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IEAAIE
2009
Springer
14 years 2 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...
DEXA
2006
Springer
129views Database» more  DEXA 2006»
13 years 11 months ago
Selectively Storing XML Data in Relations
This paper presents a new framework for users to select relevant data from an XML document and store it in an existing relational database, as opposed to previous approaches that s...
Wenfei Fan, Lisha Ma
ICDE
2007
IEEE
129views Database» more  ICDE 2007»
14 years 1 months ago
Ontology-driven Rule Generalization and Categorization for Market Data
—Radio Frequency Identification (RFID) is an emerging technique that can significantly enhance supply chain processes and deliver customer service improvements. RFID provides use...
Dongwoo Won, Dennis McLeod
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
14 years 25 days ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
ICML
2000
IEEE
14 years 8 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore