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» Using and Learning Semantics in Frequent Subgraph Mining
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FLAIRS
2010
15 years 1 months ago
Visual Object Detection using Frequent Pattern Mining
Object search in a visual scene is a highly challenging and computationally intensive task. Most of the current object detection techniques extract features from images for classi...
Yousuf Aboobaker Sait, Balaraman Ravindran
EUROCAST
2005
Springer
133views Hardware» more  EUROCAST 2005»
15 years 5 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 ...
ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
15 years 6 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
CIKM
2008
Springer
15 years 1 months ago
Structure feature selection for graph classification
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining...
Hongliang Fei, Jun Huan
SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
15 years 11 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...