Demo Data from SIGIR 2026 / reviewers in the wild / expert
Frank Ponsaert
dblp:05/2853
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1986
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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 |
Knowledge representation and reasoning · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning › representation language › knowledge representation formalisms › knowledge representation language
logic-based knowledge representation |
0.0 | 1 | 1986 | A knowledge representation language for requirements engineering · Proc. IEEE 1986 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › semantic representation
semantic networks |
0.0 | 1 | 1986 | A knowledge representation language for requirements engineering · Proc. IEEE 1986 |
Methods — techniques the papers use, named apart from their topics
logic-based representation · 0.0semantic networks · 0.0semantic network · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1986 | A knowledge representation language for requirements engineeringabstractRequirements engineering, the phase of software development where the users' needs are investigated, is more and more shifting its concern from the target system towards its environment. A new generation of languages is needed to support the definition of application domain knowledge and the behavior of the universe around the computer. This paper assesses the applicability of classical knowledge representation techniques to this purpose. Requirements engineers insist, however, more on natural representation, whereas expert systems designers insist on efficient automatic use of the knowledge. Given this priority of expressiveness, two candidates emerge: the semantic networks and the techniques based on logic. They are combined in a language called the ERAE model, which is illustrated on examples, and compared to other requirements engineering languages. Eric Dubois 0001, Jacques Hagelstein, Eugene Lahou, Frank Ponsaert, André Rifaut |
Proc. IEEE | 4 |