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Yingyi Zhou

dblp:272/8830 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
query suggestion
0.612022
InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis · UIST 2022
Information retrieval
search interfaces
0.612022
InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis · UIST 2022
Ubiquitous computing and smart environments › information work
sensemaking support
0.612022
InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis · UIST 2022

Methods — techniques the papers use, named apart from their topics

human wizard · 1.7between-subjects study · 1.7
YearPublicationVenuePosition
2022 InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis
abstract
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.
Srishti Palani, Yingyi Zhou, Sheldon Zhu, Steven Dow
UIST2