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» Parallel Mining of Maximal Frequent Itemsets from Databases
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KDD
2004
ACM
207views Data Mining» more  KDD 2004»
14 years 8 months ago
SPIN: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Jun Huan, Wei Wang 0010, Jan Prins, Jiong Yang
RCIS
2010
13 years 6 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
KDD
2007
ACM
170views Data Mining» more  KDD 2007»
14 years 8 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang
AUSDM
2007
Springer
131views Data Mining» more  AUSDM 2007»
14 years 1 months ago
A Bottom-Up Projection Based Algorithm for Mining High Utility Itemsets
Mining High Utility Itemsets from a transaction database is to find itemsests that have utility above a user-specified threshold. This problem is an extension of Frequent Itemset ...
Alva Erwin, Raj P. Gopalan, N. R. Achuthan
IDEAS
2003
IEEE
106views Database» more  IDEAS 2003»
14 years 26 days ago
Frequent Itemsets Mining for Database Auto-Administration
With the wide development of databases in general and data warehouses in particular, it is important to reduce the tasks that a database administrator must perform manually. The a...
Kamel Aouiche, Jérôme Darmont, Le Gru...