InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis

要旨

Web search is increasingly used to satisfy complex, exploratory information goals. Exploring and synthesizing information into knowledge can be slow and cognitively demanding due to a disconnect between search tools and sense-making workspaces. Our work explores how we might integrate contextual query suggestions within a person's sensemaking environment. We developed InterWeave a prototype that leverages a human wizard to generate contextual search guidance and to place the suggestions within the emergent structure of a searchers’ notes. To investigate how weaving suggestions into the sensemaking workspace affects a user's search and sensemaking behavior, we ran a between-subjects study (n=34) where we compare InterWeave’s in context placement with a conventional list of query suggestions. InterWeave’s approach not only promoted active searching, information gathering and knowledge discovery, but also helped participants keep track of new suggestions and connect newly discovered information to existing knowledge, in comparison to presenting suggestions as a separate list. These results point to directions for future work to interweave contextual and natural search guidance into everyday work.

著者
Srishti Palani
University of California, San Diego, California, United States
Yingyi Zhou
University of California, San Diego , La Jolla , California, United States
Sheldon Zhu
University of California, San Diego, La Jolla, California, United States
Steven P.. Dow
University of California, San Diego, La Jolla, California, United States
論文URL

https://doi.org/10.1145/3526113.3545696

会議: UIST 2022

The ACM Symposium on User Interface Software and Technology

セッション: Search and Exploration

6 件の発表
2022-11-02 23:30:00
2022-11-03 01:00:00