QueryCrumbs: A Compact Visualization for Navigating the Search Query History

Abstract

Models of human information seeking reveal that search, in particular ad-hoc retrieval, is non-linear and iterative. Despite these findings, todays search user interfaces do not support non-linear navigation, like for example backtracking in time. In this work, 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 firsttime users as well as intermediate users. The formative evaluation with first-time and intermediate users 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.

QueryCrumbs for Experts: A Compact Visual Query Support System to Facilitate Insights into Search Engine Internals

“…We envision the integration of QueryCrumbs into digital library interfaces as an additional supportive tool to guide expert users in the exploration and assessment of search results. The implementation is publicly available 3 and due to its search engine agnostic nature, QueryCrumbs are easily integrable to existing search interfaces. 3 https://github.com/EEXCESS/QueryCrumbs…”

“…The implementation is publicly available 3 and due to its search engine agnostic nature, QueryCrumbs are easily integrable to existing search interfaces. 3 https://github.com/EEXCESS/QueryCrumbs…”

“…In this section, we repeat the relevant parts of the original QueryCrumbs concept for the paper to be self-contained and present the according extensions towards QueryCrumbs for Experts. For a detailed discussion of the concept and its underlying human querying model, we refer the reader to [3]. Conceptually, QueryCrumbs for Experts visualizes the most recent path through the general querying graph, i.e., the user's history of search queries, supporting the 4 user tasks:…”

“…In previous work, we presented QueryCrumbs, a compact, interactive visualization for accessing, altering and re-submitting previously issued queries [3]. In this paper, we extend the QueryCrumbs approach with a qualitative comparison, allowing search experts to gain insights about search engine internals 1 The concept is depicted in Fig.…”

Impact and development of an Open Web Index for open web search

“…Search paradigms could include conversational search (Anand et al, 2020), (temporal) argumentation search (Potthast et al, 2019), and human-centric search (search over private and public data collections). Similarly, new user interfaces could explore more datacentric visualization paradigms (Höfler et al, 2014) or new query navigation techniques (Seifert et al, 2017).…”