Active and Passive Utility of Search Interface Features in Different Information Seeking Task Stages

Abstract

Models of information seeking, including Kuhlthau's InformationSearch Process model, describe fundamentally different macro-level stages. Current search systems usually do not provide support for these stages, but provide a static set of features predominantly focused on supporting micro-level search interactions. This paper investigates the utility of search user interface (SUI) features at different macro-level stages of complex tasks. A user study was designed, using simulated work tasks, to explicitly place users within different stages of a complex task: pre-focus, focus, and post-focus. Active use, passive use and perceived usefulness of features were analysed in order to derive when search features are most useful. Our results identify significant differences in the utility of SUI features between each stage. Specifically, we have observed that informational features are naturally useful in every stage, while input, control features decline in usefulness after the pre-focus stage, and personalisable features become more useful after the pre-focus stage. From these findings, we conclude that features less commonly found in web search interfaces can provide value for users, without cluttering simple searches, when provided at the right times.

Domain‐independent search expertise: Gaining knowledge in query formulation through guided practice

“…Typical support for access includes clickable facets and filters (Hienert & Mutschke, 2016) or advanced search menus (Hearst, 2009). Although such structures generally receive little active use during search (Hearst, 2009), searchers may use these passively by obtaining information in the interface without clicking (Huurdeman, Wilson, & Kamps, 2016;Wilson & Schraefel, 2008). Kules and Capra (2012) found that searchers who received information about the use of structure were more likely to visually scan facet lists than were those with no instruction.…”

“…Kules and Capra (2012) found that searchers who received information about the use of structure were more likely to visually scan facet lists than were those with no instruction. Vocabulary support is found in the form of structured query suggestions (Diriye, Kumaran, & Huang, 2012;Huurdeman et al, 2016). Dynamic suggestion typically takes the form of natural language, but may also expose a vocabulary space; for example, the Sowiport system displays associated terms and syndetic facet structure within dynamic suggestions (Hienert, Sawitzki, & Mayr, 2015).…”

Personalization in text information retrieval: A survey

“…Stage of task. Task stage has been found to affect query term selection (Vakkari, 2000;Vakkari, 2001;Vakkari & Hakala, 2000), relevance judgment criteria (Taylor et al, 2007;Vakkari, 2000;Vakkari, 2001;Vakkari & Hakala, 2000), the use of IRF and ERF by users in search (White et al, 2005), document dwell time , and utility of search interface features (Huurdeman, Wilson, & Kamps, 2016). Kelly's (1963) construct theory, Taylor's (1968) four levels of information need along the different stages of search, and Kuhlthau's (1991) ISP (Information Seeking Process) model are all classic theses about task stage.…”

“…Kelly's (1963) construct theory, Taylor's (1968) four levels of information need along the different stages of search, and Kuhlthau's (1991) ISP (Information Seeking Process) model are all classic theses about task stage. Task stage has been found to affect query term selection (Vakkari, 2000;Vakkari, 2001;Vakkari & Hakala, 2000), relevance judgment criteria (Taylor et al, 2007;Vakkari, 2000;Vakkari, 2001;Vakkari & Hakala, 2000), the use of IRF and ERF by users in search (White et al, 2005), document dwell time , and utility of search interface features (Huurdeman, Wilson, & Kamps, 2016). Task types along other dimensions.…”

Retrieval Interfaces for Supporting Exploratory Searches

“…The browsing of facets in an image retrieval system allowed image seekers to learn more about the collection (Yee, Swearingen, Li, & Hearst, 2003). Developing search user interface that supports different macro-level stages of complexity, exploratory search tasks, Huurdeman, Wilson, and Kamps (2016) used keyword search textbox and a complementary of input features such as filter using categories, keywords suggestion. This feature reduced the usage of textbox but increased the number of terms per query, suggesting that exploratory activities of the search tasks have improved the understanding of the domain and hence generates more terms when refining the search.…”