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KDD
2007
ACM
170views Data Mining» more  KDD 2007»
14 years 9 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
EUROCAST
2005
Springer
133views Hardware» more  EUROCAST 2005»
14 years 2 months ago
An Iterative Method for Mining Frequent Temporal Patterns
The incorporation of temporal semantic into the traditional data mining techniques has caused the creation of a new area called Temporal Data Mining. This incorporation is especial...
Francisco Guil, Antonio B. Bailón, Alfonso ...
TIP
2010
129views more  TIP 2010»
13 years 6 months ago
Selective Data Pruning-Based Compression Using High-Order Edge-Directed Interpolation
—This paper proposes a selective data pruning-based compression scheme to improve the rate-distortion relation of compressed images and video sequences. The original frames are p...
Dung Trung Vo, Joel Solé, Peng Yin, Cristin...
JCB
2006
91views more  JCB 2006»
13 years 8 months ago
Reverse Engineering Discrete Dynamical Systems from Data Sets with Random Input Vectors
Recently a new algorithm for reverse engineering of biochemical networks was developed by Laubenbacher and Stigler. It is based on methods from computational algebra and finds mos...
Winfried Just
IEAAIE
2009
Springer
14 years 3 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...