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» SPAMS: A Novel Incremental Approach for Sequential Pattern M...
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ASC
2008
13 years 6 months ago
Dynamic data assigning assessment clustering of streaming data
: Discovering interesting patterns or substructures in data streams is an important challenge in data mining. Clustering algorithms are very often applied to identify single substr...
Olga Georgieva, Frank Klawonn
CIKM
2009
Springer
13 years 10 months ago
Mining data streams with periodically changing distributions
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Yingying Tao, M. Tamer Özsu
KDD
2008
ACM
239views Data Mining» more  KDD 2008»
14 years 7 months ago
Mining adaptively frequent closed unlabeled rooted trees in data streams
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Albert Bifet, Ricard Gavaldà
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
14 years 7 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
IEAAIE
2009
Springer
14 years 1 months ago
An Efficient Algorithm for Maintaining Frequent Closed Itemsets over Data Stream
Data mining refers to the process of revealing unknown and potentially useful information from a large database. Frequent itemsets mining is one of the foundational problems in dat...
Show-Jane Yen, Yue-Shi Lee, Cheng-Wei Wu, Chin-Lin...