Image-mediated learning for zero-shot cross-lingual document retrieval

Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Volumn , Issue , 2015, Pages 585-590

  Funaki, Ruka ^a   Nakayama, Hideki ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS;

CROSS-LINGUAL; DOCUMENT RETRIEVAL; GENERALIZED CANONICAL CORRELATION ANALYSIS; JAPANESE TEXT; LEARNING APPROACH; PARALLEL CORPORA; RETRIEVAL ACCURACY; SEMANTIC SUBSPACES;

INFORMATION RETRIEVAL;

EID: 84959908078     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/d15-1070     Document Type: Conference Paper

References (22)

1. Douglas J Carroll. 1968. Generalization of canonical correlation analysis to three or more sets of variables. In Proceedings of the 76th Annual Convention of the American Psychological Association, volume 3, pages 227-228.
2. Ken Chatfleld, Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2014. Return of the Devil in the Details: Delving Deep into Convolutional Nets. In Proceedings of the British Machine Vision Conference, pages 1-11.
3. Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell. 2013. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. In Proceedings of the International Conference on Machine Learning, pages 647-655.
4. Hao Fang, Saurabh Gupta, Forrest Iandola, K. Rupesh Srivastava, Li Deng, Piotr Dollár, Jianfeng Gao, Xiaodong He, Margaret Mitchell, John C. Piatt, C. Lawrence Zitnick, and Geoffrey Zweig. 2015. From Captions to Visual Concepts and Back. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
5. Yunchao Gong, Qifa Ke, Michael Isard, and Svetlana Lazebnik. 2014. A Multiview Embedding Space for Modeling Internet Images, Tags, and their Semantics. International Journal of Computer Vision, 106(2):210-233.
6. David R Hardoon, Sandor Szedmak, and John Shawe-Taylor. 2004. Canonical Correlation Analysis: an Overview with Application to Learning Methods. Neural Computation, 16(12):2639-2664.
7. Harold Hotelling. 1936. Relations between Two Sets of Variants. Biometrika, 28:321-377.
8. Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell. 2014. Caffe: Convolutional Architecture for Fast Feature Embedding. In Proceedings of the ACM International Conference on Multimedia, pages 675-678.
9. Jon Robers Kettenring. 1971. Canonical Analysis of Several Sets of Variables. Biometrika, 58(3):433-451.
10. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. ImageNet Classification with Deep Convolutional Neural Networks. In Advances in Neural Information Processing Systems, pages 1097-1105.
11. Taku Kudo, Kaoru Yamamoto, and Yuji Matsumoto. 2004. Applying Conditional Random Fields to Japanese Morphological Analysis. In Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pages 230-237.
12. Yaoyong Li and John Shawe-Taylor. 2004. Using KCCA for Japanese-English Cross-language Information Retrieval and Classification. In Learning Methods for Text Understanding and Mining Workshop, pages 117-133.
13. David G Lowe. 1999. Object recognition from local scale-invariant features. In Proceedings of the Seventh IEEE International Conference on Computer Vision, volume 2, pages 1150-1157.
14. Florent Perronnin, Jorge Sánchez, and Thomas Mensink. 2010. Improving the Fisher kernel for large-scale image classification. In Proceedings of the European Conference on Computer Vision, pages 143-156.
15. Cyrus Rashtchian, Peter Young, Micah Hodosh, Julia Hockenmaier, and North Goodwin Ave. 2010. Collecting Image Annotations Using Amazon's Mechanical Turk. Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, pages 139-147.
16. Nikhil Rasiwasia, Jose Costa Pereira, Emanuele Coviello, Gabriel Doyle, Gert R. G. Lanckriet, Roger Levy, and Nuno Vasconcelos. 2010. A New Approach to Cross-modal Multimedia Retrieval. Proceedings of the International Conference on Multimedia, pages 251-260.
17. Jan Rupnik, Andrej Muhič, and Primo Škraba. 2012. Cross-Lingual Document Retrieval through Hub Languages. In Neural Information Processing Systems Workshop.
18. Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei. 2015. ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision.
19. Christian Szegedy, Scott Reed, Pierre Sermanet, Vincent Vanhoucke, and Andrew Rabinovich. 2014. Going deeper with convolutions. CoRR abs/1409.4842.
20. Raghavendra Udupa and Mitesh M Khapra. 2010. Improving the Multilingual User Experience of Wikipedia Using Cross-Language Name Search. Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pages 492-500.
21. Michel Velden and Yoshio Takane. 2012. Generalized Canonical Correlation Analysis with Missing Values. Computational Statistics, 27(3):551-571.
22. Alexei Vinokourov, John Shawe-Taylor, and Nello Cristianini. 2002. Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis. Advances in Neural Information Processing Systems, pages 1473-1480.