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KDD
2008
ACM
239views Data Mining» more  KDD 2008»
14 years 6 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
AUSDM
2008
Springer
235views Data Mining» more  AUSDM 2008»
13 years 7 months ago
ShrFP-Tree: An Efficient Tree Structure for Mining Share-Frequent Patterns
Share-frequent pattern mining discovers more useful and realistic knowledge from database compared to the traditional frequent pattern mining by considering the non-binary frequen...
Chowdhury Farhan Ahmed, Syed Khairuzzaman Tanbeer,...
AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
13 years 12 months ago
Discovering Frequent Sets from Data Streams with CPU Constraint
Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...
ICDM
2006
IEEE
114views Data Mining» more  ICDM 2006»
13 years 12 months ago
Incremental Mining of Frequent Query Patterns from XML Queries for Caching
Existing studies for mining frequent XML query patterns mainly introduce a straightforward candidate generate-and-test strategy and compute frequencies of candidate query patterns...
Guoliang Li, Jianhua Feng, Jianyong Wang, Yong Zha...
ICDM
2006
IEEE
227views Data Mining» more  ICDM 2006»
13 years 12 months ago
Incremental Mining of Sequential Patterns over a Stream Sliding Window
Incremental mining of sequential patterns from data streams is one of the most challenging problems in mining data streams. However, previous work of mining sequential patterns fr...
Chin-Chuan Ho, Hua-Fu Li, Fang-Fei Kuo, Suh-Yin Le...