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» Mining spatial association rules in image databases
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ACSC
2008
IEEE
14 years 11 months ago
An efficient hash-based algorithm for minimal k-anonymity
A number of organizations publish microdata for purposes such as public health and demographic research. Although attributes of microdata that clearly identify individuals, such a...
Xiaoxun Sun, Min Li, Hua Wang, Ashley W. Plank
KDD
2009
ACM
249views Data Mining» more  KDD 2009»
15 years 10 months ago
Drosophila gene expression pattern annotation using sparse features and term-term interactions
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...
CIKM
2005
Springer
15 years 3 months ago
Concept-based interactive query expansion
Despite the recent advances in search quality, the fast increase in the size of the Web collection has introduced new challenges for Web ranking algorithms. In fact, there are sti...
Bruno M. Fonseca, Paulo Braz Golgher, Bruno P&ocir...
ASIAMS
2007
IEEE
15 years 3 months ago
Rough-Fuzzy Granulation, Rough Entropy and Image Segmentation
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
Sankar K. Pal
BMCBI
2007
207views more  BMCBI 2007»
14 years 9 months ago
Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering
Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular lev...
Manjunatha Jagalur, Chris Pal, Erik G. Learned-Mil...