Automatic image tagging and recommendation via PARAFAC2

IEEE International Workshop on Machine Learning for Signal Processing, MLSP

Volumn 2015-November, Issue , 2015, Pages

  Pantraki, Evangelia ^a   Kotropoulos, Constantine ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Automatic Image Tagging; Image Recommendation; Multi label Classification; PARAFAC2

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); FACE RECOGNITION; IMAGE RETRIEVAL; LEARNING SYSTEMS; SEMANTICS; SIGNAL PROCESSING; USER INTERFACES; VECTOR SPACES; VECTORS;

10-FOLD CROSS-VALIDATION; AUTOMATIC IMAGE ANNOTATION; EXPERIMENTAL PROTOCOLS; IMAGE RECOMMENDATION; IMAGE TAGGING; MULTI LABEL CLASSIFICATION; PARAFAC2; PARALLEL FACTOR ANALYSIS;

IMAGE PROCESSING;

EID: 84960900601     PISSN: 21610363     EISSN: 21610371     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2015.7324363     Document Type: Conference Paper

References (20)

1. S. Lindstaedt, R. Mörzinger, R. Sorschag, and V. Pammer, "Automatic image annotation using visual content and folksonomies," Multimedia Tools and Applications, vol. 42, no. 1, pp. 97-113, March 2009.
2. F. Wu, Y. Han, Q. Tian, and Y. Zhuang, "Multi-label boosting for image annotation by structural grouping sparsity," in Proc. ACM Int. Conf. Multimedia, Florence, Italy, October 2010, pp. 15-24.
3. C. Wang, S. Yan, L. Zhang, and H. J. Zhang, "Multilabel sparse coding for automatic image annotation," in Proc. IEEE Int. Conf. Computer Vision Pattern Recognition, Miami, FL, USA, June 2009, pp. 1643-1650.
4. Y. Yang, Y. Yang, Z. Huang, H. T. Shen, and F. Nie, "Tag localization with spatial correlations and joint group sparsity," in Proc. IEEE Int. Conf. Computer Vision Pattern Recognition, Providence, RI, USA, June 2011, pp. 881-888.
5. H. Ma, J. Zhu, M. R. T. Lyu, and I. King, "Bridging the semantic gap between image contents and tags," IEEE Trans. Multimedia, vol. 12, no. 5, pp. 462-473, August 2010.
6. H. Wang, H. Heng, and C. Ding, "Image annotation using bi-relational graph of images and semantic labels," in Proc. IEEE Int. Conf. Computer Vision Pattern Recognition, Providence, RI, USA, June 2011, pp. 793-800.
7. X. Zhang, X. Zhao, Z. Li, J. Xia, R. Jain, and W. Chao, "Social image tagging using graph-based reinforcement on multi-type interrelated objects," Signal Processing, vol. 93, no. 8, pp. 2178-2189, August 2013.
8. X. Ning and G. Karypis, "SLIM: Sparse linear methods for top-n recommender systems," in Proc. 11th IEEE Int. Conf. Data Mining, Vancouver, BC, Canada, December 2011, pp. 497-506.
9. G. Zhu, S. Yan, and Y. Ma, "Image tag refinement towards low-rank, content-tag prior and error sparsity," in Proc. ACM Int. Conf. Multimedia, Florence, Italy, October 2010, pp. 461-470.
10. Y. Panagakis and C. Kotropoulos, "Automatic music tagging via PARAFAC2," in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Prague, Czech Republic, May 2011, pp. 481-484.
11. P. Chew, B. Bader, T. Kolda, and A. Abdelali, "Crosslanguage information retrieval using PARAFAC2," in Proc. 13th ACM Int. Conf. Knowledge Discovery and Data Mining, San Jose, CA, USA, August 2007, pp. 143-152.
12. A. Oliva and A. Torralba, "Building the GIST of a scene: The role of global image features in recognition," Progress in Brain Research, vol. 155, pp. 23-36, 2006.
13. R. A. Harshman, "PARAFAC2: Mathematical and technical notes," UCLA Working Papers in Phonetics, vol. 22, pp. 30-47, 1972.
14. K. Pliakos and C. Kotropoulos, "Simultaneous image tagging and geo-location prediction within hypergraph ranking framework," in IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Florence, Italy, May 2014, pp. 6894-6898.
15. T. G. Kolda and B. W. Bader, "Tensor decompositions and applications," SIAM Review, vol. 51, no. 3, pp. 455-500, September 2009.
16. R. A. Harshman, "Foundations of the PARAFAC procedure: Models and conditions for an explanatory multimodal factor analysis," UCLA Working Papers in Phonetics, vol. 16, pp. 1-84, 1970.
17. M. Hoffman, D. Blei, and P. Cook, "Easy as CBA: A simple probabilistic model for tagging music," in Proc. 10th Int. Conf. Music Information Retrieval, Kobe, Japan, October 2009, pp. 369-374.
18. Y. Panagakis, C. Kotropoulos, and G. R. Arce, "Sparse multi-label linear embedding within nonnegative tensor factorization applied to music tagging," in Proc. 11th Int. Conf. Music Information Retrieval, Utrecht, The Netherlands, August 2010, pp. 393-398.
19. D. Turnbull, L. Barrington, D. Torres, and G. Lanckriet, "Semantic annotation and retrieval of music and sound effects," IEEE Trans. Audio, Speech, and Language Processing, vol. 16, no. 2, pp. 467-476, February 2008.
20. I. Guyon, J. Makhoul, R. Schwartz, and V. Vapnik, "What size test set gives good error rate estimates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 52-64, January 1998.