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        <title>Unsupervised Inference of Object Affordance from Text Corpora</title>
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        <namePart type="given">Michele</namePart>
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        <dateIssued>2019-sep–oct</dateIssued>
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            <title>Proceedings of the 22nd Nordic Conference on Computational Linguistics</title>
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        <name type="personal">
            <namePart type="given">Mareike</namePart>
            <namePart type="family">Hartmann</namePart>
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        <name type="personal">
            <namePart type="given">Barbara</namePart>
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            <publisher>Linköping University Electronic Press</publisher>
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    <abstract>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.</abstract>
    <identifier type="citekey">persiani-hellstrom-2019-unsupervised</identifier>
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        <url>https://aclanthology.org/W19-6112</url>
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            <start>115</start>
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%0 Conference Proceedings
%T Unsupervised Inference of Object Affordance from Text Corpora
%A Persiani, Michele
%A Hellström, Thomas
%Y Hartmann, Mareike
%Y Plank, Barbara
%S Proceedings of the 22nd Nordic Conference on Computational Linguistics
%D 2019
%8 sep–oct
%I Linköping University Electronic Press
%C Turku, Finland
%F persiani-hellstrom-2019-unsupervised
%X 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.
%U https://aclanthology.org/W19-6112
%P 115-120

Markdown (Informal)

[Unsupervised Inference of Object Affordance from Text Corpora](https://aclanthology.org/W19-6112) (Persiani & Hellström, NoDaLiDa 2019)

• Unsupervised Inference of Object Affordance from Text Corpora (Persiani & Hellström, NoDaLiDa 2019)

ACL

• Michele Persiani and Thomas Hellström. 2019. Unsupervised Inference of Object Affordance from Text Corpora. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 115–120, Turku, Finland. Linköping University Electronic Press.