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» Mining evolving data streams for frequent patterns
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AUSAI
2003
Springer
15 years 2 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
ICDM
2007
IEEE
131views Data Mining» more  ICDM 2007»
15 years 4 months ago
Parallel Mining of Frequent Closed Patterns: Harnessing Modern Computer Architectures
Inspired by emerging multi-core computer architectures, in this paper we present MT CLOSED, a multi-threaded algorithm for frequent closed itemset mining (FCIM). To the best of ou...
Claudio Lucchese, Salvatore Orlando, Raffaele Pere...
ICDM
2005
IEEE
157views Data Mining» more  ICDM 2005»
15 years 3 months ago
Blocking Anonymity Threats Raised by Frequent Itemset Mining
In this paper we study when the disclosure of data mining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. The novelty o...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...
KDD
2006
ACM
208views Data Mining» more  KDD 2006»
15 years 10 months ago
Frequent subgraph mining in outerplanar graphs
In recent years there has been an increased interest in frequent pattern discovery in large databases of graph structured objects. While the frequent connected subgraph mining pro...
Tamás Horváth, Jan Ramon, Stefan Wro...
GECCO
2004
Springer
102views Optimization» more  GECCO 2004»
15 years 3 months ago
Dynamic and Scalable Evolutionary Data Mining: An Approach Based on a Self-Adaptive Multiple Expression Mechanism
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
Olfa Nasraoui, Carlos Rojas, Cesar Cardona