RecSys是ACM主辦的推薦系統(tǒng)旗艦會(huì)議，其征文范疇包含推薦系統(tǒng)的各個(gè)領(lǐng)域，包括算法設(shè)計(jì)、系統(tǒng)實(shí)現(xiàn)、理論推導(dǎo)和評(píng)估測(cè)試等。
每年RecSys都會(huì)舉辦推薦系統(tǒng)相關(guān)的比賽，本文將對(duì)歷年RecSys比賽進(jìn)行匯總。
RecSys 2010 Challenge
http://2010.recsyschallenge.com/
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比賽名稱：Challenge on Context-aware Movie Recommendation
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比賽任務(wù)：The Challenge on Context-aware Movie Recommendation focuses on identifying contextual features in datasets and generating context-aware movie recommendations.
RecSys 2011 Challenge
http://2011.recsyschallenge.com/
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比賽名稱：Challenge on Context-aware Movie Recommendation
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比賽任務(wù)：This challenge aims to tackle the practical issue of context-aware movie recommendation. A new movie rating dataset from Moviepilot will be released for the challenge.
RecSys 2012 Challenge
http://2012.recsyschallenge.com/
- 比賽名稱：Recommender Systems Challenge
CAMRa track
CAMRa track at RecSysChallenge focuses on context-aware recommendation of movie-related news from moviepilot.com.
ScienceRec track
ScienceRec track focuses on recommendations to users about scientific papers that they might be interested in, using a data set that comes from the Mendeley system.
RecSys 2014 Challenge
http://2014.recsyschallenge.com/
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比賽名稱：User Engagement as Evaluation
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比賽任務(wù)：In this challenge, we intend to use a different means of evaluating recommendations. Instead on focusing on predictive qualities, our intention is to optimize recommendations on user engagement.
RecSys 2016 Challenge
http://2016.recsyschallenge.com/
- 比賽任務(wù)：given a XING user, the goal is to predict those job postings that a user will positively interact with (e.g. click, bookmark).
RecSys 2017 Challenge
https://www.recsyschallenge.com/2017/
- 比賽任務(wù)：The ACM RecSys Challenge 2017 is focussing on the problem of job recommendations on XING in a cold-start scenario.
RecSys 2018 Challenge
https://www.recsyschallenge.com/2018/
- 比賽任務(wù)：This year’s challenge focuses on music recommendation, specifically the challenge of automatic playlist continuation.
RecSys 2019 Challenge
https://www.recsyschallenge.com/2019/
- 比賽任務(wù)：This year’s challenge focuses on travel metasearch. The goal of this challenge is to develop a session-based and context-aware recommender system using various input data to provide a list of accommodations that will match the needs of the user.
RecSys 2020 Challenge
https://www.recsyschallenge.com/2020/
- 比賽任務(wù)：The challenge focuses on a real-world task of tweet engagement prediction in a dynamic environment. The goal is to predict the probability for different types of engagement.
RecSys 2021 Challenge
https://www.recsyschallenge.com/2021/
- 比賽任務(wù)：This year's challenge brings the problem even closer to Twitter's real recommender systems by introducing latency constraints. We will also increase the data size to encourage novel methods.
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