Demo Data from EDBT 2026 / reviewers in the wild / expert
Shalini Sewraz
dblp:51/1645
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1
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.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › search engines
search result clustering |
0.0 | 1 | 2000 | New paradigms in information visualization · SIGIR 2000 |
Visualization and visual analytics › text visualization
document visualization |
0.0 | 1 | 2000 | New paradigms in information visualization · SIGIR 2000 |
Visualization and visual analytics
information visualization |
0.0 | 1 | 2000 | New paradigms in information visualization · SIGIR 2000 |
Information retrieval › interactive information retrieval › exploratory search
query result exploration |
0.0 | 1 | 2000 | New paradigms in information visualization · SIGIR 2000 |
Methods — techniques the papers use, named apart from their topics
clustering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | New paradigms in information visualizationabstractWe present three new visualization front-ends that aid navigation through the set of documents returned by a search engine (hit documents). We cluster the hit documents to visually group these documents and label the groups with related words. The different front-ends cater for different user needs, but all can browse cluster information as well as drilling up or down in one or more clusters and refining the search using one or more of the suggested related keywords. Peter Au, Matthew Carey, Shalini Sewraz, Yike Guo, Stefan M. Rüger |
SIGIR | 3 |