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Multimodal Analysis of User-Generated Multimedia Content pp 235–260Cite as

Conclusion and Future Work

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Part of the book series: Socio-Affective Computing ((SAC,volume 6))

Abstract

This book studied several significant multimedia analytics problems and presented their solutions leveraging multimodal information. The multimodal information of user-generated multimedia content (UGC) is very useful in an effective search, retrieval, and recommendation services on social media. Specifically, we determine semantics and sentics information from UGC, and leverage them in building improved systems for several significant multimedia analytics problems. We collected and created the significant amount of user-generated multimedia content in our study. To benefit from the multimodal information, we extract knowledge structures from different modalities and exploit them in our solutions for several significant multimedia-based applications. We presented our solution on event understanding from UGIs, tag ranking and recommendation for UGIs, soundtrack recommendation for UGVs, lecture videos segmentation , and news videos uploading in the area with weak network infrastructures leveraging multimodal information. Here we summarize our contributions and future work for several significant multimedia analytics problems.

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References

  1. Apple Denies Steve Jobs Heart Attack Report: “It Is Not True”. http://www.businessinsider.com/2008/10/apple-s-steve-jobs-rushed-to-er-after-heart-attack-says-cnn-citizen-journalist/. October 2008. Online: Last Accessed Sept 2015.

  2. SVMhmm: Sequence Tagging with Structural Support Vector Machines. https://www.cs.cornell.edu/people/tj/svm light/svm hmm.html. August 2008. Online: Last Accessed May 2016.

  3. NPTEL. 2009, December. http://www.nptel.ac.in. Online; Accessed Apr 2015.

  4. iReport at 5: Nearly 900,000 contributors worldwide. http://www.niemanlab.org/2011/08/ireport-at-5-nearly-900000-contributors-worldwide/. August 2011. Online: Last Accessed Sept 2015.

  5. Meet the million: 999,999 iReporters + you! http://www.ireport.cnn.com/blogs/ireport-blog/2012/01/23/meet-the-million-999999-ireporters-you. January 2012. Online: Last Accessed Sept 2015.

  6. 5 Surprising Stats about User-generated Content. 2014, April. http://www.smartblogs.com/social-media/2014/04/11/6.-surprising-stats-about-user-generated-content/. Online: Last Accessed Sept 2015.

  7. The Citizen Journalist: How Ordinary People are Taking Control of the News. 2015, June. http://www.digitaltrends.com/features/the-citizen-journalist-how-ordinary-people-are-taking-control-of-the-news/. Online: Last Accessed Sept 2015.

  8. Wikipedia API. 2015, April. http://tinyurl.com/WikiAPI-AI. API: Last Accessed Apr 2015.

  9. Apache Lucene. 2016, June. https://lucene.apache.org/core/. Java API: Last Accessed June 2016.

  10. By the Numbers: 14 Interesting Flickr Stats. 2016, May. http://www.expandedramblings.com/index.php/flickr-stats/. Online: Last Accessed May 2016.

  11. By the Numbers: 180+ Interesting Instagram Statistics (June 2016). 2016, June. http://www.expandedramblings.com/index.php/important-instagram-stats/. Online: Last Accessed July 2016.

  12. Coursera. 2016, May. https://www.coursera.org/. Online: Last Accessed May 2016.

  13. FourSquare API. 2016, June. https://developer.foursquare.com/. Last Accessed June 2016.

  14. Google Cloud Vision API. 2016, December. https://cloud.google.com/vision/. Online: Last Accessed Dec 2016.

  15. Google Forms. 2016, May. https://docs.google.com/forms/. Online: Last Accessed May 2016.

  16. MIT Open Course Ware. 2016, May. http://www.ocw.mit.edu/. Online: Last Accessed May 2016.

  17. Porter Stemmer. 2016, May. https://tartarus.org/martin/PorterStemmer/. Online: Last Accessed May 2016.

  18. SenticNet. 2016, May. http://www.sentic.net/computing/. Online: Last Accessed May 2016.

  19. Sentics. 2016, May. https://en.wiktionary.org/wiki/sentics. Online: Last Accessed May 2016.

  20. VideoLectures.Net. 2016, May. http://www.videolectures.net/. Online: Last Accessed May, 2016.

  21. YouTube Statistics. 2016, July. http://www.youtube.com/yt/press/statistics.html. Online: Last Accessed July, 2016.

  22. Abba, H.A., S.N.M. Shah, N.B. Zakaria, and A.J. Pal. 2012. Deadline based performance evaluation of job scheduling algorithms. In Proceedings of the IEEE International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, 106–110.

