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Context and Natural Language in Formal Concept Analysis

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Modeling and Using Context (CONTEXT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10257))

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Abstract

CollectionWeb is a framework that uses Formal Concept Analysis (FCA) to link contextually related objects within museum collections. These connections are used to drive a number of user interactions that are intended to promote exploration and discovery. The idea is based on museological perspectives that emphasise the importance of the human, social and cultural contexts that are associated with objects. This paper presents an application of these museological concepts as related to the principles of Formal Concept Analysis along with a description of how the CollectionWeb framework generates narratives based on conceptual pathways. The framework has been applied to a number of user facing applications and provides insights on how FCA and natural language pipelines can be used to provide contextual, linked navigation within museum collections.

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Notes

  1. 1.

    http://cogcomp.cs.illinois.edu/page/download_view/POS.

  2. 2.

    http://nlp.stanford.edu/software/CRF-NER.shtml.

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Author information

Authors and Affiliations

  1. IT University of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen S., Denmark

    Tim Wray & Peter Eklund

Authors
  1. Tim Wray
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  2. Peter Eklund
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Corresponding author

Correspondence to Peter Eklund .

Editor information

Editors and Affiliations

  1. Pierre and Marie Curie University , Paris, France

    Patrick Brézillon

  2. University of Maine , Orono, Maine, USA

    Roy Turner

  3. University of Genoa , Genoa, Italy

    Carlo Penco

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Wray, T., Eklund, P. (2017). Context and Natural Language in Formal Concept Analysis. In: Brézillon, P., Turner, R., Penco, C. (eds) Modeling and Using Context. CONTEXT 2017. Lecture Notes in Computer Science(), vol 10257. Springer, Cham. https://doi.org/10.1007/978-3-319-57837-8_28

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  • DOI: https://doi.org/10.1007/978-3-319-57837-8_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57836-1

  • Online ISBN: 978-3-319-57837-8

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