推荐系统记法：建议的教学和研究通用记法
Recommender Systems Notation: Proposed Common Notation for Teaching and Research
摘要：
随着推荐系统领域的发展，作者已经使用了无数的符号来描述推荐算法的数学工作。这些符号出现在研究论文、书籍、课堂笔记、博客文章和软件文档中。该领域的学科多样性并没有促进符号的一致性;以信息检索为基础的学者与机器学习或人机交互的学者有不同的习惯和期望。在推荐系统多年的教学和研究过程中，我们已经看到了在我们的工作中采用一致的符号的价值。这一点在我们开发Coursera上的推荐系统MOOC（Konstan et al. 2015）时特别突出，因为我们需要解释各种各样的算法，而我们的学习者不能通过改变算法之间的符号来很好地服务。在本文中，我们描述了我们在工作中采用的符号，以及它的理由和一些考虑的替代品的讨论。我们提出这一点，希望它将是有用的其他人写和教学有关推荐系统。这种符号在研究、在线教育和传统课堂教学中已经很好地服务了我们一段时间。我们认为它可以广泛使用。
英文摘要：
As the field of recommender systems has developed, authors have used a myriad of notations for describing the mathematical workings of recommendation algorithms. These notations ap-pear in research papers, books, lecture notes, blog posts, and software documentation. The dis-ciplinary diversity of the field has not contributed to consistency in notation; scholars whose home base is in information retrieval have different habits and expectations than those in ma-chine learning or human-computer interaction. In the course of years of teaching and research on recommender systems, we have seen the val-ue in adopting a consistent notation across our work. This has been particularly highlighted in our development of the Recommender Systems MOOC on Coursera (Konstan et al. 2015), as we need to explain a wide variety of algorithms and our learners are not well-served by changing notation between algorithms. In this paper, we describe the notation we have adopted in our work, along with its justification and some discussion of considered alternatives. We present this in hope that it will be useful to others writing and teaching about recommender systems. This notation has served us well for some time now, in research, online education, and traditional classroom instruction. We feel it is ready for broad use.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