    Google Scholar 

  23. Achanta, R.S., W.-Q. Yan, and M.S. Kankanhalli. 2006. Modeling Intent for Home Video Repurposing. Proceedings of the IEEE MultiMedia 45(1): 46–55.

    Google Scholar 

  24. Adcock, J., M. Cooper, A. Girgensohn, and L. Wilcox. 2005. Interactive Video Search Using Multilevel Indexing. In Proceedings of the Springer Image and Video Retrieval, 205–214.

    Google Scholar 

  25. Agarwal, B., S. Poria, N. Mittal, A. Gelbukh, and A. Hussain. 2015. Concept-level Sentiment Analysis with Dependency-based Semantic Parsing: A Novel Approach. In Proceedings of the Springer Cognitive Computation, 1–13.

    Google Scholar 

  26. Aizawa, K., D. Tancharoen, S. Kawasaki, and T. Yamasaki. 2004. Efficient Retrieval of Life Log based on Context and Content. In Proceedings of the ACM Workshop on Continuous Archival and Retrieval of Personal Experiences, 22–31.

    Google Scholar 

  27. Altun, Y., I. Tsochantaridis, and T. Hofmann. 2003. Hidden Markov Support Vector Machines. In Proceedings of the International Conference on Machine Learning, 3–10.

    Google Scholar 

  28. Anderson, A., K. Ranghunathan, and A. Vogel. 2008. Tagez: Flickr Tag Recommendation. In Proceedings of the Association for the Advancement of Artificial Intelligence.

    Google Scholar 

  29. Atrey, P.K., A. El Saddik, and M.S. Kankanhalli. 2011. Effective Multimedia Surveillance using a Human-centric Approach. Proceedings of the Springer Multimedia Tools and Applications 51(2): 697–721.

    Article  Google Scholar 

  30. Barnard, K., P. Duygulu, D. Forsyth, N. De Freitas, D.M. Blei, and M.I. Jordan. 2003. Matching Words and Pictures. Proceedings of the Journal of Machine Learning Research 3: 1107–1135.

    Google Scholar 

  31. Basu, S., Y. Yu, V.K. Singh, and R. Zimmermann. 2016. Videopedia: Lecture Video Recommendation for Educational Blogs Using Topic Modeling. In Proceedings of the Springer International Conference on Multimedia Modeling, 238–250.

    Google Scholar 

  32. Basu, S., Y. Yu, and R. Zimmermann. 2016. Fuzzy Clustering of Lecture Videos Based on Topic Modeling. In Proceedings of the IEEE International Workshop on Content-Based Multimedia Indexing, 1–6.

    Google Scholar 

  33. Basu, S., R. Zimmermann, K.L. OHalloran, S. Tan, and K. Marissa. 2015. Performance Evaluation of Students Using Multimodal Learning Systems. In Proceedings of the Springer International Conference on Multimedia Modeling, 135–147.

    Google Scholar 

  34. Beeferman, D., A. Berger, and J. Lafferty. 1999. Statistical Models for Text Segmentation. Proceedings of the Springer Machine Learning 34(1–3): 177–210.

    Article  Google Scholar 

  35. Bernd, J., D. Borth, C. Carrano, J. Choi, B. Elizalde, G. Friedland, L. Gottlieb, K. Ni, R. Pearce, D. Poland, et al. 2015. Kickstarting the Commons: The YFCC100M and the YLI Corpora. In Proceedings of the ACM Workshop on Community-Organized Multimodal Mining: Opportunities for Novel Solutions, 1–6.

    Google Scholar 

  36. Bhatt, C.A., and M.S. Kankanhalli. 2011. Multimedia Data Mining: State of the Art and Challenges. Proceedings of the Multimedia Tools and Applications 51(1): 35–76.

    Article  Google Scholar 

  37. Bhatt, C.A., A. Popescu-Belis, M. Habibi, S. Ingram, S. Masneri, F. McInnes, N. Pappas, and O. Schreer. 2013. Multi-factor Segmentation for Topic Visualization and Recommendation: the MUST-VIS System. In Proceedings of the ACM International Conference on Multimedia, 365–368.

