Demo Data from EDBT 2026 / reviewers in the wild / expert
Sheldon Zhu
dblp:332/0580
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
query suggestion |
0.6 | 1 | 2022 | InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis · UIST 2022 |
Information retrieval
search interfaces |
0.6 | 1 | 2022 | InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis · UIST 2022 |
Ubiquitous computing and smart environments › information work
sensemaking support |
0.6 | 1 | 2022 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and SynthesisabstractWeb 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 |
UIST | 3 |