抛开算法:作为生活镜头的推荐

Tamas Motajcsek, J. Moine, M. Larson, Daniel Kohlsdorf, A. Lommatzsch, D. Tikk, Omar Alonso, P. Cremonesi, Andrew M. Demetriou, Kristaps Dobrajs, F. Garzotto, A. Göker, F. Hopfgartner, D. Malagoli, T. Nguyen, J. Novak, F. Ricci, M. Scriminaci, M. Tkalcic, Anna Zacchi
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引用次数: 6

摘要

在这篇意见书中,我们采取了将算法放在一边的实验方法,并思考如果推荐人与技术无关,推荐人会是什么样子。通过观察当前推荐系统的一些缺点,并从人类的角度讨论它们的局限性,我们提出了一个问题:如果摆脱了所有的限制,RecSys应该是什么,可以是什么?然后我们转而认为,生活本身就是最好的推荐系统,而人们自己就是查询对象。通过观察生活如何让人们接触到适合他们需求或符合他们偏好的选择,我们希望进一步阐明当前的RecSys可以做得更好的地方。最后,我们来看一下RecSys在未来可能采取的形式。通过制定我们的愿景,超越了通常的考虑和当前的限制,包括商业模式、算法、数据集和评估方法,我们试图得出新的结论,这些结论可能会启发从事RecSys的研究人员社区采取的下一步行动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms Aside: Recommendation As The Lens Of Life
In this position paper, we take the experimental approach of putting algorithms aside, and reflect on what recommenders would be for people if they were not tied to technology. By looking at some of the shortcomings that current recommenders have fallen into and discussing their limitations from a human point of view, we ask the question: if freed from all limitations, what should, and what could, RecSys be? We then turn to the idea that life itself is the best recommender system, and that people themselves are the query. By looking at how life brings people in contact with options that suit their needs or match their preferences, we hope to shed further light on what current RecSys could be doing better. Finally, we look at the forms that RecSys could take in the future. By formulating our vision beyond the reach of usual considerations and current limitations, including business models, algorithms, data sets, and evaluation methodologies, we attempt to arrive at fresh conclusions that may inspire the next steps taken by the community of researchers working on RecSys.
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