how a recommendation algorithm for video worked. While the paper did not point out the algorithm as the one that generates TikTok's recommendations, the paper received significant attention in technology-focused media[17][18][19][20]
^Liu, Zhuoran; Zou, Leqi; Zou, Xuan; Wang, Caihua; Zhang, Biao; Tang, Da; Zhu, Bolin; Zhu, Yijie; Wu, Peng; Wang, Ke; Cheng, Youlong (2022). "Monolith: Real Time Recommendation System With Collisionless Embedding Table". arXiv:2209.07663 [cs.IR].
^"#2 How TikTok Real Time Recommendation algorithm scales to billions?". Retrieved 2023-02-13.
^"Computer Science Researchers at Bytedance Developed Monolith: a Collisionless Optimised Embedding Table for Deep Learning-Based Real-Time Recommendations in a Memory-Efficient Way". Retrieved 2023-02-13.
^"Paper Review Monolith: Towards Better Recommendation Systems". Retrieved 2023-02-13.
^"CHINA'S BYTEDANCE INTROS DIFFERENT APPROACH TO RECOMMENDATION AT SCALE". Retrieved 2023-02-13.
External linksedit
Official website
This article about a computer conference is a stub. You can help Wikipedia by expanding it.
conference, recommender, systems, recsys, peer, reviewed, academic, conference, series, about, recommender, systems, sponsored, association, computing, machinery, this, conference, series, focuses, issues, such, algorithms, machine, learning, human, computer, . ACM Conference on Recommender Systems ACM RecSys is a peer reviewed academic conference series about recommender systems Sponsored by the Association for Computing Machinery This conference series focuses on issues such as algorithms machine learning human computer interaction and data science from a multi disciplinary perspective The conference community includes computer scientists statisticians social scientists psychologists and others ACM Conference on Recommender SystemsAbbreviationRecSysDisciplineRecommender SystemsPublication detailsPublisherACMHistory2007 presentFrequencyAnnualThe conference is sponsored by Big Tech companies such as Amazon Netflix Meta Nvidia Microsoft Google and Spotify and large foundations such as the NSF 1 While an academic conference RecSys attracts many practitioners and industry researchers with industry attendance making up the majority of attendees 2 this is also reflected in the authorship of research papers 3 Many works published at the conference have direct impact on recommendation and personalization practice in industry 4 5 6 affecting millions of users Recommender systems are pervasive in online systems the conference provides opportunities for researchers and practitioners to address specific problems in various workshops in conjunction with the conference topics include responsible recommendation 7 causal reasoning 8 and others The workshop themes follow recent developments in the broader machine learning and human computer interaction topics The conference is the host of the ACM RecSys Challenge a yearly competition in the spirit of the Netflix Prize focussing on a specific recommendation problem The Challenge has been organized by companies such as Twitter 9 and Spotify 10 Participation in the challenge is open to everyone and participation in it has become a means of showcasing ones skills in recommendations 11 12 similar to Kaggle competitions Contents 1 Notable Events 1 1 Netflix Prize 2009 1 2 ByteDance Paper 2022 2 List of conferences 3 References 4 External linksNotable Events editNetflix Prize 2009 edit The Netflix Prize was a recommendation challenge organized by Netflix between 2006 and 2009 Shortly prior to ACM RecSys 2009 the winners of the Netflix Prize were announced 13 14 At the 2009 conference members of the winning team Bellkor s Pragmatich Chaos as well as representatives from Netflix convened in a panel on the lessons learnt from the Netflix Prize 15 ByteDance Paper 2022 edit