.. État-de-l-'art, 39 3.2.1 La spécication des requêtes, 40 3.2.2.1 Structures statiques hiérarchiques . . . . . . . . . . 42 3.2.2.2 Réseaux statiques . . . . . . . . . . . . . . . . . . . 42

.. Retour-de-pertinence-À-court-terme-dans-notre-système......-le-contenu, 52 3.3.1 Retour de pertinence basé sur les groupes pour la recherche par, p.52

/. Interaction-pour-la-recherche-mixte-texte and .. , 69 3.5.1 Notre technique de retour de pertinence pour la recherche mixte texte/images, p.69

K. La-représentation-sac-de, Représentation visuelle de mots textuels), p.89

.. Protocole-d-'expérimentation, 118 5.3.1 Validations croisées pour l'expérimentation, p.120

. Méthode-d-'évaluation-pseudo-interactive......., 121 5.3.3.1 Simulation de connaissances des utilisateurs/experts 122 5.3.3.2 Simulation de la spécication de la requête

.. La-quantité-de-connaissances, 126 5.4.2.1 Le nombre de concepts appris

A. Boucher, Text Retrieval Relevance Feedback Techniques for Bag of Words Model in CBIR, International Conference on Machine Learning and Pattern Recognition, 2009.

V. Nhu, J. Nguyen, S. Ogier, A. Tabbone, and . Boucher, Region-Based Semi-automatic Annotation Using the Bag of Words Representation of the Keywords, Proceedings of the 5th International Conference on Image and Graphics (ICIG) 2009), pp.422-427, 2009.

M. Ogier, Using SR-tree in a Content-based and Location-based Image Retrieval System, Proceedings of the 5th International Conference on Computer Vision Theory and Applications(VISAPP), p.491494, 2010.

N. Van-nguyen, J. Ogier, S. Tabbone, and A. Boucher, Clusters-Based Relevance Feedback for CBIR: A Combination of Query Movement and Query Expansion, 2010 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future (RIVF), p.422427, 2010.
DOI : 10.1109/RIVF.2010.5633118

V. Nhu, J. Nguyen, S. Ogier, A. Tabbone, and . Boucher, Cluster-based Relevance Feedback for CBIR : A combination of query point movement and query expansion, Journal of Ambient Intelligence and Humanized Computing, 2011.

]. G. Bibliographie, T. V. Aggarwal, S. Ashwin, and . Ghosal, An image retrieval system with automatic query modication, IEEE Transactions on Multimedia, vol.4, issue.2, pp.201-214, 2002.

W. Andrews, A. Putz, and . Nussbaumer, The Hierarchical Visualisation System (HVS), 2007 11th International Conference Information Visualization (IV '07), p.257262, 2007.
DOI : 10.1109/IV.2007.112

C. T. Aslandogan and . Yu, Techniques and systems for image and video retrieval, IEEE Transactions on Knowledge and Data Engineering, vol.11, issue.1, p.5663, 1999.
DOI : 10.1109/69.755615

]. Barnard, P. Duygulu, D. Forsyth, D. M. Nando-de-freitas, . Blei et al., Matching words and pictures, The Journal of Machine Learning Research, vol.3, p.11071135, 2003.

T. Herbert-bay, L. Tuytelaars, and . Van-gool, SURF : Speeded Up Robust Features, Ale² Leonardis, p.162, 2006.

B. Benjamin and . Bederson, PhotoMesa : a zoomable image browser using quantum treemaps and bubblemaps, Bibliographie Computer Vision ECCV 2006 UIST '01 : Proceedings of the 14th annual ACM symposium on User interface software and technology, pp.404417-7180, 2001.

M. Belkhatir, P. Mulhem, and Y. Chiaramella, A Conceptual Image Retrieval Architecture Combining Keyword-Based Querying with Transparent and Penetrable Query-by-Example, Image and Video Retrieval, p.528539, 2005.
DOI : 10.1007/11526346_56

A. C. Berg, T. L. Berg, and J. Malik, Shape Matching and Object Recognition Using Low Distortion Correspondences, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), p.2633, 2005.
DOI : 10.1109/CVPR.2005.320
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.8044

I. Mounia-lalmas and J. Jose, Andreas Rauber, Fabrizio Sebastiani et Ingo Frommholz, editeurs, Research and Advanced Technology for Digital Libraries, Lecture Notes in Computer Science, vol.6273, p.429

M. Carey, C. Daniel, . Heesch, M. Stefan, G. Rüger et al., Info navigator : A visualization tool for document searching and browsing Supervised Learning of Semantic Classes for Image Annotation and Retrieval, Proc. of the Intl. Conf. on Distributed Multimedia Systems (DMS), pp.2328-394410, 2003.

