Parallel Association Rule Mining for Medical Applications

Parallel Association Rule Mining for Medical Applications

For real-time applications that consist of massive number of rules, partitioning of the rules to support parallel processing is important. This paper proposes a suite of algorithms called GAPCM for parallel processing of massive number of rules. By considering even distribution, minimal waiting time...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Zhang, G. G., Xu, C. Z., Sheu, P. C-Y, Yamaguchi, H.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Algorithm design and analysis
association rule
Association rules
co-location patterns
Diseases
GAPCM
massive rules
Parallel processing
Partitioning algorithms
Program processors
Real time systems
subnet allocation
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:For real-time applications that consist of massive number of rules, partitioning of the rules to support parallel processing is important. This paper proposes a suite of algorithms called GAPCM for parallel processing of massive number of rules. By considering even distribution, minimal waiting time and minimal inter-processor communication, we propose three algorithms for subnet allocation, and apply these algorithms to association rule mining.
DOI:10.1109/BIBE.2011.31