Learning manifold representation from multimodal data for event detection in flickr-like social media

Zhenguo Yang, Qing Li, Wenyin Liu, Yun Ma

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


In this work, a three-stage social event detection model is devised to discover events in Flickr data. As the features possessed by the data are typically heterogeneous, a multimodal fusion model (M2F) exploits a soft-voting strategy and a reinforcing model is devised to learn fused features in the first stage. Furthermore, a Laplacian non-negative matrix factorization (LNMF) model is exploited to extract compact manifold representation. Particularly, a Laplacian regularization term constructed on the multimodal features is introduced to keep the geometry structure of the data. Finally, clustering algorithms can be applied seamlessly in order to detect event clusters. Extensive experiments conducted on the real-world dataset reveal the M2F-LNMF-based approaches outperform the baselines.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - DASFAA 2016 International Workshops
Subtitle of host publicationBDMS, BDQM, MoI, and SeCoP, Proceedings
EditorsJinho Kim, Hong Gao, Yasushi Sakurai
Number of pages8
ISBN (Print)9783319320540
Publication statusPublished - 1 Jan 2016
Externally publishedYes
EventInternational Workshop on Database Systems for Advanced Applications, DASFAA 2016 - Dallas, United States
Duration: 16 Apr 201619 Apr 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Workshop on Database Systems for Advanced Applications, DASFAA 2016
Country/TerritoryUnited States


  • Event detection
  • Manifold learning
  • Multimedia content analysis
  • Multimodal fusion
  • Social media analytics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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