S. Carson, H. Belongie, J. Greenspan, and . Malik, Blobworld : Image Segmentation Using Expectation-Maximization and Its Application to Image Querying Pulla Chandrika et C. V. Jawahar. Multi modal semantic indexing for image retrieval, CIVR '10 : Proceedings of the ACM International Conference on Image and Video Retrieval, pp.10261038-342349, 2002.

]. E. Chang, K. Goh, G. Sychay, and G. Wu, CBSA: content-based soft annotation for multimodal image retrieval using bayes point machines, IEEE Transactions on Circuits and Systems for Video Technology, p.2638, 2003.
DOI : 10.1109/TCSVT.2002.808079

W. Chang, H. Lin, and . Chen, A Corpus-Based Relevance Feedback Approach to Cross-Language Image Retrieval, Accessing Multilingual Information Repositories, p.592601, 2006.
DOI : 10.1007/11878773_66

C. and H. Chen, Using an Image-Text Parallel Corpus and the Web for Query Expansion in Cross-Language Image Retrieval, p.504511, 2008.

]. J. Chen, C. A. Bouman, and J. C. Dalton, Hierarchical Browsing and Search of Large Image Databases, IEEE Transactions on Image Processing, vol.9, issue.3, p.442455, 2000.

]. Y. Chen, J. Z. Wang, and R. Krovetz, CLUE : cluster-based retrieval of images by unsupervised learning, IEEE Transactions on Image Processing, vol.14, issue.8, p.11871201, 2005.

]. Lim, SnapToTell Accès ubiquitaire à de l'information multimédia à partir d'un téléphone portable, COnférence en Recherche d'Infomations et Applications -CORIA2005, p.245260, 2005.

]. Chevallet, J. Lim, and M. Leong, Object identication and retrieval from ecient image matching. Snap2Tell with the STOIC dataset, Inf. Process. Manage, vol.43, issue.2, p.515530, 2007.

]. K. Cox, Information retrieval by browsing, Proceedings of The Fifth International Conference on New Information Technology, pp.69-80, 1992.

]. Datta, D. Joshi, J. Li, and J. Z. Wang, Image retrieval, ACM Computing Surveys, vol.40, issue.2, p.160, 2008.
DOI : 10.1145/1348246.1348248

]. P. Duygulu, K. Barnard, J. F. De-freitas, and D. A. Forsyth, Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary, ECCV '02 : Proceedings of the 7th European Conference on Computer Vision-Part IV, p.97112, 2002.
DOI : 10.1007/3-540-47979-1_7

C. A. Hugo-jair-escalante, L. E. Hérnadez, M. Sucar, and . Montes, Late fusion of heterogeneous methods for multimedia image retrieval, Proceeding of the 1st ACM international conference on Multimedia information retrieval, MIR '08, p.172179, 2008.

[. Fei-fei, R. Fergus, and P. Perona, One-shot learning of object categories, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.4, p.594611, 2006.
DOI : 10.1109/TPAMI.2006.79

. Fei-fei, Li Fei-Fei. Tutorial on Bag-of-words models, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007.

]. S. Feng, R. Manmatha, and V. Lavrenko, Multiple Bernoulli relevance models for image and video annotation, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., p.10021009, 2004.
DOI : 10.1109/CVPR.2004.1315274

M. Ferecatu, N. Boujemaa, M. Crucianu-]-myron-flickner, H. S. Sawhney, J. Ashley et al., Semantic interactive image retrieval combining visual and conceptual content description Query by Image and Video Content : The QBIC System, Multimedia Systems IEEE Computer, vol.13, issue.28 9, pp.309322-2332, 1995.

]. Fu, L. Cao, G. Guo, and T. S. Huang, Multiple feature fusion by subspace learning, Proceedings of the 2008 international conference on Content-based image and video retrieval, CIVR '08, p.127134, 2008.
DOI : 10.1145/1386352.1386373

]. G. Furnas, Generalized sheye views, SIGCHI Bull, vol.17, issue.4, p.1623, 1986.

