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KDD
2000
ACM
77views Data Mining» more  KDD 2000»
13 years 11 months ago
Small is beautiful: discovering the minimal set of unexpected patterns
A drawback of most traditional data mining methods is that they do not leverage prior knowledge of users. In many business settings, managers and analysts have significant intuiti...
Balaji Padmanabhan, Alexander Tuzhilin
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 8 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
NAR
2010
123views more  NAR 2010»
13 years 2 months ago
Discovering causal signaling pathways through gene-expression patterns
High-throughput gene-expression studies result in lists of differentially expressed genes. Most current meta-analyses of these gene lists include searching for significant members...
Jignesh R. Parikh, Bertram Klinger, Yu Xia, Jarrod...
IVC
2008
69views more  IVC 2008»
13 years 7 months ago
Unsupervised texture classification: Automatically discover and classify texture patterns
In this paper, we present a novel approach to classify texture collections. This approach does not require experts to provide annotated training set. Given the image collection, w...
Lei Qin, Qingfang Zheng, Shuqiang Jiang, Qingming ...
WWW
2008
ACM
13 years 7 months ago
Discovering geographical-specific interests from web click data
As the Internet continues to play an important role in many business applications, it becomes vital to increase the competitive edge by offering geographically tailored contents t...
Chang Sheng, Wynne Hsu, Mong-Li Lee