Contextual internet multimedia advertising

Proceedings of the IEEE

Volumn 98, Issue 8, 2010, Pages 1416-1433

  Mei, Tao ^a   Hua, Xian Sheng ^a  

^a MICROSOFT RESEARCH ASIA   (China)

Author keywords

Computer vision; Contextual advertising; Multimedia advertising; Survey

Indexed keywords

COMPUTER VISION; HUMAN COMPUTER INTERACTION; SURVEYING; SURVEYS; WEBSITES;

COMPUTER HUMAN INTERACTION; CONTEXTUAL ADVERTISINGS; INSERTION POSITION; INTERNET DELIVERY; INTERNET MULTIMEDIA; MULTIMEDIA ADVERTISINGS; MULTIMEDIA RETRIEVAL; ONLINE ADVERTISING;

MARKETING;

EID: 77954853101     PISSN: 00189219     EISSN: None     Source Type: Journal    
DOI: 10.1109/JPROC.2009.2039841     Document Type: Conference Paper

References (124)

1. AdSense. [Online], http://www.google.com/adsense/
2. AdWords. [Online] http://adwords.google.com/, AdWords. [Online]
3. L. Ahn and L. Dabbish, B Labeling images with a computer game, [in Proc. SIGCHI Conf. Human Factors Comput. Syst., 2004, pp. 319-326.
4. A. Anagnostopoulos, A. Z. Border, E. Gabrilovich, V. Josifovski, and L. Riedel, BJust-in-time contextual advertising, [in Proc. ACM Conf. Inform. Knowl. Management, 2007, pp. 331-340.
5. AOL. [Online]. Available: http://www.aol.com/
6. N. Archak, A. Ghose, and P. Ipeirotis, BShow me the money: Deriving the pricing power of product features by mining consumer reviews, [in Proc. ACM Conf. Knowl. Discovery and Data Mining, 2007.
7. R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. Reading, MA: Addison Wesley, 1999.
8. S. Boll, BMultitubeVWhere multimedia and web 2.0 could meet, [IEEE Multimedia, vol. 14, no. 1, pp. 9-13, Jan.-Mar. 2007.
9. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge, U.K.: Cambridge University Press, 2004.
10. BritePic. [Online]. Available: http://www. britepic.com/
11. A. Broder, M. Fontoura, V. Josifovski, and L. Riedel, BA semantic approach to contextual advertising, [in Proc. ACM SIGIR Conf. Res. and Dev. Inform. Retrieval, 2007.
12. D. Cai, S. Yu, J.-R. Wen, and W.-Y. Ma, BExtracting content structure for web pages based on visual representation, [in Fifth Asia Pacific Web Conf., 2003.
13. D. Cai, S. Yu, J.-R. Wen, and W.-Y. Ma, "VIPS: A vision-based page segmentation algorithm, " Microsoft Technical Report (MSR-TR-2003-79), 2003.
14. D. Chakrabarti, D. Agarwal, and V. Josifovski, BContextual advertising by combining relevance with click feedback, [in Proc. Int. WWW Conf., 2008, pp. 417-426.
15. C.-H. Chang, K.-Y. Hsieh, M.-C. Chung, and J.-L. Wu, BViSA: Virtual spotlighted advertising, [in Proc. ACM Multimedia, 2008, pp. 837-840.
16. P. Chatterjee, D. L. Hoffman, and T. P. Novak, BModeling the clickstream: Implications for web-based advertising efforts, [Marketing Science, vol. 22, no. 4, pp. 520-541, 2003.
17. X. Chen and H.-J. Zhang, BText area detection from video frames, [in Proc. IEEE Pacific Rim Conf. Multimedia, 2001, pp. 222-228.
18. Y.-Y. Chuang, BA collaborative benchmark for region of interest detection algorithms, [in Proc. IEEE Conf. Comput. Vision Pattern Recognit., 2009.
19. C. Colombo, A. D. Bimbo, and P. Pala, BRetrieval of commercials by semantic content: The semiotic perspective, [Multimedia Tools and Applications, vol. 13, pp. 93-118, 2001.
