Demo Data from EDBT 2026 / reviewers in the wild / expert
C. Y. Wong
dblp:13/3638
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 |
Data mining · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data mining › pattern mining
association rule mining |
0.0 | 1 | 1996 | Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique · ICDE 1996 |
Data mining › incremental mining
incremental updating |
0.0 | 1 | 1996 | Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique · ICDE 1996 |
Methods — techniques the papers use, named apart from their topics
incremental updating technique · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Operation, Management and Performance Issues of LAN Technologies Applied to WAN ArchitectureabstractEmerging technologies, like RPR, POS and GE, are being pushed to replace the traditional SONET/SDH and ATM in WAN. This paper evaluates performance issues of RPR, POS and GE on a testbed, including fault recovery, network stress, QoS and multicast behavior. Unlike other papers, which may have done performance investigations on a theoretical or simulation basis, all results presented in this paper are measured from a physical testbed network. Yew Fai Wong, C. Y. Wong, Lek Heng Ngoh, Lawrence Wai-Choong Wong |
ISCC | 2 |
| 1996 | Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating TechniqueabstractAn incremental updating technique is developed for maintenance of the association rules discovered by database mining. There have been many studies on efficient discovery of association rules in large databases. However, it is nontrivial to maintain such discovered rules in large databases because a database may allow frequent or occasional updates and such updates may not only invalidate some existing strong association rules but also turn some weak rules into strong ones. An incremental updating technique is proposed for efficient maintenance of discovered association rules when new transaction data are added to a transaction database. David Wai-Lok Cheung, Jiawei Han 0001, Vincent T. Y. Ng, C. Y. Wong |
ICDE | 4 |