Blog:Improving Machine Learning using Background Knowledge

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|Purpose=To examine how ontologies can be used to improve machine learning techniques.
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== Purpose ==
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=== Use of Ontologies to Improve Machine Learning Techniques and Results ===
Machine Learning (ML) is a popular technique for exploring large amounts of data. However, it has been noted that if no background knowledge is employed, the results of ML may not be understandable. Background knowledge can also improve the quality of ML results by using reasoning techniques to improve coverageThis track considers how ontologies can be used to improve ML results, including understandability and quality.
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==== Organized by Mike Bennett and Andrea Westerinen ====
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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).   
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The objective of this  Ontology Summit 2017 track is to explore ...
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== References ==
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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.

Revision as of 21:52, 13 March 2017

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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