Skip to main content

Multimedia Management Services Based on User Participation with Collaborative Tagging

  • Conference paper
  • First Online:
Transactions on Engineering Technologies

Abstract

As Internet technology has rapidly developed, the amount of multimedia content on the Web has expanded exponentially. Collaborative tagging, namely folksonomy, is emerging to promote user participation in generating and distributing active content. This could be significant evidence for categorizing dynamic multimedia content. For that reason, we proposed an efficient multimedia management system based on collaborative tagging. Our system suggests the candidates, with collaborative filtering for describing and categorizing the multimedia content.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. World Wide Web: proposal for a hypertexts project [Online]. Available: http://w3.org/Proposal.html

  2. Song Y, Zhang L, Giles CL (2011) Automatic tag recommendation algorithms for social recommender systems. ACM Trans Web 5(1):1–31

    Article  Google Scholar 

  3. Kim M, Rho S (2015) Dynamic knowledge management from multiple sources in crowdsourcing environments. New Rev Hypermedia, May 2015, pp 1–13

    Google Scholar 

  4. Park J, Park K, Yun Y, Kim M, Rho S, Man K, Chong W (2015) Efficient multimedia contents management system with tag recommendations. In: Lecture notes in engineering and computer science: proceedings of the international multiconference of engineers and computer scientists 2015, IMECS 2015, 18–20 Mar 2015, Hong Kong, pp 737–738

    Google Scholar 

  5. Kim M, Park S, Joo W, Choi K, Jeong Y, Kim Y (2013) Tag based collaborative Knowledge management system with crowdsourcing. J Internet Technol 14(5):859–866

    Google Scholar 

  6. Xu Z, Fu Y, Mao J, Su D (2006) Towards the semantic web: collaborative tag suggestions. In: Proceedings of the collaborative web tagging workshop at WWW2006, 23–26 May 2006, Edinburgh, Scotland, pp 1–8

    Google Scholar 

  7. Shepitsen A, Gemmell J, Mobasher B, Burke R (2008) Personalized recommendation in social tagging systems using hierarchical clustering. In: Proceedings of the 2008 ACM conference on recommender systems, RECSYS 2008, 23–25 Oct 2008, Lausanne, Switzerland, pp 259–266

    Google Scholar 

  8. Kim M, Park SO (2013) Group affinity based social trust model for an intelligent movie recommender system. Multimedia Tools Appl 64(2):505–516

    Article  Google Scholar 

  9. Kang J (2012) User-centered innovation by crowdsourcing—interface and interaction attribute for motivation and collaboration. Digit Des Soc 35(1):557–565

    Google Scholar 

  10. Nam T, Lee S (2010) Study on the semantic extension of the concept of metadata. Korean Soc Libr Inf Sci 44(4):373–393

    Google Scholar 

  11. Hong S, Lim Y, Lim H (2015) A study on the meta data in video file of smartphone. In: Proceedings of Korean Institute of Information Technology Summer Conference 2015, 11–13 Jun 2015, Chungju-si, Korea, pp 329–331

    Google Scholar 

  12. The rise of crowdsourcing [Online]. Available: www.wired.com/wired/archive/14.06/crowds.html

  13. Kwon H, Seo S (2011) Crowdsourcing case studies and implications for open innovation. Korea Technol Innov Soc 150–160

    Google Scholar 

  14. Won JH, Lee J, Park H (2013) A tag clustering and recommendation method for photo categorization. J Korean Soc Internet Inf 14(2):1–13

    Google Scholar 

  15. Sinclair J, Cardew-Hall M (2008) The folksonomy tag cloud: when is it useful? J Inf Sci 34(1):15–29

    Article  Google Scholar 

  16. Sigurbjörnsson B, Zwol RV (2008) Flickr tag recommendation based on collective knowledge. In: Proceedings of the 17th international conference on World Wide Web, WWW 2008, 21–25 Apr 2008, Beijing, China, pp 327–336

    Google Scholar 

  17. Jäschke R, Marinho L, Hotho A, Schmidt-Thieme L, Stumme G (2007) Tag recommendations in folksonomies. In: Proceedings of the European conference on principles and practice of knowledge discovery in databases, PKDD 2007, 17–21 Sept 2007, pp 506–514

    Google Scholar 

Download references

Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2061978)

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Seungmin Rho .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this paper

Cite this paper

Park, J. et al. (2016). Multimedia Management Services Based on User Participation with Collaborative Tagging. In: Yang, GC., Ao, SI., Huang, X., Castillo, O. (eds) Transactions on Engineering Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-10-0551-0_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-0551-0_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0550-3

  • Online ISBN: 978-981-10-0551-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics