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- W2891803508 abstract "Commonsense knowledge is paramount to enable intelligent systems. Typically, it is characterized as being implicit and ambiguous, hindering thereby the automation of its acquisition. To address these challenges, this paper presents semantically enhanced models to enable reasoning through resolving part of commonsense ambiguity. The proposed models enhance in a knowledge graph embedding framework for knowledge base completion. Experimental results show the effectiveness of the new semantic models in commonsense reasoning." @default.
- W2891803508 created "2018-09-27" @default.
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- W2891803508 date "2018-11-01" @default.
- W2891803508 modified "2023-09-23" @default.
- W2891803508 title "Semantically Enhanced Models for Commonsense Knowledge Acquisition" @default.
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- W2891803508 doi "https://doi.org/10.1109/icdmw.2018.00146" @default.
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