    Google Scholar 

  38. Bhattacharjee, S., W.C. Cheng, C.-F. Chou, L. Golubchik, and S. Khuller. 2000. BISTRO: A Framework for Building Scalable Wide-Area Upload Applications. Proceedings of the ACM SIGMETRICS Performance Evaluation Review 28(2): 29–35.

    Article  Google Scholar 

  39. Cambria, E., J. Fu, F. Bisio, and S. Poria. 2015. AffectiveSpace 2: Enabling Affective Intuition for Concept-level Sentiment Analysis. In Proceedings of the AAAI Conference on Artificial Intelligence, 508–514.

    Google Scholar 

  40. Cambria, E., A. Livingstone, and A. Hussain. 2012. The Hourglass of Emotions. In Proceedings of the Springer Cognitive Behavioural Systems, 144–157.

    Google Scholar 

  41. Cambria, E., D. Olsher, and D. Rajagopal. 2014. SenticNet 3: A Common and Common-sense Knowledge Base for Cognition-driven Sentiment Analysis. In Proceedings of the AAAI Conference on Artificial Intelligence, 1515–1521.

    Google Scholar 

  42. Cambria, E., S. Poria, R. Bajpai, and B. Schuller. 2016. SenticNet 4: A Semantic Resource for Sentiment Analysis based on Conceptual Primitives. In Proceedings of the International Conference on Computational Linguistics (COLING), 2666–2677.

    Google Scholar 

  43. Cambria, E., S. Poria, F. Bisio, R. Bajpai, and I. Chaturvedi. 2015. The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis. In Proceedings of the Springer Computational Linguistics and Intelligent Text Processing, 3–22.

    Google Scholar 

  44. Cambria, E., S. Poria, A. Gelbukh, and K. Kwok. 2014. Sentic API: A Common-sense based API for Concept-level Sentiment Analysis. CEUR Workshop Proceedings 144: 19–24.

    Google Scholar 

  45. Cao, J., Z. Huang, and Y. Yang. 2015. Spatial-aware Multimodal Location Estimation for Social Images. In Proceedings of the ACM Conference on Multimedia Conference, 119–128.

    Google Scholar 

  46. Chakraborty, I., H. Cheng, and O. Javed. 2014. Entity Centric Feature Pooling for Complex Event Detection. In Proceedings of the Workshop on HuEvent at the ACM International Conference on Multimedia, 1–5.

    Google Scholar 

  47. Che, X., H. Yang, and C. Meinel. 2013. Lecture Video Segmentation by Automatically Analyzing the Synchronized Slides. In Proceedings of the ACM International Conference on Multimedia, 345–348.

    Google Scholar 

  48. Chen, B., J. Wang, Q. Huang, and T. Mei. 2012. Personalized Video Recommendation through Tripartite Graph Propagation. In Proceedings of the ACM International Conference on Multimedia, 1133–1136.

    Google Scholar 

  49. Chen, S., L. Tong, and T. He. 2011. Optimal Deadline Scheduling with Commitment. In Proceedings of the IEEE Annual Allerton Conference on Communication, Control, and Computing, 111–118.

    Google Scholar 

  50. Chen, W.-B., C. Zhang, and S. Gao. 2012. Segmentation Tree based Multiple Object Image Retrieval. In Proceedings of the IEEE International Symposium on Multimedia, 214–221.

    Google Scholar 

  51. Chen, Y., and W.J. Heng. 2003. Automatic Synchronization of Speech Transcript and Slides in Presentation. Proceedings of the IEEE International Symposium on Circuits and Systems 2: 568–571.

    Google Scholar 

  52. Cohen, J. 1960. A Coefficient of Agreement for Nominal Scales. Proceedings of the Durham Educational and Psychological Measurement 20(1): 37–46.

    Article  Google Scholar 

  53. Cristani, M., A. Pesarin, C. Drioli, V. Murino, A. Rodà,M. Grapulin, and N. Sebe. 2010. Toward an Automatically Generated Soundtrack from Low-level Cross-modal Correlations for Automotive Scenarios. In Proceedings of the ACM International Conference on Multimedia, 551–560.

    Google Scholar 

  54. Dang-Nguyen, D.-T., L. Piras, G. Giacinto, G. Boato, and F.G. De Natale. 2015. A Hybrid Approach for Retrieving Diverse Social Images of Landmarks. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME), 1–6.

    Google Scholar 

  55. Fabro, M. Del, A. Sobe, and L. Böszörmenyi. 2012. Summarization of Real-life Events Based on Community-contributed Content. In Proceedings of the International Conferences on Advances in Multimedia, 119–126.

