Demo Data from VLDB 2026 / reviewers in the wild / expert
Nan Decker
dblp:60/3130
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1985
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author
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 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Information extraction and text analysis › discourse analysis
discourse processing |
0.0 | 1 | 1985 | The Use of Syntactic Clues in Discourse Processing · ACL 1985 |
Methods — techniques the papers use, named apart from their topics
syntactic parsing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1985 | The Use of Syntactic Clues in Discourse ProcessingabstractThe desirability of a syntactic parsing component in natural language understanding systems has been the subject of debate for the past several years.This paper describes an approach to automarie text processing which is entirely based on syntactic form.A program is described which processes one genre of discourse, that of newspaper reports.The program creates summaries of reports by relying on an expanded concept of text grounding: certain syntactic structures and tense/ aspect oairs indicate the most important events in a news story.Supportive, background material is also highly coded syntactically.Certain types of information are routinely expressed with distinct syntactic forms.Where more than one episode occurs in a single report, a change of episode will also be marked syntactically in a reliable way. Nan Decker |
ACL | 1 |