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» Mining spatial association rules in image databases
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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
15 years 5 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
ICFCA
2007
Springer
15 years 3 months ago
A New and Useful Syntactic Restriction on Rule Semantics for Tabular Datasets
Different rule semantics have been successively defined in many contexts such as implications in artificial intelligence, functional dependencies in databases or association rules...
Marie Agier, Jean-Marc Petit
CORR
2010
Springer
219views Education» more  CORR 2010»
14 years 12 months ago
Finding Sequential Patterns from Large Sequence Data
Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mini...
Mahdi Esmaeili, Fazekas Gabor
DMKD
2004
ACM
127views Data Mining» more  DMKD 2004»
15 years 5 months ago
Discovering spatial patterns accurately with effective noise removal
Cluster analysis is a common approach to pattern discovery in spatial databases. While many clustering techniques have been developed, it is still challenging to discover implicit...
Yu Qian, Kang Zhang
SAC
2002
ACM
14 years 11 months ago
The P-tree algebra
The Peano Count Tree (P-tree) is a quadrant-based lossless tree representation of the original spatial data. The idea of P-tree is to recursively divide the entire spatial data, s...
Qin Ding, Maleq Khan, Amalendu Roy, William Perriz...