A cloud-assisted framework for bag-of-features tagging in social networks

Zhanming Jie, Ming Cheung, James She

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Recently, Bag-of-Features Tagging is proven to be an alternative to discover user connections from user shared images in social networks. This approach used unsupervised clustering to classify the user shared images and then correlate similar user, which is computationally intensive for real-world applications. This paper introduces a cloud-assisted framework to improve the efficiency and scalability of Bag-of-Features Tagging. The framework distributes the computation of the unsupervised clustering, the profile learning process and also the similarity calculation. The experiment proves how a scalable cloud-assisted framework outperforms a stand-alone machine with different parameters on a real social network dataset, Skyrock.

Original languageEnglish
Title of host publicationProceedings - IEEE 4th Symposium on Network Cloud Computing and Applications, NCCA 2015
EditorsDimiter R. Avresky, Kurt Tutschku, Emmanuelle Anceaume, Erik Maehle, Antonio Puliafito
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages103-106
Number of pages4
ISBN (Electronic)0769556035, 9780769556031
DOIs
Publication statusPublished - 30 Nov 2015
Externally publishedYes
Event4th IEEE Symposium on Network Cloud Computing and Applications, NCCA 2015 - Munich, Germany
Duration: 11 Jun 201512 Jun 2015

Publication series

NameProceedings - IEEE 4th Symposium on Network Cloud Computing and Applications, NCCA 2015

Conference

Conference4th IEEE Symposium on Network Cloud Computing and Applications, NCCA 2015
Country/TerritoryGermany
CityMunich
Period11/06/1512/06/15

Keywords

  • Cloud computing
  • Facebook
  • Feature extraction
  • Media
  • Scalability
  • Tagging

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