Diversity, assortment, dissimilarity, variety:A Study of diversity measures Using low level Features for video retrieval

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5478 LNCS, Issue , 2009, Pages 126-137

  Halvey, Martin ^a   Punitha, Punitha ^a   Hannah, David ^a   Villa, Robert ^a   Hopfgartner, Frank ^a   Goyal, Anuj ^a   Jose, Joemon M ^a  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DIVERSITY MEASURE; INTERACTIVE SEARCH; LOW-LEVEL FEATURES; N VALUE; RE-RANKING; SEARCH RESULTS; SIMILARITY-BASED METHODS; TRECVID; VIDEO RETRIEVAL; VIDEO SEARCH;

CONTENT BASED RETRIEVAL; INFORMATION SERVICES;

INFORMATION RETRIEVAL;

EID: 67650702302     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-00958-7_14     Document Type: Conference Paper

References (34)

1. Bradley, K., Smyth, B.: Improving Recommendation Diversity. In: Proceedings of the 12th National Conference on Artificial Intelligence and Cognitive Science, Maynooth, Ireland, pp. 75-84 (2001)
2. Bridge, D.: Diverse Product Recommendations Using an Expressive Language for Case Retrieval. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS, vol.2416, pp. 43-57. Springer, Heidelberg (2002)
3. Chen, Y., Wang, J.Z., Robert, K.: FRM CLUE: Cluster-Based Retrieval of Images by Unsupervised Learning. IEEE transactions on Image Processing 14(8) (2005)
4. Halvey, M., Keane, M.T.: Analysis of online video search and sharing. In: Proceedings of Hypertext 2007, pp. 217-226 (2007) (Pubitemid 350244527)
5. Hopfgartner, F.: Understanding Video Retrieval. VDM Verlag (2007)
6. Hu, R., Rueger, S., Song, D., Liu, H., Huang, Z.: Dissimilarity Measures for Content-based Image Retrieval. In: Proceedings of IEEE International Conference on Multimedia & Expo. (2008)
7. Jacobs, D.W., Weinshall, D., Gdalyahu, Y.: Classification with nonmetric distances: image retrieval and class representation. IEEE Trans. Pattern Anal. Mach. Intell. 22(6), 583-600 (2000) (Pubitemid 30917362)
8. Karypis, G.: Evaluation of Item-Based Top-N Recommendation Algorithms. In: Proceedings of the 10th International Conference of Information and Knowledge Management (CIKM), pp. 247-254 (2001) (Pubitemid 34974637)
9. Liu, H., Song, D., Rüger, S., Hu, R., Uren, V.: Comparing dissimilarity measures for content-based image retrieval. In: Li, H., Liu, T., Ma, W.-Y., Sakai, T., Wong, K.-F., Zhou, G. (eds.) AIRS 2008. LNCS, vol.4993, pp. 44-50. Springer, Heidelberg (2008)
10. McSherry, D.: Diversity-Conscious Retrieval. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS, vol.2416, pp. 219-233. Springer, Heidelberg (2002)
11. Over, P., Awad, G., Kraaij, W., Smeaton, A.F.: TRECVID 2007-Overview. In: Proceedings of TRECVID 2007 (2007)
12. Smeulders, A.W., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-Based Image Retrieval at the End of the Early Years. IEEE Trans. Pattern Anal. Mach. Intell. 22(12), 1349-1380 (2000) (Pubitemid 32088465)
13. Smyth, B., McClave, P.: Similarity vs. Diversity. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS, vol.2080, pp. 347-361. Springer, Heidelberg (2001)
14. Soboroff, I.: Overview of the TREC 2004 novelty track. In: Proceedings of the 13th Text Retrieval Conference (TREC) (2004)
15. Song, K., Tian, Y., Gao, W., Huang, T.: Diversifying the image retrieval results. In: MULTIMEDIA 2006: Proceedings of the 14th annual ACM international conference on Multimedia, pp. 707-710 (2006)
16. Zhang, B., Li, H., Liu, Y., Ji, L., Xi, W., Fan, W., Chen, Z., Ma, W.-Y.: Improving Web Search Results Using Affinity Graph. In: Proceedings of the 28th International SIGIR Conference on Research and Development in Information Retrieval, pp. 504-511 (2005)
