Recommender Systems for Self-Actualization
Recommender Systems for Self-Actualization
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DOI：
10.1145/2959100.2959189
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
Bart P. Knijnenburg;S. Sivakumar;Daricia Wilkinson
中科院分区：
文献类型：
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作者：
Bart P. Knijnenburg;S. Sivakumar;Daricia Wilkinson
每天，我们都会面临大量的决定，需要我们从看似无穷无尽的选择中进行选择。推荐系统本应帮助我们处理这项艰巨的任务，但一些学者声称这些系统反而将我们置于“过滤泡沫”中，严重限制了我们的视角。本文提出了推荐系统研究的新方向，其主要目标是支持用户开发、探索和理解他们独特的个人偏好。
Every day, we are confronted with an abundance of decisions that require us to choose from a seemingly endless number of choice options. Recommender systems are supposed to help us deal with this formidable task, but some scholars claim that these systems instead put us inside a "Filter Bubble" that severely limits our perspectives. This paper presents a new direction for recommender systems research with the main goal of supporting users in developing, exploring, and understanding their unique personal preferences.