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» Mining evolving data streams for frequent patterns
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81
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PVLDB
2008
107views more  PVLDB 2008»
14 years 9 months ago
Finding relevant patterns in bursty sequences
Sequence data is ubiquitous and finding frequent sequences in a large database is one of the most common problems when analyzing sequence data. Unfortunately many sources of seque...
Alexander Lachmann, Mirek Riedewald
PAKDD
2005
ACM
100views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Pushing Tougher Constraints in Frequent Pattern Mining
In this paper we extend the state-of-art of the constraints that can be pushed in a frequent pattern computation. We introduce a new class of tough constraints, namely Loose Anti-m...
Francesco Bonchi, Claudio Lucchese
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
15 years 10 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
84
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JISE
2008
108views more  JISE 2008»
14 years 9 months ago
Efficient Discovery of Frequent Continuities by Projected Window List Technology
Mining frequent patterns in databases is a fundamental and essential problem in data mining research. A continuity is a kind of causal relationship which describes a definite temp...
Kuo-Yu Huang, Chia-Hui Chang, Kuo-Zui Lin
EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
15 years 3 months ago
Mining Distributed Evolving Data Streams Using Fractal GP Ensembles
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...