Blog:Improving Machine Learning using Background Knowledge
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Revision as of 22:52, 13 March 2017 by Awesterinen (Talk | contribs)
Contents |
Purpose
Use of Ontologies to Improve Machine Learning Techniques and Results
Organized by Mike Bennett and Andrea Westerinen
Machine Learning (ML) is valuable for exploring large amounts of data. However, it has been noted that if no background knowledge is employed, the results may not be understandable or of sufficient quality. Background knowledge can also improve the quality of machine learning results by using reasoning techniques to select learning models, clean data or improve data selection (reducing large, noisy data sets to manageable, focused ones).
The objective of this Ontology Summit 2017 track is to explore ...
References
Buitelaar, Paul, Philipp Cimiano, and Bernardo Magnini. "Ontology learning from text: An overview." Ontology learning from text: Methods, evaluation and applications 123 (2005): 3-12.
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