ValueCharts: analyzing linear models expressing preferences and evaluations

G. Carenini, J. Loyd
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引用次数: 70

Abstract

In this paper we propose ValueCharts, a set of visualizations and interactive techniques intended to support decision-makers in inspecting linear models of preferences and evaluation. Linear models are popular decision-making tools for individuals, groups and organizations. In Decision Analysis, they help the decision-maker analyze preferential choices under conflicting objectives. In Economics and the Social Sciences, similar models are devised to rank entities according to an evaluative index of interest. The fundamental goal of building models expressing preferences and evaluations is to help the decision-maker organize all the information relevant to a decision into a structure that can be effectively analyzed. However, as models and their domain of application grow in complexity, model analysis can become a very challenging task. We claim that ValueCharts will make the inspection and application of these models more natural and effective. We support our claim by showing how ValueCharts effectively enable a set of basic tasks that we argue are at the core of analyzing and understanding linear models of preferences and evaluation.
ValueCharts:分析表示偏好和评估的线性模型
在本文中,我们提出了ValueCharts,这是一套可视化和交互式技术,旨在支持决策者检查偏好和评估的线性模型。线性模型是个人、团体和组织普遍使用的决策工具。在决策分析中,它们帮助决策者在目标冲突的情况下分析优先选择。在经济学和社会科学中,设计了类似的模型,根据兴趣的评估指数对实体进行排名。构建表达偏好和评估的模型的基本目标是帮助决策者将与决策相关的所有信息组织到一个可以有效分析的结构中。然而,随着模型及其应用领域的复杂性增长,模型分析可能成为一项非常具有挑战性的任务。我们声称ValueCharts将使这些模型的检验和应用更加自然和有效。我们通过展示ValueCharts如何有效地实现一组基本任务来支持我们的主张,我们认为这些任务是分析和理解偏好和评估的线性模型的核心。
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