Demo Data from EDBT 2026 / reviewers in the wild / expert
Eric Mackie
dblp:41/5493
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1993
—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 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › document retrieval › structured document retrieval
hypertext retrieval |
0.0 | 1 | 1993 | Coherent Answers for a Large Structured Document Collection · SIGIR 1993 |
Information retrieval
retrieval models |
0.0 | 1 | 1993 | Coherent Answers for a Large Structured Document Collection · SIGIR 1993 |
Information retrieval › document retrieval
structured document retrieval |
0.0 | 1 | 1993 | Coherent Answers for a Large Structured Document Collection · SIGIR 1993 |
Information retrieval › document processing › document analysis
document structure |
0.0 | 1 | 1993 | Coherent Answers for a Large Structured Document Collection · SIGIR 1993 |
Methods — techniques the papers use, named apart from their topics
node similarity · 0.0document structure exploitation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1993 | Coherent Answers for a Large Structured Document CollectionabstractThere is a simple method for integrating information retrieval and hypertext. This consists of treating nodes as isolated documents and retrieving them in order of similarity. If the nodes are structured, in particular, if sets of nodes collectively constitute documents, we can do better. This paper shows how the formation of the hypertext, the retrieval of nodes in response to content based queries, and the presentation of the nodes can be achieved in a way that exploits the knowledge encoded as the structure of the documents. The ideas are then exemplified in an SGML based hypertext information retrieval system. Michael Fuller, Eric Mackie, Ron Sacks-Davis, Ross Wilkinson |
SIGIR | 2 |