探索性搜索的视觉任务表征

Vikram Singh
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引用次数: 0

摘要

人类生活在大数据、高级分析和人类信息交互的时代。“数据”的巨大增长给信息搜寻带来了巨大的挑战。naïve用户采用几种策略(例如,分析搜索、类比搜索等)来聚合知识。增强可视化通过视觉认知支持在用户搜索(即简单的视觉搜索、视觉探索等)中发挥关键作用。虽然用户很难寻找特定的任务或视觉隐喻,因为很少对视觉任务进行评估,但信息可视化在用户搜索中扮演什么角色(如果有的话)尚不清楚。本文采用视觉分类法对主要的可视化工具进行了系统的综述,以了解可视化任务、内在功能和可行性。关键的贡献是跟踪当前的趋势和维度上的进展(例如,视觉成就和视觉含义),并断言注释将提供探索性视觉分析状态、不断发展的框架和工具的愿景。
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Visual Task Characterization for Exploratory Search
Humans are living in the age of big data, advanced analytics, and human information interaction. The tremendous growth of ‘the data' presents enormous challenges to information-seeking. A naïve user adapts several strategies (e.g., analytical search, search by analogy, etc.) to aggregate the knowledge. Augmented visualization plays a pivotal role via visual cognitive support in user searches (i.e., simple visual search, visual exploration, etc.). Though it is hard for a user to look for specific tasks or visual metaphors, as evaluation of visual task is rarely undertaken, it is unclear what role, if any, information visualizations play in the user search. In this paper, a visual taxonomy is adopted to systematically review key visualization tools to understand the visual tasks and inherent functions and viability. The key contribution is to trace the current trends and advancements on the dimensions (i.e., visual accomplishments and visual implications) and to assert that annotations will provide a vision on the state of exploratory visual analytics, evolving frameworks, and tools.
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