VLDB 2026 Research / reviewers in the wild / expert
Gregory R. Olsen
dblp:22/3339
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1Theory of computation · 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
2 papers |
Knowledge representation and reasoning · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology |
0.0 | 2 | 1996 | The configuration design ontologies and the VT elevator domain theory · Int. J. Hum. Comput. Stud. 1996 An Ontology for Engineering Mathematics · KR 1994 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology
domain ontology |
0.0 | 1 | 1994 | An Ontology for Engineering Mathematics · KR 1994 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › domain knowledge
domain theory |
0.0 | 1 | 1996 | The configuration design ontologies and the VT elevator domain theory · Int. J. Hum. Comput. Stud. 1996 |
Methods — techniques the papers use, named apart from their topics
ontology engineering · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | The configuration design ontologies and the VT elevator domain theoryabstractIn the VT/Sisyphus experiment, a set of problem solving systems were being built against a common specification of a problem. An important hypothesis was that the specification could be given, in large part, as a common ontology. This article is that ontology. This ontology is different than normal software specification documents in two fundamental ways. First, it is formal and machine readable (i.e. in the KIF/Ontolingua syntax). Second, the descriptions of the input and output of the task to be performed include domain knowledge (i.e. about elevator configuration) that characterize semantic constraints on possible solutions, rather than describing the form (data structure) of the answer. The article includes an overview of the conceptualization, excerpts from the machine-readable Ontolingua source files, and pointers to the complete ontology library available on the Internet. Thomas R. Gruber, Gregory R. Olsen, Jay T. Runkel |
Int. J. Hum. Comput. Stud. | 2 |
| 1994 | An Ontology for Engineering Mathematics
Thomas R. Gruber, Gregory R. Olsen |
KR | 2 |