Demo Data from VLDB 2026 / reviewers in the wild / expert
Yannick Ponte
dblp:222/1194
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
evaluation |
0.3 | 1 | 2018 | IRevalOO: An Object Oriented Framework for Retrieval Evaluation · SIGIR 2018 |
Information retrieval › evaluation › test collection
test collection evaluation |
0.3 | 1 | 2018 | IRevalOO: An Object Oriented Framework for Retrieval Evaluation · SIGIR 2018 |
Information retrieval › evaluation
retrieval effectiveness |
0.1 | 1 | 2018 | IRevalOO: An Object Oriented Framework for Retrieval Evaluation · SIGIR 2018 |
Methods — techniques the papers use, named apart from their topics
object-oriented design · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | IRevalOO: An Object Oriented Framework for Retrieval EvaluationabstractWe propose IRevalOO, a flexible Object Oriented framework that (i) can be used as-is as a replacement of the widely adopted trec\_eval software, and (ii) can be easily extended (or "instantiated'', in framework terminology) to implement different scenarios of test collection based retrieval evaluation. Instances of IRevalOO can provide a usable and convenient alternative to the state-of-the-art software commonly used by different initiatives (TREC, NTCIR, CLEF, FIRE, etc.). Also, those instances can be easily adapted to satisfy future customization needs of researchers, as: implementing and experimenting with new metrics, even based on new notions of relevance; using different formats for system output and "qrels''; and in general visualizing, comparing, and managing retrieval evaluation results. Kevin Roitero, Eddy Maddalena, Yannick Ponte, Stefano Mizzaro |
SIGIR | 3 |