Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
World Wide Web
Erschienen in: World Wide Web 5/2017

28.10.2016

Dual graph regularized NMF model for social event detection from Flickr data

verfasst von: Zhenguo Yang, Qing Li, Wenyin Liu, Yun Ma, Min Cheng

Erschienen in: World Wide Web | Ausgabe 5/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this work, we aim to discover real-world events from Flickr data by devising a three-stage event detection framework. In the first stage, a multimodal fusion (MF) model is designed to deal with the heterogeneous feature modalities possessed by the user-shared data, which is advantageous in computation complexity. In the second stage, a dual graph regularized non-negative matrix factorization (DGNMF) model is proposed to learn compact feature representations. DGNMF incorporates Laplacian regularization terms for the data graph and base graph into the objective, keeping the geometry structures underlying the data samples and dictionary bases simultaneously. In the third stage, hybrid clustering algorithms are applied seamlessly to discover event clusters. Extensive experiments conducted on the real-world dataset reveal the MF-DGNMF-based approaches outperform the baselines.
Vorheriger Artikel A semantic based Web page classification strategy using multi-layered domain ontology
Nächster Artikel Tide-tree: A self-tuning indexing scheme for hybrid storage system

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Literatur
1.
Ahsan, U., Essa, I.: Clustering social event images using kernel canonical correlation analysis. In: Computer Vision and Pattern Recognition Workshops, 2014 IEEE Conference on, pp. 814–819 (2014)
2.
Ah-Pine, J., Csurka, G., Clinchant, S.: Semi-supervised visual and textual information fusion in CBMIR using graph-based methods. ACM Trans. Inf. Syst. (TOIS) 33(2), 9 (2015)CrossRef
3.
Cai, X., Nie, F., Huang, H., Kamangar, F.: Heterogeneous image feature integration via multi-modal spectral clustering. In: Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pp. 1977–1984 (2011)
4.
Cai, D., He, X., Han, J., Huang, T.S.: Graph regularized nonnegative matrix factorization for data representation. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1548–1560 (2011)CrossRef
5.
Cands, E.J., Li, X., Ma, Y., Wright, J.: Robust principal component analysis? J. ACM (JACM) 58(3), 11 (2011)MathSciNetMATH
6.
Chen, L., Roy, A.: Event detection from flickr data through wavelet-based spatial analysis. In: Proceedings of the 18th ACM conference on Information and knowledge management, pp. 523–532 (2009)
7.
Chen, J., Cui, Y., Ye, G., Liu, D., Chang, S.F.: Event-driven semantic concept discovery by exploiting weakly tagged internet images. In: Proceedings of International Conference on Multimedia Retrieval, p. 1 (2014)
8.
Choi, J., Kim, E., Larson, M., Friedland, G., Hanjalic, A.: Evento 360: Social event discovery from Web-scale multimedia collection (2015)
9.
Duan, K., Crandall, D.J., Batra, D.: Multimodal learning in loosely-organized Web images. In: Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pp. 2465–2472 (2014)
10.
Elhamifar, E., Vidal, R.: Sparse subspace clustering: Algorithm, theory, and applications. IEEE Trans. Pattern Anal. Mach. Intell. 35(11), 2765–2781 (2013)CrossRef
11.
Hinton, G.E., Salakhutdinov, R.R.: Reducing the dimensionality of data with neural networks. Science 313(5786), 504–507 (2006)MathSciNetCrossRefMATH
12.
Hinton, G.: A practical guide to training restricted Boltzmann machines. Momentum 9(1), 926 (2010)
13.
Hyvrinen, A., Karhunen, J., Oja, E.: Independent component analysis (Vol. 46) John Wiley & Sons (2004)
14.
Jiang, X., Lai, J.: Sparse and dense hybrid representation via dictionary decomposition for face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(5), 1067–1079 (2015)CrossRef
15.
Jolliffe, I.: Principal component analysis. John Wiley & Sons Ltd (2002)
16.
Kim, G., Sigal, S.M.L.: Joint photo stream and blog post summarization and exploration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3081–3089 (2015)
17.
Lee, D.D., Sebastian Seung, H.: Algorithms for non-negative matrix factorization. Advances in neural information processing systems, 556–562 (2001)
18.
Li, R., Lei, K.H., Khadiwala, R., Chang, K.: Tedas: A twitter-based event detection and analysis system. In: Data engineering (ICDE), 2012 IEEE 28th international conference on, pp. 1273–1276 (2001)
19.
Li, Z., Liu, J., Tang, J., Lu, H.: Robust structured subspace learning for data representation. IEEE Trans. Pattern Anal. Mach. Intell. 37(10), 2085–2098 (2015)CrossRef
20.
Liu, X., Huet, B.: Heterogeneous features and model selection for event-based media classification. In: 3rd ACM International Conference on Multimedia Retrieval, pp. 151–158 (2013)
21.
Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: Robust recovery of subspace structures by low-rank representation. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 171–184 (2013)CrossRef
22.
Liu, G., Xu, H., Tang, J., Liu, Q., Yan, S.: A deterministic analysis for LRR. IEEE Trans. Pattern Anal. Mach. Intell. 38(3), 417–430 (2015)CrossRef
23.
Nitta, N., Kumihashi, Y., Kato, T., Babaguchi, N.: Real-World Event detection using flickr images. In: MultiMedia Modeling, pp. 307–314 (2014)
