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» Theoretical Frameworks for Data Mining
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ICDM
2008
IEEE
97views Data Mining» more  ICDM 2008»
15 years 4 months ago
Semi-supervised Learning from General Unlabeled Data
We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
KDD
2008
ACM
142views Data Mining» more  KDD 2008»
15 years 10 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...
RELMICS
2005
Springer
15 years 3 months ago
Control-Flow Semantics for Assembly-Level Data-Flow Graphs
Abstract. As part of a larger project, we have built a declarative assembly language that enables us to specify multiple code paths to compute particular quantities, giving the ins...
Wolfram Kahl, Christopher Kumar Anand, Jacques Car...
ICDM
2007
IEEE
134views Data Mining» more  ICDM 2007»
15 years 4 months ago
On Regional Association Rule Scoping
A special challenge for spatial data mining is that information is not distributed uniformly in spatial data sets. Consequently, the discovery of regional knowledge is of fundamen...
Wei Ding 0003, Christoph F. Eick, Xiaojing Yuan, J...
GECCO
2006
Springer
128views Optimization» more  GECCO 2006»
15 years 1 months ago
FTXI: fault tolerance XCS in integer
In the realm of data mining, several key issues exists in the traditional classification algorithms, such as low readability, large rule number, and low accuracy with information ...
Hong-Wei Chen, Ying-Ping Chen