20. K. S. Coulter, BThe effects of affective response to media context on advertising evaluations, [J. Adv., vol. XXVII, no. 4, pp. 41-51, 1998.
21. H. Cui, J.-R. Wen, J.-Y. Nie, and W.-Y. Ma, BProbabilistic query expansion using query logs, [in Proc. Int. Conf. WWW, 2002, pp. 325-332.
22. H. Dai, L. Zhao, Z. Nie, J.-R. Wen, L. Wang, and Y. Li, BDetecting online commercial intention, [in Proc. Int. WWW Conf., 2006.
23. R. Datta, D. Joshi, J. Li, and J. Z. Wang, BImage retrieval: Ideas, influences, and trends of the new age, [ACM Comput. Surveys, vol. 40, no. 65, 2008.
24. DoubleClick. [Online]. Available: http://www.doubleclick.com/
25. L.-Y. Duan, J. Wang, Y. Zheng, J. S. Jin, H. Lu, and C. Xu, BSegmentation, categorization, and identification of commercials from TV streams using multimodal analysis, [in Proc. ACM Multimedia, 2006, pp. 201-210.
26. L.-Y. Duan, J. Wang, Y. Zheng, H. Lu, and J. S. Jin, BDigesting commercial clips from TV streams, [IEEE MultiMedia, vol. 15, no. 1, pp. 28-41, 2008.
27. L. Fei-Fei, R. Fergus, and P. Perona, BOne-shot learning of object categories, [IEEE Trans. Pattern Anal. Mach. Intell., vol. 128, no. 4, pp. 594-611, 2006.
28. T. S. Feltham and S. J. Arnold, BProgram involvement and ad/program consistency as moderators of program context effects, [J. Consumer Psychology, vol. 3, no. 1, pp. 51-77, 1994.
29. R. J. Gerrig and P. G. Zimbardo, Psychology and Life (16 Edition). Boston, MA: Allyn & Bacon, 2001.
30. Google Image Labeler. [Online]. Available: http://images.google.com/ imagelabeler/; http://images.google.com/imagelabeler/
31. J. Guo, T. Mei, F. Liu, and X.-S. Hua, BAdOn: An intelligent overlay video advertising system, [in Proc. ACM SIGIR Conf. Res. Dev. Inform. Retrieval, 2009, pp. 628-629.
32. A. Hanjalic, BExtracting moods from pictures and sounds: Towards truly personalized TV, [IEEE Signal Process. Mag., vol. 23, no. 2, pp. 90-100, Mar. 2006.
33. A. Hanjalic and L.-Q. Xu, BAffective video content representation and modeling, [IEEE Trans. Multimedia, vol. 7, no. 1, pp. 143-154, 2005.
34. A. G. Hauptmann, M. Christel, and R. Yan, BVideo retrieval based on semantic concepts, [Proc. IEEE, pp. 602-622, 2008.
35. A. G. Hauptmann, W. H. Lin, R. Yan, J. Yang, and M. Y. Chen, BExtreme video retrieval: Joint maximization of human and computer performance, [in Proc. ACM Int. Conf. Multimedia, Santa Barbara, 2006.
36. A. G. Hauptmann, R. Yan, W.-H. Lin, M. Christel, and H. Wactlar, BCan high-level concepts fill the semantic gap in video retrieval? A case study with broadcast news, [IEEE Trans. Multimedia, vol. 9, no. 5, pp. 958-966, 2007.
37. J. Hu, H.-J. Zeng, H. Li, C. Niu, and Z. Chen, BDemographic prediction based on user's browsing behavior, [in Proc. Int. WWW Conf., 2007.
38. X.-S. Hua, L. Lu, and H.-J. Zhang, BOptimization-based automated home video editing system, [IEEE Trans. Circuit Syst. for Video Technol., vol. 14, no. 5, pp. 572-583, 2004.
39. X.-S. Hua, L. Lu, and H.-J. Zhang, BRobust learning-based TV commercial detection, [in Proc. ICME, Jul. 2005.
40. X.-S. Hua, T. Mei, and S. Li, BWhen multimedia advertising meets the new internet era, [in Proc. IEEE Int. Workshop Multimedia Signal Process., 2008, pp. 1-5.
