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» A hybrid approach to mining frequent sequential patterns
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JIIS
2006
147views more  JIIS 2006»
14 years 9 months ago
Mining sequential patterns from data streams: a centroid approach
In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...
Alice Marascu, Florent Masseglia
ESWA
2006
139views more  ESWA 2006»
14 years 9 months ago
An efficient data mining approach for discovering interesting knowledge from customer transactions
Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
Show-Jane Yen, Yue-Shi Lee
ICTAI
2003
IEEE
15 years 2 months ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
CIKM
2006
Springer
15 years 1 months ago
TRIPS and TIDES: new algorithms for tree mining
Recent research in data mining has progressed from mining frequent itemsets to more general and structured patterns like trees and graphs. In this paper, we address the problem of...
Shirish Tatikonda, Srinivasan Parthasarathy, Tahsi...
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KDD
2007
ACM
170views Data Mining» more  KDD 2007»
15 years 10 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang