Models of human information seeking reveal that search, in particular ad-hoc retrieval, is non-linear and iterative. Despite these findings, today’s search user interfaces do not support non-linear navigation, like for example backtracking in time. We propose QueryCrumbs, a compact and easy-to-understand visualization for navigating the search query history supporting iterative query refinement. We apply a multi-layered interface design to support novices and first-time users as well as intermediate and expert users. The visualization is evaluated with novice users in a formative user study, with experts in a think aloud test and its usage in a long-term study with software logging. The formative evaluation showed that the interactions can be easily performed, and the visual encodings were well understood without instructions. Results indicate that QueryCrumbs can support users when searching for information in an iterative manner. The evaluation with experts showed that expert users can gain valuable insights into the back-end search engine by identifying specific patterns in the visualization. In a long-term usage study, we observed an uptake of the visualization, indicating that users deem QueryCrumbs beneficial for their search interactions.

人类信息搜索模型表明，搜索，尤其是临时检索，是非线性的和迭代的。尽管有这些发现，但是当今的搜索用户界面不支持非线性导航，例如及时回溯。我们建议使用QueryCrumbs，这是一种紧凑且易于理解的可视化工具，用于导航搜索查询历史记录，以支持迭代查询优化。我们应用了多层界面设计，以支持新手和初学者以及中级和专业用户。可视化在形成性用户研究中由新手用户评估，由专家进行大声思考测试，并在软件记录的长期研究中用于可视化。形成性评估表明，可以轻松进行交互，并且无需说明即可很好地理解视觉编码。结果表明，当以迭代方式搜索信息时，QueryCrumbs可以支持用户。与专家进行的评估表明，通过识别可视化中的特定模式，专家用户可以获得对后端搜索引擎的宝贵见解。在长期的使用研究中，我们观察到可视化的吸收，表明用户认为QueryCrumbs对其搜索交互有利。