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A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features

Author

Listed:
  • Antonio Maria Rinaldi

    (Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy
    These authors contributed equally to this work.)

  • Cristiano Russo

    (Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy
    These authors contributed equally to this work.)

  • Cristian Tommasino

    (Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy
    These authors contributed equally to this work.)

Abstract

In recent years the information user needs have been changed due to the heterogeneity of web contents which increasingly involve in multimedia contents. Although modern search engines provide visual queries, it is not easy to find systems that allow searching from a particular domain of interest and that perform such search by combining text and visual queries. Different approaches have been proposed during years and in the semantic research field many authors proposed techniques based on ontologies. On the other hand, in the context of image retrieval systems techniques based on deep learning have obtained excellent results. In this paper we presented novel approaches for image semantic retrieval and a possible combination for multimedia document analysis. Several results have been presented to show the performance of our approach compared with literature baselines.

Suggested Citation

  • Antonio Maria Rinaldi & Cristiano Russo & Cristian Tommasino, 2020. "A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features," Future Internet, MDPI, vol. 12(11), pages 1-20, October.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:11:p:183-:d:435816
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    References listed on IDEAS

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    2. Stephen P. Harter, 1992. "Psychological relevance and information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 602-615, October.
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    Cited by:

    1. Filipe Portela, 2021. "Data Science and Knowledge Discovery," Future Internet, MDPI, vol. 13(7), pages 1-4, July.

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