41. X.-S. Hua, P. Yin, and H.-J. Zhang, BEfficient video text recognition using multiple frame integration, [in Proc. IEEE Int. Conf. Image Process., 2002, pp. 397-400.
42. T. S. Huang, C. K. Dagli, S. Rajaram, E. Y. Chang, M. I. Mandel, G. E. Poliner, and D. P. W. Ellis, BActive learning for interactive multimedia retrieval, [Proc. IEEE, vol. 96, no. 4, pp. 648-667, Apr. 2008.
43. Hulu. [Online]. Available: http://www.hulu.com/
44. IT Facts. [Online]. Available: http://www.itfacts.biz/50-bln-digital- photos-taken-in-2007-60-bln-by-2011/8985
45. iTVx. [Online]. Available: http://www.itvx.com/
46. R. J. K. Jacob and K. S. Karn, BEye tracking in human-computer interaction and usability research: Ready to deliver the promises, [in The Mind's Eye: Cognitive and Applied Aspects of Eye Movement Research, R. Radach, J. Hyona, and H. Deubel, Eds. Boston: North-Holland/Elsevier, 2003.
47. K. Jarvelin and J. Kekalainen, BCumulated gain-based evaluation of IR techniques, [ACM Trans. Inform. Syst., vol. 20, no. 4, pp. 442-446, 2002.
48. W. Jiang, D. Liu, X. Xie, M. R. Scott, J. Tien, and D. Xiang, BAn online advertisement platform based on image content bidding, [in IEEE Int. Conf. Multimedia & Expo, 2009.
49. A. Joshi and R. Motwani, BKeyword generation for search engine advertising, [in Proc. Workshops IEEE Int. Conf. Data Mining, 2006.
50. Jupiter Research. [Online]. Available: http://www.jupiterresearch.com/
51. G. Kastidou and R. Cohen, BAn approach for delivering personalized ads in interactive TV customized to both users and advertisers, [in Proc. Eur. Conf. Interactive Television, 2006.
52. L. Kennedy, S.-F. Chang, and A. Natsev, BQuery-adaptive fusion for multimodal search, [Proc. IEEE, vol. 96, no. 4, pp. 567-588, 2008.
53. L. Kennedy, M. Naaman, S. Ahern, R. Nair, and T. Rattenbury, BHow Flickr helps us make sense of the world: Context and content in community-contributed media collections, [in Proc. ACM Multimedia, Augsburg, Germany, 2007.
54. A. Lacerda, M. Cristo, M. A. Goncalves et al., BLearning to advertise, [in Proc. ACM SIGIR Conf. Res. Dev. Inform. Retrieval, 2006.
55. G. Lekakos, D. Papakiriakopoulos, and K. Chorianopoulos, BAn integrated approach to interactive and personalized TV advertising, [in Proc. Workshop on Personalization in Future TV, 2001.
56. D. Li, B. Wang, Z. Li, N. Yu, and M. Li, BOn detection of advertising images, [in IEEE Int. Conf. Multimedia & Expo, 2007.
57. H. Li, S. M. Edwards, and J.-H. Lee, BMeasuring the intrusiveness of advertisements: Scale development and validation, [J. Advertising, vol. 31, no. 2, pp. 37-47, 2002.
58. H. Li, D. Zhang, J. Hu, H.-J. Zeng, and Z. Chen, BFinding keyword from online broadcasting content for targeted advertising, [in Int. Workshop on Data Mining and Audience Intelligence for Advertising, 2007.
59. L. Li, T. Mei, and X.-S. Hua, BGameSense: Game-like in-image advertising, [Multimedia Tools and Applications, 2009.
60. L. Li, T. Mei, C. Liu, and X.-S. Hua, BGameSense, [in Proc. Int. WWW Conf., Madrid, Spain, Apr. 2009, pp. 1097-1098.
