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» Using Temporal Data for Making Recommendations
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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...
FLAIRS
2008
14 years 11 months ago
A Backward Adjusting Strategy and Optimization of the C4.5 Parameters to Improve C4.5's Performance
In machine learning, decision trees are employed extensively in solving classification problems. In order to design a decision tree classifier two main phases are employed. The fi...
Jason R. Beck, Maria Garcia, Mingyu Zhong, Michael...
ESWS
2009
Springer
15 years 4 months ago
An Ontology of Resources: Solving the Identity Crisis
The primary goal of the Semantic Web is to use URIs as a universal space to name anything, expanding from using URIs for webpages to URIs for “real objects and imaginary concepts...
Harry Halpin, Valentina Presutti
SDM
2008
SIAM
130views Data Mining» more  SDM 2008»
14 years 11 months ago
Mining Sequence Classifiers for Early Prediction
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
14 years 7 months ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar