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» Mining Regular Patterns in Data Streams
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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 10 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
KDD
2010
ACM
223views Data Mining» more  KDD 2010»
14 years 1 months ago
Frequent regular itemset mining
Concise representations of frequent itemsets sacrifice readability and direct interpretability by a data analyst of the concise patterns extracted. In this paper, we introduce an...
Salvatore Ruggieri
SIGKDD
2008
125views more  SIGKDD 2008»
13 years 9 months ago
Incremental pattern discovery on streams, graphs and tensors
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
Jimeng Sun
EDBT
2008
ACM
138views Database» more  EDBT 2008»
14 years 10 months ago
Mine your own business, mine others' news!
Major media companies such as The Financial Times, the Wall Street Journal or Reuters generate huge amounts of textual news data on a daily basis. Mining frequent patterns in this...
Boualem Benatallah, Guillaume Raschia, Noureddine ...
ICDM
2008
IEEE
123views Data Mining» more  ICDM 2008»
14 years 4 months ago
Mining Periodic Behavior in Dynamic Social Networks
Social interactions that occur regularly typically correspond to significant yet often infrequent and hard to detect interaction patterns. To identify such regular behavior, we p...
Mayank Lahiri, Tanya Y. Berger-Wolf