Paper Info
Title
Maintenance of Discovered Knowledge: A Case in Multi-Level Association Rules
Abstract
Many knowledge discovery (kdd) systems need to spend substantial amount of effort to search for rulesand patterns within large amount of data. After some natural evolutions, as a consequence of updatesapplied to their databases, these systems must update their previously discovered knowledge to reflect thecurrent state of their databases. The straight forward approach of re-running the discovery process onthe whole updated database to re-discover the rules and patterns is not...
Year
Venue
Keywords
1996
KDD
association rule,knowledge discovery
Field
DocType
Citations 
Data mining,Computer science,Association rule learning,Artificial intelligence,Knowledge base,Machine learning
Conference
35
PageRank 
References 
Authors
3.58
12
3
Name
Order
Citations
PageRank
David Wai-Lok Cheung12469282.09
Vincent T. Y. Ng2504122.85
Benjamin W. Tam3373.95