]. R. Haralick, D. , and K. Shanmugam, Textural features for image classication, IEEE Transactions on Systems, Man, and Cybernetics, vol.3, p.610621, 1973.

E. Susan-havre, P. Hetzler, L. Whitney, and . Nowell, ThemeRiver : Visualizing Thematic Changes in Large Document Collections, IEEE Transactions on Visualization and Computer Graphics, vol.8, issue.1, p.920, 2002.

H. Jingrui-he, M. Tong, H. Li, C. Zhang, and . Zhang, Mean version space : a new active learning method for contentbased image retrieval, MIR '04 : Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval, p.1522, 2004.

A. Daniel-heesch, S. Yavlinsky, and . Rüger, NNk networks and automated annotation for browsing large image collections from the world wide web, MULTIMEDIA '06 : Proceedings of the 14th annual ACM international conference on Multimedia, p.493494, 2006.

E. Hörster, R. Lienhart, and M. Slaney, Continuous visual vocabulary modelsfor pLSA-based scene recognition, CIVR '08 : Proceedings of the 2008 international conference on Content-based image and video retrieval, p.319328, 2008.

]. Huang, S. R. Kumar, M. Mitra, W. Zhu, and R. Zabih, Image Indexing Using Color Correlograms. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, p.762, 1997.

J. Mark, M. S. Huiskes, and . Lew, Performance evaluation of relevance feedback methods, CIVR '08 : Proceedings of the 2008 international conference on Content-based image and video retrieval, p.239248, 2008.

D. F. Bibliographie, S. M. Huynh, P. Drucker, C. Baudisch, and . Wong, Time quilt : scaling up zoomable photo browsers for large, unstructured photo collections, CHI '05 extended abstracts on Human factors in computing systems, CHI '05, 2005.

A. Jaimes, N. Sebe, and D. Gatica-perez, Humancentered computing : a multimedia perspective, MULTIMEDIA '06 : Proceedings of the 14th annual ACM international conference on Multimedia, p.855864, 2006.

K. Anil, R. C. Jain, and . Dubes, Algorithms for clustering data, 1988.

]. J. Jeon, V. Lavrenko, and R. Manmatha, Automatic image annotation and retrieval using cross-media relevance models, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval , SIGIR '03, p.119126, 2003.
DOI : 10.1145/860435.860459

J. Sun, . Li, and . Hong-hui, On interactive browsing of large images, IEEE Transactions on Multimedia, vol.5, issue.4, pp.581-590, 2003.

J. Xiangyu and J. C. French, Improving image retrieval eectiveness via multiple queries, MMDB '03 : Proceedings of the 1st ACM international workshop on Multimedia databases, p.8693, 2003.

F. Jing, M. Li, H. Zhang, and B. Zhang, Relevance Feedback for Keyword and Visual Feature-Based Image Retrieval, Image and Video Retrieval, p.648648, 2004.
DOI : 10.1007/978-3-540-27814-6_52

]. Jones, S. Walker, and S. E. Robertson, A probabilistic model of information retrieval : development and comparative experiments, Inf. Process. Manage, vol.36, issue.6, p.779808, 2000.

H. Lim, Sihem Nouarah Merah Joo-Hwee Lim Jean-Pierre Chevallet. SnapToTell : Ubiquitous Information Access from Camera, Workshop on Mobile and Ubiquitous Information Access (MUIA04), 2004.

]. T. Kadir, A. Zisserman, and J. M. Brady, An Ane Invariant Salient Region Detector, European Conference on Computer Vision, 2004.

]. S. Karthik and C. V. Jawahar, Discriminative relevance feedback with virtual textual representation for ecient image retrieval, p.309314, 2006.

D. Kim, C. Chung, and K. Barnard, Relevance feedback using adaptive clustering for image similarity retrieval On nding the number of clusters, J. Syst. Softw. Pattern Recogn. Lett, vol.78, issue.20 4, pp.923-405416, 1999.

H. Lai, N. Van-nguyen, A. Boucher, and J. Ogier, Using SR-tree in a Content-based and Location-based Image Retrieval System, VISAPP-International Conference on Computer Vision Theory and Applications, p.491494, 2010.