    Google Scholar 

  56. Du, L., W.L. Buntine, and M. Johnson. 2013. Topic Segmentation with a Structured Topic Model. In Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 190–200.

    Google Scholar 

  57. Fan, Q., K. Barnard, A. Amir, A. Efrat, and M. Lin. 2006. Matching Slides to Presentation Videos using SIFT and Scene Background Matching. In Proceedings of the ACM International Conference on Multimedia, 239–248.

    Google Scholar 

  58. Filatova, E. and V. Hatzivassiloglou. 2004. Event-Based Extractive Summarization. In Proceedings of the ACL Workshop on Summarization, 104–111.

    Google Scholar 

  59. Firan, C.S., M. Georgescu, W. Nejdl, and R. Paiu. 2010. Bringing Order to Your Photos: Event-driven Classification of Flickr Images Based on Social Knowledge. In Proceedings of the ACM International Conference on Information and Knowledge Management, 189–198.

    Google Scholar 

  60. Gao, S., C. Zhang, and W.-B. Chen. 2012. An Improvement of Color Image Segmentation through Projective Clustering. In Proceedings of the IEEE International Conference on Information Reuse and Integration, 152–158.

    Google Scholar 

  61. Garg, N. and I. Weber. 2008. Personalized, Interactive Tag Recommendation for Flickr. In Proceedings of the ACM Conference on Recommender Systems, 67–74.

    Google Scholar 

  62. Ghias, A., J. Logan, D. Chamberlin, and B.C. Smith. 1995. Query by Humming: Musical Information Retrieval in an Audio Database. In Proceedings of the ACM International Conference on Multimedia, 231–236.

    Google Scholar 

  63. Golder, S.A., and B.A. Huberman. 2006. Usage Patterns of Collaborative Tagging Systems. Proceedings of the Journal of Information Science 32(2): 198–208.

    Article  Google Scholar 

  64. Gozali, J.P., M.-Y. Kan, and H. Sundaram. 2012. Hidden Markov Model for Event Photo Stream Segmentation. In Proceedings of the IEEE International Conference on Multimedia and Expo Workshops, 25–30.

    Google Scholar 

  65. Guo, Y., L. Zhang, Y. Hu, X. He, and J. Gao. 2016. Ms-celeb-1m: Challenge of recognizing one million celebrities in the real world. Proceedings of the Society for Imaging Science and Technology Electronic Imaging 2016(11): 1–6.

    CAS  Google Scholar 

  66. Hanjalic, A., and L.-Q. Xu. 2005. Affective Video Content Representation and Modeling. Proceedings of the IEEE Transactions on Multimedia 7(1): 143–154.

    Article  Google Scholar 

  67. Haubold, A. and J.R. Kender. 2005. Augmented Segmentation and Visualization for Presentation Videos. In Proceedings of the ACM International Conference on Multimedia, 51–60.

    Google Scholar 

  68. Healey, J.A., and R.W. Picard. 2005. Detecting Stress during Real-world Driving Tasks using Physiological Sensors. Proceedings of the IEEE Transactions on Intelligent Transportation Systems 6(2): 156–166.

    Article  Google Scholar 

  69. Hefeeda, M., and C.-H. Hsu. 2010. On Burst Transmission Scheduling in Mobile TV Broadcast Networks. Proceedings of the IEEE/ACM Transactions on Networking 18(2): 610–623.

    Article  Google Scholar 

  70. Hevner, K. 1936. Experimental Studies of the Elements of Expression in Music. Proceedings of the American Journal of Psychology 48: 246–268.

    Article  Google Scholar 

  71. Hochbaum, D.S.. 1996. Approximating Covering and Packing Problems: Set Cover, Vertex Cover, Independent Set, and related Problems. In Proceedings of the PWS Approximation algorithms for NP-hard problems, 94–143.

    Google Scholar 

  72. Hong, R., J. Tang, H.-K. Tan, S. Yan, C. Ngo, and T.-S. Chua. 2009. Event Driven Summarization for Web Videos. In Proceedings of the ACM SIGMM Workshop on Social Media, 43–48.

    Google Scholar 

  73. P. ITU-T Recommendation. 1999. Subjective Video Quality Assessment Methods for Multimedia Applications.

    Google Scholar 

  74. Jiang, L., A.G. Hauptmann, and G. Xiang. 2012. Leveraging High-level and Low-level Features for Multimedia Event Detection. In Proceedings of the ACM International Conference on Multimedia, 449–458.

