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» Mining Association Rules in Hypertext Databases
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ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 25 days 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
ICDE
2008
IEEE
498views Database» more  ICDE 2008»
15 years 7 months ago
Injector: Mining Background Knowledge for Data Anonymization
Existing work on privacy-preserving data publishing cannot satisfactorily prevent an adversary with background knowledge from learning important sensitive information. The main cha...
Tiancheng Li, Ninghui Li
TCS
2008
13 years 7 months ago
Itemset frequency satisfiability: Complexity and axiomatization
Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pai...
Toon Calders
HPCC
2007
Springer
14 years 1 months ago
A Data Imputation Model in Sensor Databases
Data missing is a common problem in database query processing, which can cause bias or lead to inefficient analyses, and this problem happens more often in sensor databases. The re...
Nan Jiang
FQAS
2004
Springer
146views Database» more  FQAS 2004»
13 years 11 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