]. C. Lau, D. Tjondronegoro, J. Zhang, S. Geva, and Y. Liu, Fusing Visual and Textual Retrieval Techniques to Eectively Search Large Collections of Wikipedia Images, Norbert Fuhr, Mounia Lalmas et Andrew Trotman, editeurs, Comparative Evaluation of XML Information Retrieval Systems, p.345357, 2007.

]. V. Lavrenko, R. Manmatha, and J. Jeon, A Model for Learning the Semantics of Pictures, Advances in Neural Information Processing Systems (NIPS), p.553560, 2004.

]. Li and P. Perona, A Bayesian Hierarchical Model for Learning Natural Scene Categories, CVPR '05 : Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition 168, 2005.

]. , L. , and J. Z. Wang, Real-Time Computerized Annotation of Pictures, IEEE Trans. Pattern Anal. Mach. Intell, vol.30, p.9851002, 2008.

]. Lienhart, S. Romberg, and E. Hörster, Multilayer pLSA for multimodal image retrieval, Proceeding of the ACM International Conference on Image and Video Retrieval, CIVR '09, p.18, 2009.
DOI : 10.1145/1646396.1646408

]. Lin, Y. Chang, and H. Chen, Integrating textual and visual information for cross-language image retrieval: A trans-media dictionary approach, Information Processing & Management, vol.43, issue.2, p.488502, 2007.
DOI : 10.1016/j.ipm.2006.07.015

H. Liu, D. Song, S. Rüger, R. Hu, and V. Uren, Comparing Dissimilarity Measures for Content-Based Image Retrieval, AIRS'08 : Proceedings of the 4th Asia information retrieval conference on Information retrieval technology, p.4450, 2008.
DOI : 10.1007/978-3-540-68636-1_5

]. Liu, K. A. Hua, K. Vu, and N. Yu, Fast Query Point Movement Techniques for Large CBIR Systems, IEEE Trans. on Knowl. and Data Eng, vol.21, issue.5, p.729743, 2009.

G. David and . Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, p.91110, 2004.

A. Makadia, V. Pavlovic, and S. Kumar, Baselines for Image Annotation, International Journal of Computer Vision, vol.58, issue.1, p.88105, 2010.
DOI : 10.1007/s11263-010-0338-6
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.9205

]. S. Mallat, A Theory for Multiresolution Signal Decomposition : The Wavelet Representation, IEEE Trans. Pattern Anal. Mach. Intell, vol.11, issue.7, p.674693, 1989.

]. J. Matas, O. Chum, M. Urban, and T. Pajdla, Robust wide baseline stereo from maximally stable extremal regions, Proceedings of British Machine Vision Conference, p.384393, 2002.
DOI : 10.5244/c.16.36
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.671.8241

]. Metzler and R. Manmatha, An Inference Network Approach to Image Retrieval, CIVR04-Proceedings of the 2004 international conference on Content-based image and video retrieval, p.4250, 2004.
DOI : 10.1007/978-3-540-27814-6_9

M. Krystian, C. Schmid-rahman, M. Antani, S. Long, L. Demner-fushman et al., A performance evaluation of local descriptors Lecture notes in computer science. rst miccai international workshop on medical content-based retrieval for clinical decision support (mcbr-cds 2009) ; part of the 12th international conference on medical image computing and computer assisted interventio february 2010, chapitre Multi-Modal Query Expansion Based On Local Analysis For Medical Image Retrieval, Ane Region Detectors. Int. J. Comput. Vision, pp.4372-16151630, 2005.

]. Monay and D. Gatica-perez, On image auto-annotation with latent space models, Proceedings of the eleventh ACM international conference on Multimedia , MULTIMEDIA '03, p.275278, 2003.
DOI : 10.1145/957013.957070

]. Y. Mori, H. Takahashi, and R. Oka, Image-to-word transformation based on dividing and vector quantizing images with words, Proc. First Int'l Workshop Multimedia Intelligent Storage and Retrieval Management, 1999.