61. S. Z. Li, L. Zhu, Z. Zhang, A. Blake, H.-J. Zhang, and H. Shum, BStatistical learning of multi-view face detection, [in Proc. Eur. Conf. Computer Vision, Copenhagen, Denmark, May 2002, pp. 67-81.
62. M: Multi-video synopsis, [in 1st Int. Workshop on Video Mining, in Conjunction With the IEEE Int. Conf. Data Mining, 2008, pp. 854-861.
63. X. Li, C. G. M. Snoek, and M. Worring, BLearning tag relevance by neighbor voting for social image retrieval, [in Proc. ACM Multimedia Inform. Retrieval, 2008.
64. Y. Li, K. Wan, X. Yan, and C. Xu, BAdvertisement insertion in baseball video based on advertisement effect, [in Proc. ACM Multimedia, 2005, pp. 343-346.
65. Z. Li, L. Zhang, and W.-Y. Ma, BDelivering online advertisements inside images, [in Proc. ACM Multimedia, 2008, pp. 1051-1060.
66. W.-S. Liao, K.-T. Chen, and W. H. Hsu, BAdimage: Video advertising by image matching and ad scheduling optimization, [in Proc. ACM SIGIR Conf. Res. Dev. Inform. Retrieval, 2008, pp. 767-768.
67. R. Lienhart, C. Kuhmunch, and W. Effelsberg, BOn the detection and recognition of television commercials, [in Proc. Int. Conf. Multimedia Comput. Syst., Ottawa, Canada, 1997, pp. 509-516.
68. D. Liu, X.-S. Hua, L. Yang, M. Wang, and H.-J. Zhang, BTag ranking, [in Proc. Int. WWW Conf., 2009.
69. H. Liu, S. Jiang, Q. Huang, and C. Xu, BA generic virtual content insertion system based on visual attention analysis, [in Proc. ACM Int. Conf. Multimedia, 2008, pp. 379-388.
70. T. Liu, J. Sun, N.-N. Zheng, X. Tang, and H.-Y. Shum, BLearning to detect a salient object, [in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2007, pp. 1-8.
71. D. G. Lowe, BDistinctive image features from scale-invariant keypoints, [Int. J. Comput. Vis., vol. 60, no. 2, pp. 91-110, 2004.
72. Y.-F. Ma, L. Lu, H.-J. Zhang, and M. Li, BA user attention model for video summarization, [in Proc. ACM Multimedia, 2002, pp. 533-542.
73. Y.-F. Ma and H.-J. Zhang, BContrast-based image attention analysis by using fuzzy growing, [in Proc. ACM Multimedia, Nov. 2003, pp. 374-381.
74. S. Mccoy, A. Everard, P. Polak, and D. F. Galletta, BThe effects of online advertising, [Commun. ACM, vol. 50, no. 3, pp. 84-88, 2007.
75. A. Mehta, A. Saberi, U. Vazirani, and V. Vazirani, BAdwords and generalized on-line matching, [J. ACM, vol. 54, no. 5, Oct. 2007.
76. T. Mei, J. Guo, X.-S. Hua, and F. Liu, BAdOn: Toward contextual overlay in-video advertising, [Multimedia Syst., 2010.
77. T. Mei, X.-S. Hua, W. Lai, L. Yang et al., BMSRA-USTC-SJTU at TRECVID 2007: High-level feature extraction and search, [in TREC Video Retrieval Evaluation Online Proc., 2007.
78. T. Mei, X.-S. Hua, and S. Li, BContextual in-image advertising, [in Proc. ACM Multimedia, Vancouver, Canada, 2008, pp. 439-448.
79. T. Mei, X.-S. Hua, and S. Li, BVideoSense: A contextual in-video advertising system, [IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 12, pp. 1866-1879, Dec. 2009.
80. T. Mei, X.-S. Hua, L. Yang, and S. Li, BVideoSense: Towards effective online video advertising, [in Proc. ACM Multimedia, Augsburg, Germany, 2007, pp. 1075-1084.
81. T. Mei, X.-S. Hua, C.-Z. Zhu, H.-Q. Zhou, and S. Li, BHome video visual quality assessment with spatiotemporal factors, [IEEE Trans. Circuits Syst. Video Technol., vol. 17, no. 6, pp. 699-706, Jun. 2007.
