Assessing Topic Representations for Gist-Forming
Assessing Topic Representations for Gist-Forming
复制标题
评估主题表达以形成要点
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Michael Gleicher
中科院分区：
文献类型：
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作者：
E. Alexander;Michael Gleicher
随着主题建模越来越流行，可视化过程的工具也变得越来越普遍。尽管这些工具支持各种不同的任务，但它们通常都有一个视图或模块来传达单个主题的内容。这些视图支持gist-forming的重要任务：帮助用户建立一个有凝聚力的整体意义上的主题的语义内容，可以概括的特定子集的话，显示。有许多因素会影响这些视图，包括使用的视觉编码，包含的主题词的数量以及主题本身的质量。据我们所知，没有对这些因素可能改变用户解释的方式进行正式评价。在一系列的众包实验中，我们试图比较视觉主题表征的特点，在其适用于gist-forming。我们发现，gist-forming能力是显着抵抗视觉表征的变化，虽然它恶化的主题质量较低。
As topic modeling has grown in popularity, tools for visualizing the process have become increasingly common. Though these tools support a variety of different tasks, they generally have a view or module that conveys the contents of an individual topic. These views support the important task of gist-forming: helping the user build a cohesive overall sense of the topic's semantic content that can be generalized outside the specific subset of words that are shown. There are a number of factors that affect these views, including the visual encoding used, the number of topic words included, and the quality of the topics themselves. To our knowledge, there has been no formal evaluation comparing the ways in which these factors might change users' interpretations. In a series of crowdsourced experiments, we sought to compare features of visual topic representations in their suitability for gist-forming. We found that gist-forming ability is remarkably resistant to changes in visual representation, though it deteriorates with topics of lower quality.