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DATAMINE
2010
133views more  DATAMINE 2010»
15 years 7 months ago
Using background knowledge to rank itemsets
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...
Nikolaj Tatti, Michael Mampaey
ICDM
2010
IEEE
187views Data Mining» more  ICDM 2010»
15 years 5 months ago
Financial Forecasting with Gompertz Multiple Kernel Learning
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...
Han Qin, Dejing Dou, Yue Fang
SDM
2011
SIAM
242views Data Mining» more  SDM 2011»
14 years 10 months ago
Fast Algorithms for Finding Extremal Sets
Identifying the extremal (minimal and maximal) sets from a collection of sets is an important subproblem in the areas of data-mining and satisfiability checking. For example, ext...
Roberto J. Bayardo, Biswanath Panda
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 7 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
KDD
2005
ACM
182views Data Mining» more  KDD 2005»
16 years 7 months ago
Making holistic schema matching robust: an ensemble approach
The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. As an essential task toward integrating these m...
Bin He, Kevin Chen-Chuan Chang