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Papers101: Supporting the Discovery Process in the Literature Review Workflow for Novice Researchers

机译：Papers101：支持新手研究人员文献审查工作流程中的发现过程

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摘要

A literature review is a critical task in performing research. However, even browsing an academic database and choosing must-read items can be daunting for novice researchers. In this paper, we introduce Papers101, an interactive system that supports novice researchers’ discovery of papers relevant to their research topics. Prior to system design, we performed a formative study to investigate what difficul-ties novice researchers often face and how experienced researchers address them. We found that novice researchers have difficulty in identifying appropriate search terms, choosing which papers to read first, and ensuring whether they have examined enough candidates. In this work, we identified key requirements for the system dedicated to novices: prioritizing search results, unifying the contexts of multiple search results, and refining and validating the search queries. Accordingly, Papers101 provides an opinionated perspective on selecting important metadata among papers. It also visualizes how the priority among papers is developed along with the users’ knowledge discovery process. Finally, we demonstrate the potential usefulness of our system with the case study on the metadata collection of papers in visualization and HCI community.
机译：文献综述是执行研究的关键任务。但是，即使浏览学术数据库并选择必读物品对于新手研究人员来说也可以令人生畏。在本文中，我们介绍了Papers101，这是一个互动系统，支持新手研究人员发现与他们的研究主题相关的论文。在系统设计之前，我们进行了一种形成性研究，以研究差异的新手研究人员经常面临的差异，研究人员如何解决它们。我们发现新手研究人员难以识别适当的搜索条件，选择首先阅读哪些文件，并确保他们是否已经检查了足够的候选人。在这项工作中，我们确定了专​​用于新手的系统的关键要求：优先考虑搜索结果，统一多个搜索结果的上下文，并炼制和验证搜索查询。因此，论文101在选择论文中选择重要元数据提供了一种自由的视角。它还可视化论文的优先级如何与用户的知识发现过程一起开发。最后，我们展示了我们系统的潜在有用性与可视化和HCI社区中论文的元数据收集的案例研究。

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