推荐系统数据的交互式可视化

SHCIS '17 Pub Date : 2017-06-19 DOI:10.1145/3099012.3099014
Christian Richthammer, Johannes Sänger, G. Pernul
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引用次数: 8

摘要

推荐系统提供了一种有价值的机制,通过将数据集减少到特定用户可能感兴趣的项目来解决信息过载问题。虽然近年来推荐的质量有了显著提高,但使用的复杂算法导致最终用户的高度不透明。我们建议使用交互式可视化来呈现建议。通过让用户参与信息缩减过程,可以在保持系统透明度的同时提高推荐的质量。这项工作通过分析推荐系统数据并将其与合适的可视化和交互技术相匹配,提供了第一个见解。研究结果通过基于典型现实世界设置的示例场景来说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive Visualization of Recommender Systems Data
Recommender systems provide a valuable mechanism to address the information overload problem by reducing a data set to the items that may be interesting for a particular user. While the quality of recommendations has notably improved in the recent years, the complex algorithms in use lead to high non-transparency for the end user. We propose the usage of interactive visualizations for presenting recommendations. By involving the user in the information reduction process, the quality of recommendations could be enhanced whilst keeping the system's transparency. This work gives first insights by analyzing recommender systems data and matching them to suitable visualization and interaction techniques. The findings are illustrated by means of an example scenario based on a typical real-world setting.
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