VLDB 2026 Research / reviewers in the wild / expert
Teun Kortekaas
dblp:424/7990
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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 |
Spatial and temporal data management · 67% Indexing and storage engines · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Indexing and storage engines
multidimensional indexing |
0.9 | 1 | 2025 | MS-Index: Fast Top-k Subsequence Search for Multivariate Time Series under Euclidean Distance · Proc. VLDB Endow. 2025 |
Spatial and temporal data management › time series data management
subsequence matching |
0.9 | 1 | 2025 | MS-Index: Fast Top-k Subsequence Search for Multivariate Time Series under Euclidean Distance · Proc. VLDB Endow. 2025 |
Spatial and temporal data management
time series data management |
0.9 | 1 | 2025 | MS-Index: Fast Top-k Subsequence Search for Multivariate Time Series under Euclidean Distance · Proc. VLDB Endow. 2025 |
Methods — techniques the papers use, named apart from their topics
indexing · 0.9euclidean distance · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | MS-Index: Fast Top-k Subsequence Search for Multivariate Time Series under Euclidean Distance
Jens E. d'Hondt, Teun Kortekaas, Odysseas Papapetrou, Themis Palpanas |
Proc. VLDB Endow. | 2 |