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DATAMINE
2006
139views more  DATAMINE 2006»
13 years 5 months ago
Discovering Classification from Data of Multiple Sources
In many large e-commerce organizations, multiple data sources are often used to describe the same customers, thus it is important to consolidate data of multiple sources for intell...
Charles X. Ling, Qiang Yang
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
14 years 6 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin
ICML
2003
IEEE
14 years 6 months ago
Learning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers...
Matthew Richardson, Pedro Domingos
NAACL
2004
13 years 7 months ago
Predicting Emotion in Spoken Dialogue from Multiple Knowledge Sources
We examine the utility of multiple types of turn-level and contextual linguistic features for automatically predicting student emotions in human-human spoken tutoring dialogues. W...
Katherine Forbes-Riley, Diane J. Litman
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
14 years 4 days ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...