标签：整理 学习 nan matrix acm parallel for ems red
导读：深入学习任何一门学科，都离不开对前沿知识的了解。对于推荐系统学习者来说，一年一度的RecSys大会就是了解学术界与工业界研究热点的最佳平台。鉴于此，在这篇文章中，我们把过往的RecSys论文整理成一个清单，列出了大家学习推荐系统必看的10篇RecSys论文。下边这5篇是根据ACM数字图书馆中的阅读量整理出来的。在已发表的925篇论文中，这五篇论文是阅读量最高的。这五篇论文约占所有RecSys会议论文引用的12％！
· Performance of recommender algorithms on top-n recommendation tasks — 2010, by Paolo Cremonesi, Yehuda Koren, Roberto Turrin
· Trust-aware recommender systems — 2007, by Paolo Massa, Paolo Avesani
· A matrix factorization technique with trust propagation for recommendation in social networks — 2010, by Mohsen Jamali, Martin Ester
· Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering — 2010, by Alexandros Karatzoglou, Xavier Amatriain, Linas Baltrunas, Nuria Oliver
· Hidden factors and hidden topics: understanding rating dimensions with review text — 2013, by Julian McAuley, Jure Leskovec
自从2009年以来，每一年的ACM RecSys大会还会为当年作出较大贡献的论文进行颁奖，接下来的5篇论文在近5年内被评为了“最佳论文”。
· Modeling the Assimilation-Contrast Effects in Online Product Rating Systems: Debiasing and Recommendations — 2017, by X. Zhang, J. Zhao, J.C.S. Lui
· Local Item-Item Models for Top-N Recommendation — 2016, by E. Christakopoulou and G. Karypis；
· Context-Aware Event Recommendation in Event-based Social Networks— 2015, by A. Macedo, L. Marinho and R. Santos
· Beyond Clicks: Dwell Time for Personalization — 2014, by X. Yi, L. Hong, E. Zhong, N. Nan Liu and S. Rajan
· A Fast Parallel SGD for Matrix Factorization in Shared Memory Systems— 2013, by Y. Zhuang, W. Chin, Y. Juan and C. Lin (Best Paper)
学习推荐系统必看的10篇RecSys论文，收藏！（官方推荐）
标签：整理 学习 nan matrix acm parallel for ems red
原文地址：https://blog.51cto.com/13945147/2444537