H. Muller, S. Marchand-maillet, and T. Pun, The Truth about Corel - Evaluation in Image Retrieval, Image and Video Retrieval, p.3849, 2002.
DOI : 10.1007/3-540-45479-9_5

]. A. Natsev and J. R. Smith, Active selection for multi-example querying by content, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698), p.445448, 2003.
DOI : 10.1109/ICME.2003.1220950

. Paul, M. R. Natsev, J. Naphade, and . Te²i‚, Learning the semantics of multimedia queries and concepts from a small number of examples, MULTIMEDIA '05 : Proceedings of the 13th annual ACM international conference on Multimedia, p.598607, 2005.

M. Ortega-binderberger and S. Mehrotra, Relevance feedback techniques in the MARS image retrieval system, Multimedia Systems, vol.9, issue.6, p.535547, 2004.
DOI : 10.1007/s00530-003-0126-z

N. E. Pham, J. Maillot, J. Lim, and . Chevallet, Latent semantic fusion model for image retrieval and annotation, Proceedings of the sixteenth ACM conference on Conference on information and knowledge management , CIKM '07, p.439444, 2007.
DOI : 10.1145/1321440.1321503
URL : https://hal.archives-ouvertes.fr/hal-00953882

J. Foliguet, P. H. Gony, and . Gosselin, FReBIR : An image retrieval system based on fuzzy region matching, Computer Vision and Image Understanding, vol.113, p.693707, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00519447

]. J. Rocchio, Relevance feedback in information retrieval, pp.313-323, 1971.

K. Rodden, W. Basalaj, D. Sinclair, and K. Wood, Does organisation by similarity assist image browsing?, Proceedings of the SIGCHI conference on Human factors in computing systems , CHI '01, 2001.
DOI : 10.1145/365024.365097

]. G. Salton, A. Wong, C. S. Yang-simone-santini, A. Gupta, and R. Jain, A vector space model for automatic indexing Emergent Semantics through Interaction in Image Databases, Commun. ACM IEEE Trans. on Knowl. and Data Eng, vol.18, issue.13 3, pp.613620-337351, 1975.

]. Sclaro, M. L. Cascia, and S. Sethi, Unifying textual and visual cues for content-based image retrieval on the World Wide Web, 1999.

]. E. Shechtman and M. Irani, Matching Local Self-Similarities across Images and Videos Ben Shneiderman. The Eyes Have It : A Task by Data Type Taxonomy for Information Visualizations, IEEE Computer Society Conference on Computer Vision and Pattern Recognition VL '96 : Proceedings of the 1996 IEEE Symposium on Visual Languages, pp.18-336, 1996.

]. J. Sivic and A. Zisserman, Ecient Visual Search for Objects in Videos, Proceedings of the IEEE, p.548566, 2008.

. Smeulders, W. M. Arnold, M. Smeulders, S. Worring, A. Santini et al., Content-based image retrieval at the end of the early years, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.12, p.13491380, 2000.
DOI : 10.1109/34.895972

G. M. Cees, M. Snoek, and . Worring, Multimodal Video Indexing : A Review of the State-of-the-art, Multimedia Tools Appl, vol.25, issue.1, p.535, 2005.

D. Stan, K. Ishwar, M. M. Sethi-seyed, J. A. Tahaghoghi, H. E. Thom et al., eID : a system for exploration of image databases Multiple Example Queries in Content-Based Image Retrieval, SPIRE 2002 : Proceedings of the 9th International Symposium on String Processing and Information Retrieval, pp.335361-227240, 2002.

]. H. Tamura, T. Mori, and T. Yamawaki, Textural Features Corresponding to Visual Perception. Systems, Man and Cybernetics, IEEE Transactions on, vol.8, p.460473, 1978.

D. Tao, X. Tang, X. Li, X. Wu, A. Theobald et al., Asymmetric Bagging and Random Subspace for Support Vector Machines-Based Relevance Feedback in Image Retrieval The Index-Based XXL Search Engine for Querying XML Data with Relevance Ranking, EDBT '02 : Proceedings of the 8th International Conference on Extending Database Technology, pp.10881099-477495, 2002.

B. Qi-tian, T. S. Moghaddam, and . Huang, Display Optimization for Image Browsing, MDIC '01 : Proceedings of the Second International Workshop on Multimedia Databases and Image Communication, p.167178, 2001.

]. Tieu and P. Viola, Boosting Image Retrieval, International Journal of Computer Vision, vol.56, p.1736, 2004.

