Demo Data from EDBT 2026 / reviewers in the wild / expert
Piper Armstrong
dblp:241/6279
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 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 |
Data mining · 67% Information retrieval · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › evaluation › evaluation methodology
automatic evaluation |
0.4 | 1 | 2019 | Automatic Evaluation of Local Topic Quality · ACL (1) 2019 |
Data mining › text mining
topic modeling |
0.4 | 1 | 2019 | Automatic Evaluation of Local Topic Quality · ACL (1) 2019 |
Data mining › text mining › topic model
topic quality evaluation |
0.4 | 1 | 2019 | Automatic Evaluation of Local Topic Quality · ACL (1) 2019 |
Methods — techniques the papers use, named apart from their topics
topic coherence metrics · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Automatic Evaluation of Local Topic QualityabstractJeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, Jordan Boyd-Graber, Kevin Seppi. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019. Jeffrey Lund, Piper Armstrong, Wilson Fearn, Stephen Cowley, Courtni Byun, Jordan L. Boyd-Graber, Kevin D. Seppi |
ACL (1) | 2 |