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  • 1.
    Persiani, Michele
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Hellström, Thomas
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Unsupervised Inference of Object Affordance from Text Corpora2019In: Proceedings of the 22nd Nordic Conference on Computational Linguistics / [ed] Mareike Hartmann, Barbara Plank, Association for Computational Linguistics, 2019, article id W19-6112Conference paper (Refereed)
    Abstract [en]

    Affordances denote actions that can be performed in the presence of different objects, or possibility of action in an environment. In robotic systems, affordances and actions may suffer from poor semantic generalization capabilities due to the high amount of required hand-crafted specifications. To alleviate this issue, we propose a method to mine for object-action pairs in free text corpora, successively training and evaluating different prediction models of affordance based on word embeddings.

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