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AUSAI
2008
Springer
14 years 12 days ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
ESWS
2008
Springer
14 years 5 days ago
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
Christoph Kiefer, Abraham Bernstein, André ...
EDM
2010
248views Data Mining» more  EDM 2010»
13 years 12 months ago
Analyzing Learning Styles using Behavioral Indicators in Web based Learning Environments
It is argued that the analysis of the learner's generated log files during interactions with a learning environment is necessary to produce interpretative views of their activ...
Nabila Bousbia, Jean-Marc Labat, Amar Balla, Issam...
ICML
2005
IEEE
14 years 11 months ago
A martingale framework for concept change detection in time-varying data streams
In a data streaming setting, data points are observed one by one. The concepts to be learned from the data points may change infinitely often as the data is streaming. In this pap...
Shen-Shyang Ho
BMCBI
2010
118views more  BMCBI 2010»
13 years 10 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...