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International Conference on Theory and Practice of Digital Libraries

TPDL 2018: Digital Libraries for Open Knowledge pp 286–292Cite as

Recommending Scientific Videos Based on Metadata Enrichment Using Linked Open Data

Part of the Lecture Notes in Computer Science book series (LNISA,volume 11057)

Abstract

The amount of available videos in the Web has significantly increased not only for entertainment etc., but also to convey educational or scientific information in an effective way. There are several web portals that offer access to the latter kind of video material. One of them is the TIB AV-Portal of the Leibniz Information Centre for Science and Technology (TIB), which hosts scientific and educational video content. In contrast to other video portals, automatic audiovisual analysis (visual concept classification, optical character recognition, speech recognition) is utilized to enhance metadata information and semantic search. In this paper, we propose to further exploit and enrich this automatically generated information by linking it to the Integrated Authority File (GND) of the German National Library. This information is used to derive a measure to compare the similarity of two videos which serves as a basis for recommending semantically similar videos. A user study demonstrates the feasibility of the proposed approach.

Keywords

  • Video recommendation
  • Semantic enrichment
  • Linked data

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Notes

  1. 1.

    As of June 16, 2017.

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Author information

Authors and Affiliations

  1. Leibniz Information Centre for Science and Technology (TIB), Hannover, Germany

    Christian Otto & Ralph Ewerth

  2. Leibniz Universität Hannover, Hannover, Germany

    Justyna Medrek

  3. L3S Research Center, Leibniz Universität Hannover, Hannover, Germany

    Christian Otto & Ralph Ewerth

Authors
  1. Justyna Medrek
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  2. Christian Otto
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  3. Ralph Ewerth
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Corresponding author

Correspondence to Christian Otto .

Editor information

Editors and Affiliations

  1. University Carlos III, Madrid, Spain

    Eva Méndez

  2. USI, Università della Svizzera Italiana, Lugano, Switzerland

    Fabio Crestani

  3. INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal

    Cristina Ribeiro

  4. INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal

    Gabriel David

  5. INESC TEC, Faculty of Engineering, University of Porto, Porto, Portugal

    João Correia Lopes

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Medrek, J., Otto, C., Ewerth, R. (2018). Recommending Scientific Videos Based on Metadata Enrichment Using Linked Open Data. In: Méndez, E., Crestani, F., Ribeiro, C., David, G., Lopes, J. (eds) Digital Libraries for Open Knowledge. TPDL 2018. Lecture Notes in Computer Science(), vol 11057. Springer, Cham. https://doi.org/10.1007/978-3-030-00066-0_25

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  • DOI: https://doi.org/10.1007/978-3-030-00066-0_25

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