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Infographics Retrieval: A New Methodology

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Natural Language Processing and Information Systems (NLDB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8455))

Abstract

Information graphics, such as bar charts and line graphs, are a rich knowledge source that should be accessible to users. However, techniques that have been effective for document or image retrieval are inadequate for the retrieval of such graphics. We present and evaluate a new methodology that hypothesizes information needs from user queries and retrieves infographics based on how well the inherent structure and intended message of the graphics satisfy the query information needs.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science, University of Delaware, USA

    Zhuo Li, Sandra Carberry, Kathleen F. McCoy & Kelly Peterson

  2. Department of Electrical and Computer Engineering, University of Delaware, USA

    Hui Fang

Authors
  1. Zhuo Li
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  2. Sandra Carberry
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  3. Hui Fang
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  4. Kathleen F. McCoy
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  5. Kelly Peterson
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Editor information

Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Computer Science,, 2 rue Conté, 75003, Paris, France

    Elisabeth Métais

  2. Cirad, TETIS, 500 rue J.F. Breton, 34093, Montpellier Cedex 5, France

    Mathieu Roche

  3. Irstea, TETIS, 500 rue J.F. Breton, 34093, Montpellier Cedex 5, France

    Maguelonne Teisseire

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Li, Z., Carberry, S., Fang, H., McCoy, K.F., Peterson, K. (2014). Infographics Retrieval: A New Methodology. In: Métais, E., Roche, M., Teisseire, M. (eds) Natural Language Processing and Information Systems. NLDB 2014. Lecture Notes in Computer Science, vol 8455. Springer, Cham. https://doi.org/10.1007/978-3-319-07983-7_15

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  • DOI: https://doi.org/10.1007/978-3-319-07983-7_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07982-0

  • Online ISBN: 978-3-319-07983-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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