Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jaerheen Yang
dblp:35/5356
· 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
Systems, architecture and hardware · 1Databases, 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 |
Query processing and optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization
join processing |
0.0 | 1 | 1996 | A Parallel Distributive Join Algorithm for Cube-Connected Multiprocessors · IEEE Trans. Parallel Distributed Syst. 1996 |
Query processing and optimization › join processing
parallel join |
0.0 | 1 | 1996 | A Parallel Distributive Join Algorithm for Cube-Connected Multiprocessors · IEEE Trans. Parallel Distributed Syst. 1996 |
Parallel and multicore computing
parallel algorithms |
0.0 | 1 | 1996 | A Parallel Distributive Join Algorithm for Cube-Connected Multiprocessors · IEEE Trans. Parallel Distributed Syst. 1996 |
Methods — techniques the papers use, named apart from their topics
performance analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | A Parallel Distributive Join Algorithm for Cube-Connected MultiprocessorsabstractThis paper presents a parallel distributive join algorithm for cube-connected multiprocessors. The performance analysis shows that the proposed algorithm has an almost linear speedup over the sequential distributive join algorithm as the number of processors increases, and its performance is comparable to that of the parallel hybrid-hash join algorithm. A big advantage of the proposed algorithm over hash-based join algorithms is that it does not have the bucket overflow problem caused by nonuniform hashing of the smaller operand relation. Moreover, the proposed algorithm can easily support the nonequijoin operation, which is very hard to implement by using hash-based join algorithms. Soon Myoung Chung, Jaerheen Yang |
IEEE Trans. Parallel Distributed Syst. | 2 |
| 1993 | Distributive Join Algorithm for Cube-Connected Multiprocessors
Soon Myoung Chung, Jaerheen Yang |
DASFAA | 2 |