Combining representation learning with logic for language processing
The current state-of-the-art in many natural language processing and automated knowledge base completion tasks is held by representation learning methods which learn distributed vector representations of symbols via gradient based optimization. They require little or no hand-crafted features, thus a...
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University College London (University of London)
2018
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| Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747206 |