82. MSN Video. [Online]. Available: http://video.msn.com/
83. V. Murdock, M. Ciaramita, and V. Plachouras, BA noisy-channel approach to contextual advertising, [in 1st Int. Workshop on Data Mining and Audience Intelligence for Advertising, 2007, pp. 96-99.
84. M. Naphade, J. R. Smith, J. Tesic, S.-F. Chang, W. Hsu, L. Kennedy, A. Hauptmann, and J. Curtis, BLarge-scale concept ontology for multimedia, [IEEE MultiMedia, vol. 13, no. 3, pp. 86-91, Jul.-Sep. 2006.
85. Online Publishers. [Online]. Available: http://www.online-publishers.org/
86. A. Poole and L. J. Ball, BEye tracking in human-computer interaction and usability research: Current status and future prospects, [in Encyclopedia of Human Computer Interaction, Idea Group, 2004.
87. G.-J. Qi, X.-S. Hua, Y. Rui, J. Tang, T. Mei, and H.-J. Zhang, BCorrelative multi-label video annotation, [in ACM Multimedia, Augsburg, Germany, Sep. 2007, pp. 17-26.
88. Revver. [Online]. Available: http://one.revver.com/revver
89. B. Ribeiro-Neto, M. Cristo, P. B. Golgher, and E. S. Moura, BImpedance coupling in content-targeted advertising, [in Proc. ACM SIGIR Conf. Res. Devel. Inform. Retrieval, 2005.
90. M. Richardson, E. Dominowska, and R. Ragno, BPredicting clicks: Estimating click-through rate for new ads, [in Proc. Int. WWW Conf., 2007.
91. C. Rohrer and J. Boyd, BThe rise of intrusive online advertising and the response of user experience research at Yahoo![in Proc. SIGCHI Conf. Human Factors Comput. Syst., 2004.
92. Y. Rui, T. S. Huang, M. Ortega, and S. Mehrotra, BRelevance feedback: A power tool for interactive content-based image retrieval, [IEEE Trans. Circuits Video Technol., vol. 8, no. 5, pp. 644-655, Sep. 1998.
93. M. R. Scott, W. Jiang, X. Xie, J. Tien, G. Chen, and D. Xiang, BVisiAds: A vision-based advertising platform for camera phones, [in IEEE Int. Conf. Multimedia & Expo, 2009.
94. D. Shen, J.-T. Sun, Q. Yang, and Z. Chen, BBuilding bridges for web query classification, [in Proc. ACM SIGIR Conf. Res. Devel. Inform. Retrieval, 2006.
95. C. G. M. Snoek, M. Worring, J. C. van Gemert, J. M. Geusebroek, and A. W. M. Smeulders, BThe challenge problem for automated detection of 101 semantic concepts in multimedia, [in Proc. ACM Int. Conf. Multimedia, Santa Barbara, 2006.
96. S. H. Srinivasan, N. Sawant, and S. Wadhwa, BvADeo: Video advertising system, [in Proc. ACM Multimedia, 2007, pp. 455-456.
97. A. Thawani, S. Gopalan, and V. Sridhar, BContext aware personalized ad insertion in an interactive TV environment, [in Proc. Workshop on Personalization in Future TV, 2004.
98. TRECVID. [Online]. Available: http://www-nlpir.nist.gov/projects/trecvid/
99. S. Velusamy, L. Gopal, S. Bhatnagar, and S. Varadarajan, BAn efficient ad recommendation system for TV programs, [Multimedia Syst., vol. 14, pp. 73-87, Jul. 2008.
100. Vibrant Media. [Online]. Available: http://www.vibrantmedia.com/
101. Videoegg. [Online]. Available: http://www.videoegg.com/
102. E. M. Voorhees and D. K. Harman, TREC: Experiment and Evaluation in Information Retrieval. Cambridge, MA: MIT Press, 2005.
103. K. Wan, X. Yan, X. Yu, and C. Xu, BRobust goal-mouth detection for virtual content insertion, [in Proc. ACM Multimedia, Nov. 2003, pp. 468-469.
