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Harvesting Intelligence in Multimedia Social Tagging Systems

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Emergent Web Intelligence: Advanced Information Retrieval

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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Abstract

As more people adopt tagging practices, social tagging systems tend to form rich knowledge repositories that enable the extraction of patterns reflecting the way content semantics is perceived by the web users. This is of particular importance, especially in the case of multimedia content, since the availability of such content in the web is very high and its efficient retrieval using textual annotations or content-based automatically extracted metadata still remains a challenge. It is argued that complementing multimedia analysis techniques with knowledge drawn from web social annotations may facilitate multimedia content management. This chapter focuses on analyzing tagging patterns and combining them with content feature extraction methods, generating, thus, intelligence from multimedia social tagging systems. Emphasis is placed on using all available “tracks” of knowledge, that is tag co-occurrence together with semantic relations among tags and low-level features of the content. Towards this direction, a survey on the theoretical background and the adopted practices for analysis of multimedia social content are presented. A case study from Flickr illustrates the efficiency of the proposed approach.

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Notes

  1. 1.

    Flickr photo-sharing system: http://www.flickr.com del.icio.us

  2. 2.

    Del.icio.us social bookmarks manager: http://del.icio.us

  3. 3.

    YouTube video-sharing website: http://www.youtube.com

  4. 4.

    Technorati blog search engine: http://technorati.com

  5. 5.

    wget: http://www.gnu.org/software/wget

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Acknowledgements

The work presented in this paper was partially supported by the European Commission under contracts FP7-215453 WeKnowIt and FP6-26978 X-media.

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Authors and Affiliations

  1. Informatics Department, Aristotle University of Thessaloniki, Thessaloniki, 540.06, Greece

    Eirini Giannakidou & Athena Vakali

  2. Informatics & Telematics Institute, CERTH, Thermi, Thessaloniki, 57001, Greece

    Foteini Kaklidou, Elisavet Chatzilari & Ioannis Kompatsiaris

Authors
  1. Eirini Giannakidou
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  2. Foteini Kaklidou
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  3. Elisavet Chatzilari
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  4. Ioannis Kompatsiaris
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  5. Athena Vakali
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Correspondence to Eirini Giannakidou .

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Editors and Affiliations

  1. Fac. Sciences Mirande, Université de Bourgogne, Dijon CX, France

    Richard Chbeir

  2. INSA de Lyon, avenue Jean Capelle 7, Villeurbanne CX, 69621, France

    Youakim Badr

  3. Technology, Norwegian University of Science &, O.S. Bragstads plass 2E, Trondheim, 7491, Norway

    Ajith Abraham

  4. College of Business & Administration, Kuwait University, Safat, Kuwait

    Aboul-Ella Hassanien

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Giannakidou, E., Kaklidou, F., Chatzilari, E., Kompatsiaris, I., Vakali, A. (2010). Harvesting Intelligence in Multimedia Social Tagging Systems. In: Chbeir, R., Badr, Y., Abraham, A., Hassanien, AE. (eds) Emergent Web Intelligence: Advanced Information Retrieval. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-84996-074-8_6

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  • DOI: https://doi.org/10.1007/978-1-84996-074-8_6

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