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» New Parallel Algorithms for Frequent Itemset Mining in Very ...
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FIMI
2004
161views Data Mining» more  FIMI 2004»
13 years 8 months ago
ABS: Adaptive Borders Search of frequent itemsets
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
Frédéric Flouvat, Fabien De Marchi, ...
AUSAI
2003
Springer
14 years 19 days 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
CINQ
2004
Springer
119views Database» more  CINQ 2004»
14 years 24 days ago
How to Quickly Find a Witness
The subfield of itemset mining is essentially a collection of algorithms. Whenever a new type of constraint is discovered, a specialized algorithm is proposed to handle it. All o...
Daniel Kifer, Johannes Gehrke, Cristian Bucila, Wa...
SIGMOD
2010
ACM
260views Database» more  SIGMOD 2010»
14 years 6 days ago
Towards proximity pattern mining in large graphs
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
Arijit Khan, Xifeng Yan, Kun-Lung Wu
ADBIS
1998
Springer
118views Database» more  ADBIS 1998»
13 years 11 months ago
Itemset Materializing for Fast Mining of Association Rules
Mining association rules is an important data mining problem. Association rules are usually mined repeatedly in different parts of a database. Current algorithms for mining associa...
Marek Wojciechowski, Maciej Zakrzewicz