17. Ziegler, C.-N., McNee, S.M., Konstan, J.A., Lausen, G.: Improving Recommendation Lists through topic Diversification. In: Proceedings of the 14th International Conference in the World Wide Web, pp. 22-32 (2005)
18. van Zwol, R., Murdock, V., Garcia Pueyo, L., Ramirez, G.: Diversifying Image Search with User Generated Content. In: Proceedings of 1st ACM international conference on Multimedia Information Retrieval (2008)
19. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell. 22(12), 1349-1380 (2000) (Pubitemid 32088465)
20. Duygulu, P., Barnard, K., de Freitas, J.F.G., Forsyth, D.A.: Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol.2353, pp. 97-112. Springer, Heidelberg (2002)
21. Lavrenko, V., Manmatha, R., Jeon, J.: A model for learning the semantics of pictures. In: Thrun, S., Saul, L., Schölkopf, B. (eds.) Advances in Neural Information Processing Systems, vol.16. MIT Press, Cambridge (2003)
22. Feng, S., Manmatha, R., Lavrenko, V.: Multiple bernoulli relevance models for image and video annotation. In: CVPR 2004 Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 27 June-2 July 2004, vol.2, pp. II-1002-II-1009 (2004)
23. Blei, D.M., Jordan, M.I.: Modeling annotated data. In: SIGIR 2003: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pp. 127-134. ACM Press, New York (2003)
24. Carneiro, G., Chan, A.B., Moreno, P.J., Vasconcelos, N.: Supervised learning of semantic classes for image annotation and retrieval. TPAMI: IEEE Transactions on Pattern Analysis and Machine Intelligence 29(3), 394-410 (2007) (Pubitemid 46336416)
25. Vasconcelos, N., Lippman, A.: Learning mixture hierarchies. In: Proceedings of Neural Information Processing Systems, vol.11, pp. 606-612. MIT Press, Cambridge (1998)
26. Jordan, M.I., Ghahramani, Z., Jaakkola, T.S., Saul, L.K.: An introduction to variational methods for graphical models. In: Proceedings of the NATO Advanced Study Institute on Learning in graphical models, Norwell, MA, USA, pp. 105-161. Kluwer Academic Publishers, Dordrecht (1998)
27. Attias, H.: A variational bayesian framework for graphical models. In: In Advances in Neural Information Processing Systems, vol.12, pp. 209-215. MIT Press, Cambridge (2000)
28. Yavlinsky, A., Schofield, E.J., Rüger, S.: Automated image annotation using global features and robust nonparametric density estimation. In: Leow, W.-K., Lew, M., Chua, T.-S., Ma, W.-Y., Chaisorn, L., Bakker, E.M. (eds.) CIVR 2005. LNCS, vol.3568, pp. 507-517. Springer, Heidelberg (2005)
29. Jeon, J., Lavrenko, V., Manmatha, R.: Automatic image annotation and retrieval using cross-media relevance models. In: SIGIR 2003: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pp. 119-126. ACM Press, New York (2003)
30. Magalhaes, J., Rüger, S.: Information-theoretic semantic multimedia indexing. In: CIVR 2007: Proceedings of the 6th ACM international conference on Image and video retrieval, pp. 619-626. ACM, New York (2007) (Pubitemid 350229680)
31. Figueiredo, M., Jain, A.: Unsupervised learning of finite mixture models. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(3), 381-396 (2002) (Pubitemid 35289353)
32. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)
33. Vasconcelos, N.: Bayesian Models for Visual Information Retrieval. PhD thesis, Massachusetts Institute of Technology (June 2000)
34. Nasios, N., Bors, A.: Variational learning for gaussian mixture models. IEEE Transactions on Systems, Man, and Cybernetics, Part B 36(4), 849-862 (2006) (Pubitemid 44178154)