Visually interpreting names as demographic attributes by exploiting click-through data

Proceedings of the National Conference on Artificial Intelligence

Volumn 1, Issue , 2015, Pages 44-50

  Chen, Yan Ying ^a,b   Kuo, Yin Hsi ^a   Wu, Chun Che ^a   Hsu, Winston H ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b FX PALO ALTO LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; IMAGE RETRIEVAL; POPULATION STATISTICS;

ATTRIBUTE-BASED; CLICKTHROUGH DATA; CULTURAL BACKGROUNDS; FACE IMAGE RETRIEVAL; INCREMENTAL DATA; KEYWORD-BASED; MANUAL LABELING; USER PROFILING;

DATA VISUALIZATION;

EID: 84959554963     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. Aaker, J. L. 1997. Dimensions of brand personality. In Journal of Marketing Research.
2. Ahonen, T.; Hadid, A.; and Pietikäinen, M. 2004. Face recognition with local binary patterns. In Proceedings of the European Conference on Computer Vision (ECCV).
3. Beeferman, D., and Berger, A. 2000. Agglomerative clustering of a search engine query log. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD).
4. Bird, S. 2006. Nltk: the natural language toolkit. In Proceedings of the COLINGACL on Interactive presentation sessions.
5. Burger, J. D.; Henderson, J.; Kim, G.; and Zarrella, G. 2012. Discriminating gender on twitter. In Proceedings of the Conference on Empirical Methods on Natural Language Processing (EMNLP).
6. Cao, B.; Shen, D.; Wang, K.; and Yang, Q. 2010. Click-through log analysis by collaborative ranking. In Proceedings of the AAA/Conference on Artificial Intelligence (AAAI).
7. Chang, C.-C, and Lin, C.-J. 2011. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
8. Chen, W.; Ji, Z.; Shen, S.; and Yang, Q. 2011. A whole page click model to better interpret search engine click data. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
9. Chen, H.; Gallagher, A. C; and Girod, B. 2013. What's in a name? first names as facial attributes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
10. Cheng, A.-J.; Chen, Y.-Y; Huang, Y.-T.; Hsu, W. H.; and Liao, H.-Y. M. 2011. Personalized travel recommendation by mining people attributes from community-contributed photos. In Proceedings of the ACM International Conference on Multimedia (ACM MM).
11. Crasweil, N., and Szummer, M. 2007. Random walks on the click graph. In Proceedings of the ACM SIGIR Conference on Research & Development on Information Retrieval (SIGIR).
12. Dey, R.; Jelveh, Z.; and Ross, K. 2012. Facebook users have become much more private: A large-scale study. In Proceedings of the IEEE International Workshop on Security and Social Networking (SESOC).
13. Hasan, M. K., and Pal, C. 2014. Experiments on visual information extraction with the faces of wikipedia. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
14. Hua, X.-S.; Yang, L.; Wang, J.; Wang, J.; Ye, M.; Wang, K.; Rui, Y; and Li, J. 2013. Clickage: Towards bridging semantic and intent gaps via mining click logs of search engines. In Proceedings of the ACM International Conference on Multimedia (ACM MM).
15. Jain, V., and Varma, M. 2011. Learning to re-rank: Query-dependent image re-ranking using click data. In Proceedings of the International World Wide Web Conference (WWW).
16. Joachims, T. 2002. Optimizing search engines using click-through data. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD).
17. Joachims, T. 2005. Accurately interpreting clickthrough data as implicit feedback. In Proceedings of the ACM SIGIR Conference on Research & Development on Information Retrieval (SIGIR).
18. Kumar, N.; Belhumeur, P.; and Nayar, S. 2008. Facetracer: A search engine for large collections of images with faces. In Proceedings of the European Conference on Computer Vision (ECCV).
19. Lampert, C. H.; Nickisch, H.; and Hanneling, S. 2014. Attribute-based classification for zero-shot visual object categorization. IEEE Transactions on Pattern Analysis and Machine Intelligence.
20. Liu, W.; Zamal, F. A.; and Ruths, D. 2012. Using social media to infer gender composition of commuter papulations. In Proceedings of the International AAAI Conference on We-blogs and Social Media (ICWSM) Workshop on When the City Meets the Citizen.
21. Liu, W.; Zamal, F. A.; and Ruths, D. 2013. What's in a name? using first names as features for gender inference in twitter. In Proceedings of the AAAI Spring Symposium.
22. Mislove, A.; Lehmann, S.; Ahn, Y.-Y; Onnela, J.-R; and Rosenquist, J. N. 2012. Understanding the demographics of twitter users. In Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM).
23. Pennacchiotti, M., and Popescu, A.-M. 2011. A machine learning approach to twitter user classification. In Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM).
24. Sahami, M., and Heilman, T. D. 2006. A web-based kernel function for measuring the similarity of short text snippets. In Proceedings of the International World Wide Web Conference (WWW).
25. Song, H.; Miao, C; and Shen, Z. 2011. Generating true relevance labels in chinese search engine using clickthrough data. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
26. Vaquero, D. A.; Feris, R. S.; Tran, D.; Brown, L.; Hampapur, A.; and Turk, M. 2009. Attribute-based people search in surveillance environments. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV).
27. Viola, P., and Jones, M. 2001. Rapid object detection using a boosted cascade of simple features. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
28. Yao, T; Mei, T.; Ngo, C.-W; and Li, S. 2013. Annotation for free: Video tagging by mining user search behavior. In Proceedings of the ACM International Conference on Multimedia (ACM MM).