Demo Data from SIGIR 2026 / reviewers in the wild / expert
Chu-Hui Lin
dblp:126/4819
· DBLP profile ↗
1ranked-venue papers
1as 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 · 1 · 1 first-authorSystems, architecture and hardware · 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.
| Theoretical computer science
1 paper |
Automated reasoning and model checking · 56% Mathematical optimization · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Automated reasoning and model checking
petri net analysis |
0.0 | 1 | 1996 | Petri net based dynamic scheduling of an elevator system · ICRA 1996 |
Mathematical optimization
scheduling |
0.0 | 1 | 1996 | Petri net based dynamic scheduling of an elevator system · ICRA 1996 |
Automated reasoning and model checking
reachability |
0.0 | 1 | 1996 | Petri net based dynamic scheduling of an elevator system · ICRA 1996 |
Methods — techniques the papers use, named apart from their topics
timed place petri-net · 0.0a* search · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Petri net based dynamic scheduling of an elevator systemabstractIn this paper, a hybrid model of a multiple elevator system is proposed, consisting of a timed place Petri net (TPPN) model and a set of control rules implemented via the so-called control places in the TPPN model. The Petri net model is a highly modulized structure, whose constituent modules can be classified into three types: basic movement module, loading/unloading module, and direction reversing module. The whole complete model is a combination of the copies of the above three modules. Since the firing sequences of the TPPN equate the evolution of the modeled system, they can be regarded as a schedule. A heuristic search algorithm, A* search, is thus used on the reachability graph of the TPPN model to obtain the desirable schedule. To show the feasibility of the proposed method, an emulator of the elevator system is constructed for demonstration. The experiment result for a 15-floor building with four elevators is shown to be satisfactory. Chu-Hui Lin, Li-Chen Fu |
ICRA | 1 |