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AUSAI
2003
Springer
14 years 4 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
IQ
2007
14 years 10 days ago
Rule-Based Measurement Of Data Quality In Nominal Data
: Sufficiently high data quality is crucial for almost every application. Nonetheless, data quality issues are nearly omnipresent. The reasons for poor quality cannot simply be bla...
Jochen Hipp, Markus Müller, Johannes Hohendor...
DKE
2008
124views more  DKE 2008»
13 years 11 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
14 years 4 months ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
FQAS
2004
Springer
146views Database» more  FQAS 2004»
14 years 2 months ago
Discovering Representative Models in Large Time Series Databases
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Simona E. Rombo, Giorgio Terracina