Demo Data from EDBT 2026 / reviewers in the wild / expert
Shachar Seidman
dblp:136/9154
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
—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.
| Artificial intelligence
1 paper |
Information extraction and text analysis · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Information extraction and text analysis › text mining › authorship analysis
authorship attribution |
0.2 | 1 | 2013 | Automatically Identifying Pseudepigraphic Texts · EMNLP 2013 |
Natural language and speech › Information extraction and text analysis › text mining › authorship analysis
authorship verification |
0.2 | 1 | 2013 | Automatically Identifying Pseudepigraphic Texts · EMNLP 2013 |
Natural language and speech › Information extraction and text analysis › text mining
text anomaly detection |
0.2 | 1 | 2013 | Automatically Identifying Pseudepigraphic Texts · EMNLP 2013 |
Methods — techniques the papers use, named apart from their topics
unsupervised learning · 0.2document similarity · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | Automatically Identifying Pseudepigraphic TextsabstractThe identification of pseudepigraphic textstexts not written by the authors to which they are attributedhas important historical, forensic and commercial applications.We introduce an unsupervised technique for identifying pseudepigrapha.The idea is to identify textual outliers in a corpus based on the pairwise similarities of all documents in the corpus.The crucial point is that document similarity not be measured in any of the standard ways but rather be based on the output of a recently introduced algorithm for authorship verification.The proposed method strongly outperforms existing techniques in systematic experiments on a blog corpus. Moshe Koppel, Shachar Seidman |
EMNLP | 2 |