Overcoming Incomplete User Models in Recommendation Systems Via an Ontology

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Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...

Overcoming Incomplete User Models in Recommendation Systems Via an Ontology

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