    Google Scholar 

  75. Joachims, T., T. Finley, and C.-N. Yu. 2009. Cutting-plane Training of Structural SVMs. Proceedings of the Machine Learning Journal 77(1): 27–59.

    Article  Google Scholar 

  76. Johnson, J., L. Ballan, and L. Fei-Fei. 2015. Love Thy Neighbors: Image Annotation by Exploiting Image Metadata. In Proceedings of the IEEE International Conference on Computer Vision, 4624–4632.

    Google Scholar 

  77. Johnson, J., A. Karpathy, and L. Fei-Fei. 2015. Densecap: Fully Convolutional Localization Networks for Dense Captioning. In Proceedings of the arXiv preprint arXiv:1511.07571.

    Google Scholar 

  78. Jokhio, F., A. Ashraf, S. Lafond, I. Porres, and J. Lilius. 2013. Prediction-Based dynamic resource allocation for video transcoding in cloud computing. In Proceedings of the IEEE International Conference on Parallel, Distributed and Network-Based Processing, 254–261.

    Google Scholar 

  79. Kaminskas, M., I. Fernández-Tobías, F. Ricci, and I. Cantador. 2014. Knowledge-Based Identification of Music Suited for Places of Interest. Proceedings of the Springer Information Technology & Tourism 14(1): 73–95.

    Article  Google Scholar 

  80. Kaminskas, M. and F. Ricci. 2011. Location-adapted Music Recommendation using Tags. In Proceedings of the Springer User Modeling, Adaption and Personalization, 183–194.

    Google Scholar 

  81. Kan, M.-Y.. 2001. Combining Visual Layout and Lexical Cohesion Features for Text Segmentation. In Proceedings of the Citeseer.

    Google Scholar 

  82. Kan, M.-Y. 2003. Automatic Text Summarization as Applied to Information Retrieval. PhD thesis, Columbia University.

    Google Scholar 

  83. Kan, M.-Y., J.L. Klavans, and K.R. McKeown.1998. Linear Segmentation and Segment Significance. In Proceedings of the arXiv preprint cs/9809020.

    Google Scholar 

  84. Kan, M.-Y., K.R. McKeown, and J.L. Klavans. 2001. Applying Natural Language Generation to Indicative Summarization. Proceedings of the ACL European Workshop on Natural Language Generation 8: 1–9.

    CAS  Google Scholar 

  85. Kang, H.B.. 2003. Affective Content Detection using HMMs. In Proceedings of the ACM International Conference on Multimedia, 259–262.

    Google Scholar 

  86. Kang, Y.-L., J.-H. Lim, M.S. Kankanhalli, C.-S. Xu, and Q. Tian. 2004. Goal Detection in Soccer Video using Audio/Visual Keywords. Proceedings of the IEEE International Conference on Image Processing 3: 1629–1632.

    Google Scholar 

  87. Kang, Y.-L., J.-H. Lim, Q. Tian, and M.S. Kankanhalli. 2003. Soccer Video Event Detection with Visual Keywords. Proceedings of the Joint Conference of International Conference on Information, Communications and Signal Processing, and Pacific Rim Conference on Multimedia 3: 1796–1800.

    Google Scholar 

  88. Kankanhalli, M.S., and T.-S. Chua. 2000. Video Modeling using Strata-Based Annotation. Proceedings of the IEEE MultiMedia 7(1): 68–74.

    Article  Google Scholar 

  89. Kennedy, L., M. Naaman, S. Ahern, R. Nair, and T. Rattenbury. 2007. How Flickr Helps us Make Sense of the World: Context and Content in Community-Contributed Media Collections. In Proceedings of the ACM International Conference on Multimedia, 631–640.

    Google Scholar 

  90. Kennedy, L.S., S.-F. Chang, and I.V. Kozintsev. 2006. To Search or to Label?: Predicting the Performance of Search-Based Automatic Image Classifiers. In Proceedings of the ACM International Workshop on Multimedia Information Retrieval, 249–258.

    Google Scholar 

  91. Kim, Y.E., E.M. Schmidt, R. Migneco, B.G. Morton, P. Richardson, J. Scott, J.A. Speck, and D. Turnbull. 2010. Music Emotion Recognition: A State of the Art Review. In Proceedings of the International Society for Music Information Retrieval, 255–266.

