Contagion: Optimizing foodborne outbreak analysis with automatic suggestions

Dan Guo
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Abstract

Contagion is a web-based foodborne outbreak analysis tool that suggests users the most pertinent views of their data. Contagion is a proposed solution to the case when there are many ways to filter, view, and analyze a given data set and there are distinct segments of the population interested in the data set for different reasons. Contagion is unique for its ability to learn analysis patterns of previous users to suggest popular views for new users. It tailors the data viewing and analysis experience to each user. More broadly, Contagion looks at the human-computer interface and seeks to delineate which aspects of user interface design can be automated. It takes a data-driven approach to suggest views for users, reducing the influence of the user interface designer. Contagion lays the groundwork for future user interfaces to be learned, decoupling the designer from the design decisions.
传染:优化食源性爆发分析与自动建议
传染病是一个基于网络的食源性疾病爆发分析工具,建议用户对他们的数据最相关的观点。当有许多方法可以过滤、查看和分析给定的数据集,并且有不同的人群出于不同的原因对数据集感兴趣时,传染是针对这种情况提出的解决方案。Contagion的独特之处在于它能够学习以前用户的分析模式,从而为新用户提供流行的观点。它为每个用户量身定制数据查看和分析体验。更广泛地说,Contagion着眼于人机界面,并试图描述用户界面设计的哪些方面可以自动化。它采用数据驱动的方法为用户建议视图,减少了用户界面设计人员的影响。传染为未来的用户界面学习奠定了基础,将设计师与设计决策分离开来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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