104. G. Wang and D. Forsyth, BObject image retrieval by exploiting online knowledge resources, [in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2008.
105. J. Wang and L.-Y. Duan, BLinking video ads with product or service information by web search, [in IEEE Int. Conf. Multimedia & Expo, 2009.
106. M. Weideman and T. Haig-Smith, BAn investigation into search engines as a form of targeted advert delivery, [in South African Institute of Computer Scientists and Information Technologies on Enablement Through Technology, 2002, pp. 258-258
107. D. Whitley, BA genetic algorithm tutorial, [Stat. Comput., vol. 4, pp. 65-85, 1994.
108. Wikipedia. [Online]. Available: http://en.wikipedia.org/wiki/click- through-rate
109. L. Wu, X.-S. Hua, N. Yu, W.-Y. Ma, and S. Li, BFlickr distance, [in Proc. ACM Multimedia, Vancouver, Canada, 2008, pp. 31-40.
110. X. Xie, L. Lu, M. Jia, H. Li, S. Frank, and W.-Y. Ma, BMobile search with multimodal queries, [Proc. IEEE, vol. 96, no. 4, pp. 589-601, Apr. 2008.
111. C. Xu, K. W. Wan, S. H. Bui, and Q. Tian, BImplanting virtual advertisement into broadcast soccer video, [in Proc. IEEE Pacific Rim Conf. Multimedia, 2004, pp. 264-271.
112. Yahoo!. [Online]. Available: http://www.yahoo.com/
113. J. Yan, N. Liu, G. Wang, W. Zhang, Y. Jiang, and Z. Chen, BHow much can behavioral targeting help online advertising?" in Proc. WWW, 2009, pp. 261-270.
114. B. Yang, T. Mei, X.-S. Hua, L. Yang, S.-Q. Yang, and M. Li, BOnline video recommendation based on multimodal fusion and relevance feedback, [in Proc. ACM Int. Conf. Image Video Retrieval, 2007.
115. K. Yang, M. Wang, and H.-J. Zhang, BActive tagging for image indexing, [in Proc. Int. Workshop Internet Multimedia Search Mining, in Conjunction With ICME, 2009.
116. Y. Yang and X. Liu, BA re-examination of text categorization methods, [in Proc. ACM SIGIR Conf. Res. Devel. Inform. Retrieval, 1999.
117. W.-T. Yih, J. Goodman, and V. R. Carvalho, BFinding advertising keywords on web pages, [in Proc. Int. WWW Conf., 2006.
118. YouTube. [Online]. Available: http://www.youtube.com/
119. Z.-J. Zha, T. Mei, Z. Wang, and X.-S. Hua, BBuilding a comprehensive ontology to refine video concept detection, [in Proc. ACM SIGMM Int. Conf. Workshop Multimedia Inform. Retrieval, Augsburg, Germany, Sep. 2007, pp. 227-236.
120. H.-J. Zhang, A. Kankanhalli, and S. W. Smoliar, BAutomatic partitioning of full-motion video, [Multimedia Syst., vol. 1, no. 1, pp. 10-28, Jun. 1993.
121. S. Zhang, Q. Tian, S. Jiang, Q. Huang, and W. Gao, BAffective mtv analysis based on arousal and valence features, [in Proc. ICME, 2008, pp. 1369-1372.
122. L. Zhao, W. Qi, Y.-J. Wang, S.-Q. Yang, and H.-J. Zhang, BVideo shot grouping using best first model merging, [in Proc. Storage and Retrieval for Media Database, 2001, pp. 262-269.
123. Y. Zheng, Q. Li, Y. Chen, and X. Xie, BUnderstanding mobility based on GPS data, [in Proc. ACM Conf. Ubiquitous Comput., Seoul, Korea, 2008, pp. 312-321.
124. X. S. Zhou and T. S. Huang, BRelevance feedback for image retrieval: A comprehensive review, [Multimedia Syst., vol. 8, no. 6, pp. 536-544, Apr. 2003.