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KDD
2001
ACM
118views Data Mining» more  KDD 2001»
16 years 3 months ago
Infominer: mining surprising periodic patterns
In this paper, we focus on mining surprising periodic patterns in a sequence of events. In many applications, e.g., computational biology, an infrequent pattern is still considere...
Jiong Yang, Wei Wang 0010, Philip S. Yu
SDM
2009
SIAM
192views Data Mining» more  SDM 2009»
16 years 20 days ago
Mining Cohesive Patterns from Graphs with Feature Vectors.
The increasing availability of network data is creating a great potential for knowledge discovery from graph data. In many applications, feature vectors are given in addition to g...
Arash Rafiey, Flavia Moser, Martin Ester, Recep Co...
LSSC
2001
Springer
15 years 8 months ago
On the Parallelization of the Sparse Grid Approach for Data Mining
Abstract. Recently we presented a new approach [5, 6] to the classification problem arising in data mining. It is based on the regularization network approach, but in contrast to ...
Jochen Garcke, Michael Griebel
123
Voted
KDD
2008
ACM
142views Data Mining» more  KDD 2008»
16 years 3 months ago
Efficient ticket routing by resolution sequence mining
IT problem management calls for quick identification of resolvers to reported problems. The efficiency of this process highly depends on ticket routing--transferring problem ticke...
Qihong Shao, Yi Chen, Shu Tao, Xifeng Yan, Nikos A...
139
Voted
BIBM
2007
IEEE
133views Bioinformatics» more  BIBM 2007»
15 years 3 months ago
Mining Clinical Data with a Temporal Dimension: A Case Study
Clinical databases store large amounts of information about patients and their medical conditions. Data mining techniques can extract relationships and patterns holding in this we...
Michele Berlingerio, Francesco Bonchi, Fosca Giann...