• Alvo, M. and Cabilio, P. (1995). Testing order alternatives in the presence of incomplete data. Journal of the American Statistical Association, 90(431): 10151024.
  • Cox, I. J., Miller, M. L., Minka, T. P., Papathomas, T. V., and Yianilos, P. N. (2009). The Bayesian image retrieval system, PicHunter: theory, implementation and psychological experiments. IEEE Transactions on Image Processing, 9(1).
  • Fagin, R., Kumar, R., and Sivakumar, D. (2003). Comparing top-k lists. SIAM Journal of Discrete Mathematics, 17(1): 134160.
  • Fei-Fei, L., Fergus, R., and Perona, P. (2007). Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. Computer Vision and Image Understanding, 106(1): 5970.
  • Frese, T., Bouman, C. A., and Allebach, J. P. (1997). A methodology for designing image similarity metrics based on human visual system models. In Proceedings of SPIE, Human Vision and Electronic Imaging II, pages 472–483, San Jose, CA, United States.
  • Hollink, L., Schreiber, A., Wielinga, B., and Worring, M. (2004). Clasiffication of user image descriptions. International Journal of Human-Computer Studies, 61(5): 601626.
  • Huiskes, M. J. and Lew, M. S. (2008). The MIR Flickr retrieval evaluation. In Proceedings of the ACM Conference on Multimedia Information Retrieval (MIR), pages 3943, Vancouver, BC, Canada.
  • Jaimes, A., Jaimes, R., and Chang, S.-f. (2000). A conceptual framework for indexing visual information at multiple levels. In in proceedings of SPIE, Internet Imaging, pages 215, San Jose, CA, United States.
  • Jégou, H., Douze, M., and Schmid, C. (2008). Hamming embedding and weak geometric consistency for large scale image search. In Proceedings of the European Conference on Computer Vision (ECCV), volume 1, pages 304–317, Marseille, France.
  • Kennedy, L., Slaney, M., and Weinberger, K. (2009). Reliable tags using image similarity: mining specificity and expertise from large-scale multimedia databases. In Proceedings of the 1st workshop on Web-scale multimedia corpus (WSMC), pages 17–24, Beijing, China.
  • Krsukal, W. H. (1958). Ordinal measures of association. Journal of the American Statistical Association, 23(284): 814861.
  • Liu, H., Xie, X., Tang, X., Li, Z.-W., and Ma, W.-Y. (2004). Effective browsing of web image search results. In Proceedings of the ACM International Workshop on Multimedia Information Retrieval (MIR), pages 84–90, New York, NY, USA.
  • Makadia, A., Pavlovic, V., and Kumar, S. (2008). A new baseline for image annotation. In Proceedings of the European Conference on Computer Vision (ECCV), pages 316–329, Marseille, France.
  • Müller, H., Marchand-Maillet, S., and Pun, T. (2002). The truth about corel-evaluation in image retrieval. In Proceedings of the Conference on Image and Video Retrieval (CIVR), pages 38–49, London, UK.
  • Neumann, D. and Gegenfurtner, K. R. (2006). Image retrieval and perceptual similarity. ACM Transactions on applied perception, 3(1): 3147.
  • Ponce, J., Berg, T., Everingham, M., Forsyth, D. M. H., Lazebnik, S., Marszalek, M., Schmid, C., Russell, B., Torralba, A., Williams, C., Zhang, J., and Zisser-man, A. (2006). Dataset Issues in Object Recognition, pages 2948. Springer-Verlag.
  • Rodden, K., Basalaj, W., Sinclair, D., and Wood, K. (2001). Does organisation by similarity assist image browsing? In Proceedings of the ACM SIGCHI conference, Seattle, WA, United States.
  • Rogowitz, B. E., Frese, T., Smith, J. R., Bouman, C. A., and Kalin, E. (1998). Perceptual image similarity experiments. In Proceedings of the SPIE, Human Vision and electronic Imaging III, San Jose, CA, United States.
  • Russel, B. C., Torralba, A., Murphy, K. P., and Freeman, W. T. (2008). Labelme: a database and web-based annotation tool for image annotation. International Journal of Computer Vision (IJCV), 77(1-3): 157173.
  • Scassellati, B., Alexopoulos, S., and Flickner, M. (1994). Retrieving images by 2d shape: a comparison of computation methods with human perceptual judgments. In Proceedings if SPIE, Storage and Retrieval for Image and Video Databases, pages 2–14, San Jose, CA, United States.
  • Smeulders, A., Worring, M., Santini, S. A. G. and R. J. (2000). Content-based retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 22(12): 13491380.
  • Squire, D. M. and Pun, T. (1997). A comparison of human and machine assessments of image similarity for the organization of image databases. In Proceedings of the Scandinavian conference on image analysis, Lappeenranta, Finland.