R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo, Fast discovery of association rules, chapter 12 Advances in Knowledge Discovery and Data Mining, 1996.

D. Cai, X. He, Z. Li, W. Y. Ma, and J. R. Wen, Hierarchical clustering of WWW image search results using visual, textual and link information, Proceedings of the 12th annual ACM international conference on Multimedia , MULTIMEDIA '04, pp.952-959, 2004.
DOI : 10.1145/1027527.1027747

T. Calders, C. Rigotti, and J. Boulicaut, A Survey on Condensed Representations for Frequent Sets, Constraint-Based Mining and Inductive Databases, pp.64-80, 2005.
DOI : 10.1007/11615576_4

E. Chang, C. Li, J. Wang, P. Mork, and G. Wiederhold, Searching near-replicas of images via clustering, SPIE Multimedia Storage and Archiving Systems IV, 1999.

E. Y. Chang, J. Wang, C. Li, and G. Wiederhold, Rime: A replicated image detector for the world-wide web, Proc. of SPIE symposium of voice, video and data communications, pp.58-67, 1998.

O. Chum, J. Philbin, and A. Zisserman, Near Duplicate Image Detection: min-Hash and tf-idf Weighting, Procedings of the British Machine Vision Conference 2008, 2008.
DOI : 10.5244/C.22.50

M. Douze, H. Jégou, H. Sandhawalia, L. Amsaleg, and C. Schmid, Evaluation of GIST descriptors for web-scale image search, Proceeding of the ACM International Conference on Image and Video Retrieval, CIVR '09, pp.1-19, 2009.
DOI : 10.1145/1646396.1646421
URL : https://hal.archives-ouvertes.fr/inria-00394212

J. Foo, J. Zobel, and R. Sinha, Clustering near-duplicate images in large collections, Proceedings of the international workshop on Workshop on multimedia information retrieval , MIR '07, pp.21-30, 2007.
DOI : 10.1145/1290082.1290089

V. Ganti, R. Ramakrishnan, J. Gehrke, A. Powell, and J. French, Clustering large datasets in arbitrary metric spaces, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337), pp.502-511, 1999.
DOI : 10.1109/ICDE.1999.754966

F. Geerts, J. Goethals, and . Van-den-bussche, A tight upper bound on the number of candidate patterns, ICDM, pp.155-162, 2001.

K. Grauman and T. Darrell, The pyramid match kernel: discriminative classification with sets of image features, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.1458-1465, 2005.
DOI : 10.1109/ICCV.2005.239

H. Jégou, M. Douze, and C. Schmid, Product Quantization for Nearest Neighbor Search, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.1, pp.117-128, 2011.
DOI : 10.1109/TPAMI.2010.57

L. S. Kennedy and M. Naaman, Generating diverse and representative image search results for landmarks, Proceeding of the 17th international conference on World Wide Web , WWW '08, pp.297-306, 2008.
DOI : 10.1145/1367497.1367539

B. Larsen and C. Aone, Fast and effective text mining using linear-time document clustering, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '99, pp.16-22, 1999.
DOI : 10.1145/312129.312186
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.474.6500

W. Liu, Y. Jiang, J. Luo, and S. Chang, Noise resistant graph ranking for improved web image search, CVPR 2011, pp.849-856, 2011.
DOI : 10.1109/CVPR.2011.5995315

R. T. Ng, V. S. Lakshmanan, J. Han, and A. Pang, Exploratory mining and pruning optimizations of constrained associations rules, proceedings of ACM SIGMOD'98, pp.13-24, 1998.

D. Nistér and H. Stewénius, Scalable Recognition with a Vocabulary Tree, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.2161-2168, 2006.
DOI : 10.1109/CVPR.2006.264

F. Pan, G. Cong, A. K. Tung, Y. Yang, and M. J. Zaki, Carpenter, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.637-642, 2003.
DOI : 10.1145/956750.956832

N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, Discovering Frequent Closed Itemsets for Association Rules, proceedings of 7th International Conference on Database Theory (ICDT'99), volume 1540 of Lecture notes in artificial intelligence, pp.398-416, 1999.
DOI : 10.1007/3-540-49257-7_25
URL : https://hal.archives-ouvertes.fr/hal-00467747

J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, Object retrieval with large vocabularies and fast spatial matching, 2007 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2007.
DOI : 10.1109/CVPR.2007.383172

T. Quack, V. Ferrari, B. Leibe, and L. J. Van-gool, Efficient Mining of Frequent and Distinctive Feature Configurations, 2007 IEEE 11th International Conference on Computer Vision, pp.1-8, 2007.
DOI : 10.1109/ICCV.2007.4408906

G. Salton and C. Buckley, Term-weighting approaches in automatic text retrieval, Information Processing and Management, pp.513-523, 1988.
DOI : 10.1016/0306-4573(88)90021-0

J. Sivic and A. Zisserman, Video Google: a text retrieval approach to object matching in videos, Proceedings Ninth IEEE International Conference on Computer Vision, pp.1470-1477, 2003.
DOI : 10.1109/ICCV.2003.1238663

Y. Su, M. Allan, and F. Jurie, Improving object classification using semantic attributes, Procedings of the British Machine Vision Conference 2010, 2010.
DOI : 10.5244/C.24.26

T. Uno, T. Asai, Y. Uchida, and H. Arimura, An Efficient Algorithm for Enumerating Closed Patterns in Transaction Databases, proceedings of Discovery Science, pp.16-31, 2004.
DOI : 10.1007/978-3-540-30214-8_2

C. Wallraven, B. Caputo, and A. B. Graf, Recognition with local features: the kernel recipe, Proceedings Ninth IEEE International Conference on Computer Vision, pp.257-264, 2003.
DOI : 10.1109/ICCV.2003.1238351

B. Wang, Z. Li, M. Li, and W. Ma, Large-Scale Duplicate Detection for Web Image Search, 2006 IEEE International Conference on Multimedia and Expo, pp.353-356, 2006.
DOI : 10.1109/ICME.2006.262509

X. J. Wang, L. Zhang, X. R. Li, and W. Y. Ma, Annotating Images by Mining Image Search Results, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.11, pp.1919-1932, 2008.
DOI : 10.1109/TPAMI.2008.127

J. Yuan, M. Yang, and Y. Wu, Mining discriminative co-occurrence patterns for visual recognition, CVPR 2011, pp.2777-2784, 2011.
DOI : 10.1109/CVPR.2011.5995476