In 2022 at one of the workshops at the conference a paper from ByteDance 16 the company behind TikTok described in detail how a recommendation algorithm for video worked While the paper did not point out the algorithm as the one that generates TikTok s recommendations the paper received significant attention in technology focused media 17 18 19 20 List of conferences editPast and future RecSys conferences include Year Location Date General Chairs Link2024 Bari Italy October 14 18 Pasquale Lops Tommaso Di Noia Website2023 Singapore September 18 22 Jie Zhang Li Chen Shlomo Berkovsky Website2022 Seattle WA USA and online September 18 23 Jen Golbeck Max Harper Vanessa Murdock Website2021 Amsterdam the Netherlands and online September 27 October 1 Martha Larson Martijn Willemsen Humberto Corona Website2020 Online September 22 26 Leandro Balby Marinho Rodrygo Santos Website2019 Copenhagen Denmark September 16 20 Toine Bogers Alan Said Website2018 Vancouver Canada October 2 7 Sole Pera Michael Ekstrand Website2017 Cernobbio Italy August 27 31 Paolo Cremonesi Francesco Ricci Website2016 Boston MA USA September 15 19 Werner Geyer Shilad Sen Website2015 Vienna Austria September 16 20 Hannes Werthner de Markus Zanker Website2014 Foster City CA USA October 6 10 Alfred Kobsa Michelle Zhou Website2013 Hong Kong China October 12 16 Irwin King Qiang Yang Qing Li Website2012 Dublin Ireland September 9 13 Padraig Cunningham Neil Hurley Website2011 Chicago IL USA October 23 27 Bamshad Mobasher Robin Burke Website2010 Barcelona Spain September 26 30 Xavier Amatriain Marc Torrens Website2009 New York NY USA October 11 15 Lawrence Bergman Alexander Tuzhilin Website2008 Lausanne Switzerland October 23 25 Pearl Pu Website2007 Minneapolis MN USA September 19 20 Joe Konstan WebsiteReferences edit ACM RecSys 2022 Sponsorship Retrieved 2022 09 08 RecSys 2020 Welcome Session YouTube Retrieved 2022 09 26 TD Bank creates AI powered Spotify playlist to win contest Retrieved 2022 09 26 Wie entwickelt das ZDF Empfehlungsalgorithmen in German Retrieved 2022 09 26 Die8nhs diakrish ereynhtikhs omadas toy ELMEPA sto diagwnismo plhroforikhs toy RecSys in Greek Retrieved 2022 09 26 Reverse Engineering The YouTube Algorithm Part II Retrieved 2022 09 26 The People Trying to Make Internet Recommendations Less Toxic Retrieved 2022 09 27 New workshop to help bring causal reasoning to recommendation systems RecSys Challenge 2021 Retrieved 2022 09 08 RecSys Challenge 2018 Retrieved 2022 09 08 Inside TD s AI play How Layer 6 s technology hopes to improve old fashioned banking advice The Globe and Mail Retrieved 2022 09 27 TD s Layer 6 wins Spotify RecSys Challenge 2018 Retrieved 2023 02 13 BellKor s Pragmatic Chaos Wins 1 Million Netflix Prize by Mere Minutes Retrieved 2023 02 13 How the Netflix Prize Was Won Retrieved 2023 02 13 RecSys 2009 Program Retrieved 2023 02 13 Liu Zhuoran Zou Leqi Zou Xuan Wang Caihua Zhang Biao Tang Da Zhu Bolin Zhu Yijie Wu Peng Wang Ke Cheng Youlong 2022 Monolith Real Time Recommendation System With Collisionless Embedding Table arXiv 2209 07663 cs IR 2 How TikTok Real Time Recommendation algorithm scales to billions Retrieved 2023 02 13 Computer Science Researchers at Bytedance Developed Monolith a Collisionless Optimised Embedding Table for Deep Learning Based Real Time Recommendations in a Memory Efficient Way Retrieved 2023 02 13 Paper Review Monolith Towards Better Recommendation Systems Retrieved 2023 02 13 CHINA S BYTEDANCE INTROS DIFFERENT APPROACH TO RECOMMENDATION AT SCALE Retrieved 2023 02 13 External links editOfficial website This article about a computer conference is a stub You can help Wikipedia by expanding it vte Retrieved from https en wikipedia org w index php title ACM Conference on Recommender Systems amp oldid 1186452573, wikipedia, wiki, book, books, library,
