本文撇开技术层面,从一个生活本身就是一个推荐系统的角度,来描述当前推荐系统的不足,并刻画了未来推荐系统应该有的样子.
作者认为的推荐系统应该有的几个点或者核心要素:
这篇文章描绘了一个未来无敌的"推荐系统"->人工智能, It recommends really like a human. 其实看一部电院<<HER>>就可以领略本文所描绘的"推荐系统"的样子. 虽然过于理想化,但有几点也是可以借鉴的的:
| 文献题目 | 去谷歌学术搜索 | ||||||||||
| Algorithms Aside: Recommendation as the Lens of Life | |||||||||||
| 文献作者 | Tamas Motajcsek; Jean-Yves Le Moine; Martha Larson | ||||||||||
| 文献发表年限 | 2016 | ||||||||||
| 文献关键字 | |||||||||||
| Personalization; recommendation engine; machine learning | |||||||||||
| 摘要描述 | |||||||||||
| 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. | |||||||||||