]. Tirilly, V. Claveau, and P. Gros, Language modeling for bag-of-visual words image categorization, Proceedings of the 2008 international conference on Content-based image and video retrieval, CIVR '08, p.249258, 2008.
DOI : 10.1145/1386352.1386388
URL : https://hal.archives-ouvertes.fr/hal-00811922

S. Tollari, P. Mulhem, M. Ferecatu, H. Glotin, M. Detyniecki et al., A Comparative Study of Diversity Methods for Hybrid Text and Image Retrieval Approaches, CLEF, p.585592, 2008.
DOI : 10.1007/978-3-642-04447-2_72
URL : https://hal.archives-ouvertes.fr/hal-00581664

R. S. Torres, C. G. Silva, C. B. Medeiros, V. Heloisa, and . Rocha, Visual structures for image browsing, Proceedings of the twelfth international conference on Information and knowledge management , CIKM '03, p.4955, 2003.
DOI : 10.1145/956863.956874

T. Tuytelaars, L. Van-gool-jana-urban-et-joemon, and M. Jose, Matching Widely Separated Views Based on Evidence Combination for Multi- Point Query Learning in Content-Based Image Retrieval, ISMSE '04 : Proceedings of the IEEE Sixth International Symposium on Multimedia Software Engineering, pp.6185-583586, 2004.

S. Naquet and . Ullman, Object Recognition with Informative Features and Linear Classication, ICCV '03 : Proceedings of the Ninth IEEE International Conference on Computer Vision, p.281, 2003.

J. Villena-román, S. Lana-serrano, and J. González, Merging Textual and Visual Strategies to Improve Medical Image Retrieval, Advances in Multilingual and Multimodal Information Retrieval de Lecture Notes in Computer Science, p.593596, 2007.

]. Vinokourov, D. R. Hardoon, and J. Shawe-taylor, Learning the semantics of multimedia content with application to web image retrieval and classication, Fourth International Symposium on Independent Component Analysis and Blind Source Separation, 2003.

]. J. Vogel and B. Schiele, On Performance Characterization and Optimization for Image Retrieval, Anders Heyden, p.173, 2006.
DOI : 10.1007/3-540-47979-1_4

P. Nielsen, J. Wang, G. Li, and . Wiederholdy, SIMPLIcity : Semanticssensitive Integrated Matching for Picture LIbraries, Advances in Visual Information Systems, volume 1929 de Lecture Notes in Computer Science, pp.5155-171193, 2000.

]. Wang, L. Liu, and L. Khan, Automatic image annotation and retrieval using subspace clustering algorithm, Proceedings of the 2nd ACM international workshop on Multimedia databases , MMDB '04, p.100108, 2004.
DOI : 10.1145/1032604.1032621

]. Wang, H. Fang, and C. Zhai, A study of methods for negative relevance feedback, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '08, p.219226, 2008.
DOI : 10.1145/1390334.1390374

. Jr and . Ward, Hierarchical grouping to optimize an objective function Semi-Automatic Image Annotation, IN- TERACT2001, 8th IFIP TC.13 Conference on Human-Computer Interaction, pp.236244-326333, 1963.

]. T. Westerveld, Image retrieval : Content versus context, Content-Based Multimedia Information Access, RIAO, 2000.

Y. Keiji and K. Barnard, Image region entropy : a measure of "visualness" of web images associated with one concept, Proceedings of 174, 2005.

Y. Yang, A. G. Jiang, C. Hauptmann, and . Ngo, Evaluating bag-of-visual-words representations in scene classication, MIR '07 : Proceedings of the international workshop on Workshop on multimedia information retrieval, 2007.

A. Yavlinsky, E. Schoeld, and S. Rüger, Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation, Image and Video Retrieval, p.507517, 2005.
DOI : 10.1007/11526346_54

]. Yee, D. Fisher, R. Dhamija, and M. Hearst, Animated Exploration of Dynamic Graphs with Radial Layout, Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01), 2001.

M. Zhang, W. Li, H. Ma, and . Zhang, A Probabilistic Semantic Model for Image Annotation and Multi-Modal Image Retrieva, ICCV '05 : Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05), p.846851, 2005.

W. I. Zhao and . Grosky, Narrowing the semantic gap -improved text-based web document retrieval using visual features, IEEE Transactions on Multimedia, vol.4, issue.2, p.189200, 2002.