Exploring Visualization Challenges for Interactive Recommender Systems
Exploring Visualization Challenges for Interactive Recommender Systems
复制标题
探索交互式推荐系统的可视化挑战
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
D. Kammer
中科院分区：
文献类型：
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作者：
Mandy Keck;D. Kammer
用户在大型、复杂的数据集合中面临着日益严重的信息过载问题。推荐系统通过向用户提供建议将数据集减少到可管理的大小。过去几年的研究主要集中在底层算法的质量上。最近的研究开始关注推荐系统中的用户体验。主要挑战是透明度、可控性、可探索性和情境感知。交互式可视化有可能解决所有这些问题。在本文中，我们提出了针对不同使用场景的三种用户界面概念：电影、活动和旅行搜索。我们提出了用户界面构建块的分类法，以评估这些与可视化挑战相关的概念。
Users are faced with an increasing information overload problem in large, complex data collections. Recommender systems reduce the data set to a manageable size by providing suggestions to the user. Research in the last years has primarily focused on the quality of the underlying algorithms. Recent research started to focus on the user experience in recommender systems. The main challenges are transparency, controllability, explorability, and context-awareness. Interactive visualizations have the potential to address all of these issues. In this paper, we present three user interface concepts for different usage scenarios: movie, activities, and travel search. We propose a taxonomy of user interface building blocks to evaluate these concepts with regards to the visualization challenges.