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FLAIRS
2007
13 years 11 months ago
Mining Sequences in Distributed Sensors Data for Energy Production
The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
Mehmed M. Kantardzic, John Gant
ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 1 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
BMCBI
2007
154views more  BMCBI 2007»
13 years 8 months ago
PepBank - a database of peptides based on sequence text mining and public peptide data sources
Background: Peptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequence...
Timur Shtatland, Daniel Guettler, Misha Kossodo, M...
PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
14 years 2 months ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 9 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici