PUREsuggest:以引用为基础的文献搜索和以关键字控制的排名进行视觉探索
IEEE transactions on visualization and computer graphics
|September 10, 2024
概括
本研究介绍了PUREsuggest,这是一种使用引用网络和视觉分析进行文献发现的新方法. 它帮助研究人员找到相关论文,建立收藏,并有效地识别专家.
科学领域:
- 图书统计学 图书统计学
- 信息科学 信息科学 信息科学
- 计算机科学 计算机科学
背景情况:
- 引用对于识别相关研究至关重要.
- 现有的方法可能缺乏透明度或以用户为导向的改进.
研究的目的:
- 介绍PUREsuggest,一个用于文学搜索和食的系统.
- 通过引用网络分析,增强文献收藏和专家识别.
主要方法:
- 结合基于引用的建议与引用网络的增强可视化.
- 包含用户定义的关键字来指导搜索相关性.
- 采用互动改进文学建议.
主要成果:
- PUREsuggest提供了透明的,可视化解释的建议文献排名.
- 该系统有助于逐步构建相关出版物集合.
- 用户研究评估了搜索策略和使用模式.
结论:
- PUREsuggest提供了一种有效和交互式的文学发现方法.
- 该系统支持建立,更新和评估文学收藏.
- 它有助于识别研究领域内的相关专家.
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