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A Document Visualization Strategy Based on Semantic Multimedia Big Data

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Pervasive Systems, Algorithms and Networks (I-SPAN 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1080))

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Abstract

The integration of semantic web and big data is a key factor in the definition of efficient model to represent knowledge and implement real world applications. In this paper we present a multimedia knowledge base implemented as a semantic multimedia big data storing semantic and linguistic relations between concepts and their multimedia representations. Moreover, we propose a document visualization strategy based on statistical and semantic analysis of textual and visual contents. The proposed approach has been implemented in a tool, called Semantic Tag Cloud, whose task is to show in a concise way the main topic of a document using both textual features and images. We also propose a case study of our approach and an evaluation from a user perception point of view.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy

    Antonio M. Rinaldi

  2. IKNOS-LAB Intelligent and Knowledge Systems, University of Naples Federico II, LUPT, Naples, Italy

    Antonio M. Rinaldi

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  1. Antonio M. Rinaldi
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Correspondence to Antonio M. Rinaldi .

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Editors and Affiliations

  1. University of Naples Federico II, Naples, Napoli, Italy

    Christian Esposito

  2. Soongsil University, Seoul, Korea (Republic of)

    Jiman Hong

  3. The University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

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Rinaldi, A.M. (2019). A Document Visualization Strategy Based on Semantic Multimedia Big Data. In: Esposito, C., Hong, J., Choo, KK. (eds) Pervasive Systems, Algorithms and Networks. I-SPAN 2019. Communications in Computer and Information Science, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-30143-9_4

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  • DOI: https://doi.org/10.1007/978-3-030-30143-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30142-2

  • Online ISBN: 978-3-030-30143-9

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