24.
Petkos, G., Papadopoulos, S., Kompatsiaris, Y.: Social event detection using multimodal clustering and integrating supervisory signals. In: Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, p. 23 (2012)
25.
Petkos, G., Papadopoulos, S., Mezaris, V., Kompatsiaris, Y.: Social event detection at MediaEval 2014: Challenges, datasets, and evaluation. In: MediaEval 2014 Workshop, Barcelona, Spain (2014)
26.
Qian, S., Zhang, T., Xu, C., Hossain, M.S.: Social event classification via boosted multimodal supervised latent dirichlet allocation. ACM Trans. Multimed. Comput. Commun. Appl. (TOMM) 11(2), 27 (2014)
27.
Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes Twitter users: real-time event detection by social sensors. In: Proceedings of the 19th international conference on World wide web, pp. 851–860 (2010)
28.
Sakaki, T., Okazaki, M., Matsuo, Y.: Tweet analysis for real-time event detection and earthquake reporting system development. IEEE Trans. Knowl. Data Eng. 25(4), 919–931 (2013)CrossRef
29.
Schinas, M., Papadopoulos, S., Petkos, G., Kompatsiaris, Y., Mitkas, P.A.: Multimodal graph-based event detection and summarization in social media streams. In: Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, pp. 189–192 (2015)
30.
Shekhar, S., Patel, V.M., Nasrabadi, N.M., Chellappa, R.: Joint sparse representation for robust multimodal biometrics recognition. IEEE Trans. Pattern Anal. Mach. Intell. 36(1), 113–126 (2014)CrossRef
31.
Snoek, C.G.M., Worring, M., Smeulders, A.W.M.: Early versus late fusion in semantic video analysis. In: Proceedings of the 13th annual ACM international conference on Multimedia, pp. 399–402 (2005)
32.
Strehl, A., Ghosh, J.: Cluster ensembles-a knowledge reuse framework for combining multiple partitions. J. Mach. Learn. Res. 3, 583–617 (2003)MathSciNetMATH
33.
Sutanto, T., Nayak, R.: The ranking based constrained document clustering method and its application to social event detection. In: Database Systems for Advanced Applications, pp. 47–60 (2014)
34.
Sutanto, T., Nayak, R.: Ranking based clustering for social event detection. In: Working Notes Proceedings of the MediaEval 2014 Workshop, vol. 1263, pp. 1–2 (2014)
35.
Wang, Y., Sundaram, H., Xie, L.: Social event detection with interaction graph modeling. In: Proceedings of the 20th ACM international conference on Multimedia, pp. 865–868 (2012)
36.
Wu, F., Yu, Z., Yang, Y., Tang, S., Zhang, Y., Zhuang, Y.: Sparse multi-modal hashing. IEEE Trans. Multimedia 16(2), 427–439 (2014)CrossRef
37.
Yang, Z., Li, Q., Lu, Z., Ma, Y., Gong, Z., Pan, H.: Semi-supervised multimodal clustering algorithm integrating label signals for social event detection. In: Multimedia Big Data (BigMM), 2015 IEEE International Conference on, pp. 32–39 (2015)
38.
Yang, Z., Li, Q., Lu, Z., Ma, Y., Gong, Z., Pan, H., Chen, Y.: Semi-Supervised Multimodal fusion model for social event detection on web image collections. Int. J. Multimedia Data Eng. Manag. (IJMDEM) 6(4), 1–22 (2015)CrossRef
39.
Yang, X., Zhang, T., Xu, C., Hossain, M.S.: Automatic visual concept learning for social event understanding. IEEE Trans. Multimedia 17(3), 346–358 (2015)CrossRef
40.
Yang, Z., Li, Q., Liu, W., Ma, Y.: Learning manifold representation from multimodal data for event detection in Flickr-like social media, The 3rd International Workshop on Semantic Computing and Personalization in conjunction with The 21th International Conference on Database Systems for Advanced Applications, 160–167 (2016)
41.
Yin, M., Gao, J., Lin, Z.: Laplacian regularized low-rank representation and its applications. IEEE Trans. Pattern Anal. Mach. Intell. 38(3), 504–517 (2015)CrossRef
42.
Zhang, Z., Zhao, K.: Low-rank matrix approximation with manifold regularization. IEEE Trans. Pattern Anal. Mach. Intell. 35(7), 1717–1729 (2015)CrossRef
43.
Zhang, W., Zeng, S., Wang, D., Xue, X.: Weakly supervised semantic segmentation for social images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2718–2726 (2015)
44.
45.
Zhuang, L., Gao, S., Tang, J., Wang, J., Lin, Z., Ma, Y.: Constructing a non-Negative low rank and sparse graph with data-adaptive features. IEEE Trans. Image Process. 24(11), 3717–3728 (2015)MathSciNetCrossRef
Metadaten
Titel
Dual graph regularized NMF model for social event detection from Flickr data
verfasst von
Zhenguo Yang
Qing Li
Wenyin Liu
Yun Ma
Min Cheng
Publikationsdatum
28.10.2016
Verlag
Springer US
Erschienen in
World Wide Web / Ausgabe 5/2017
Print ISSN: 1386-145X
Elektronische ISSN: 1573-1413
DOI
https://doi.org/10.1007/s11280-016-0405-1

Weitere Artikel der Ausgabe 5/2017

World Wide Web 5/2017 Zur Ausgabe

OriginalPaper

Ranking weighted clustering coefficient in large dynamic graphs

OriginalPaper

Reverse direction-based surrounder queries for mobile recommendations

OriginalPaper

Efficient computation of distance labeling for decremental updates in large dynamic graphs

OriginalPaper

Novel structures for counting frequent items in time decayed streams

OriginalPaper

Tide-tree: A self-tuning indexing scheme for hybrid storage system

OriginalPaper

Discovery of probabilistic nearest neighbors in traffic-aware spatial networks

Premium Partner

    Bildnachweise