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  • Learning, Identifying, Sharing

    Author(s)
    Martin, Philippe
    Griffith University Author(s)
    Martin, Philippe A.
    Year published
    2010
    Metadata
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    Abstract
    This article argues that a cooperatively-built well-organized shared knowledge base is a new - and, from certain viewpoints, optimal - kind of support (refining and integrating other kinds of supports) for the following three complementary tasks: learning about living entities (and how to identify them), supporting their identification, and sharing knowledge about them. This article gives the ideas behind our prototype and argues that knowledge providers can be not solely specialists but also amateurs. In essence, for these three tasks, it argues for the (re-)use of much more semantically organized and interconnected ...
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    This article argues that a cooperatively-built well-organized shared knowledge base is a new - and, from certain viewpoints, optimal - kind of support (refining and integrating other kinds of supports) for the following three complementary tasks: learning about living entities (and how to identify them), supporting their identification, and sharing knowledge about them. This article gives the ideas behind our prototype and argues that knowledge providers can be not solely specialists but also amateurs. In essence, for these three tasks, it argues for the (re-)use of much more semantically organized and interconnected versions of semantic wikis or scratchpads.
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    Conference Title
    Bioidentify 2010
    Publisher URI
    http://web.archive.org/web/20100501180206/http://www.bioidentify.eu/
    Subject
    Artificial Intelligence and Image Processing not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/46508
    Collection
    • Conference outputs

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