    Google Scholar 

  92. Klavans, J.L., K.R. McKeown, M.-Y. Kan, and S. Lee. 1998. Resources for Evaluation of Summarization Techniques. In Proceedings of the arXiv preprint cs/9810014.

    Google Scholar 

  93. Ko, Y.. 2012. A Study of Term Weighting Schemes using Class Information for Text Classification. In Proceedings of the ACM Special Interest Group on Information Retrieval, 1029–1030.

    Google Scholar 

  94. Kort, B., R. Reilly, and R.W. Picard. 2001. An Affective Model of Interplay between Emotions and Learning: Reengineering Educational Pedagogy-Building a Learning Companion. Proceedings of the IEEE International Conference on Advanced Learning Technologies 1: 43–47.

    Article  Google Scholar 

  95. Kucuktunc, O., U. Gudukbay, and O. Ulusoy. 2010. Fuzzy Color Histogram-Based Video Segmentation. Proceedings of the Computer Vision and Image Understanding 114(1): 125–134.

    Article  Google Scholar 

  96. Kuo, F.-F., M.-F. Chiang, M.-K. Shan, and S.-Y. Lee. 2005. Emotion-Based Music Recommendation by Association Discovery from Film Music. In Proceedings of the ACM International Conference on Multimedia, 507–510.

    Google Scholar 

  97. Lacy, S., T. Atwater, X. Qin, and A. Powers. 1988. Cost and Competition in the Adoption of Satellite News Gathering Technology. Proceedings of the Taylor & Francis Journal of Media Economics 1(1): 51–59.

    Article  Google Scholar 

  98. Lambert, P., W. De Neve, P. De Neve, I. Moerman, P. Demeester, and R. Van de Walle. 2006. Rate-distortion performance of H. 264/AVC compared to state-of-the-art video codecs. Proceedings of the IEEE Transactions on Circuits and Systems for Video Technology 16(1): 134–140.

    Article  Google Scholar 

  99. Laurier, C., M. Sordo, J. Serrà, and P. Herrera. 2009. Music Mood Representations from Social Tags. In Proceedings of the International Society for Music Information Retrieval, 381–386.

    Google Scholar 

  100. Li, C.T. and M.K. Shan. 2007. Emotion-Based Impressionism Slideshow with Automatic Music Accompaniment. In Proceedings of the ACM International Conference on Multimedia, 839–842.

    Google Scholar 

  101. Li, J., and J.Z. Wang. 2008. Real-Time Computerized Annotation of Pictures. Proceedings of the IEEE Transactions on Pattern Analysis and Machine Intelligence 30(6): 985–1002.

    Article  Google Scholar 

  102. Li, X., C.G. Snoek, and M. Worring. 2009. Learning Social Tag Relevance by Neighbor Voting. Proceedings of the IEEE Transactions on Multimedia 11(7): 1310–1322.

    Article  Google Scholar 

  103. Li, X., T. Uricchio, L. Ballan, M. Bertini, C.G. Snoek, and A.D. Bimbo. 2016. Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement, and Retrieval. Proceedings of the ACM Computing Surveys (CSUR) 49(1): 14.

    Google Scholar 

  104. Li, Z., Y. Huang, G. Liu, F. Wang, Z.-L. Zhang, and Y. Dai. 2012. Cloud Transcoder: Bridging the Format and Resolution Gap between Internet Videos and Mobile Devices. In Proceedings of the ACM International Workshop on Network and Operating System Support for Digital Audio and Video, 33–38.

    Google Scholar 

  105. Liang, C., Y. Guo, and Y. Liu. 2008. Is Random Scheduling Sufficient in P2P Video Streaming? In Proceedings of the IEEE International Conference on Distributed Computing Systems, 53–60. IEEE.

    Google Scholar 

  106. Lim, J.-H., Q. Tian, and P. Mulhem. 2003. Home Photo Content Modeling for Personalized Event-Based Retrieval. Proceedings of the IEEE MultiMedia 4: 28–37.

    Google Scholar 

  107. Lin, M., M. Chau, J. Cao, and J.F. Nunamaker Jr. 2005. Automated Video Segmentation for Lecture Videos: A Linguistics-Based Approach. Proceedings of the IGI Global International Journal of Technology and Human Interaction 1(2): 27–45.

    Article  Google Scholar 

  108. Liu, C.L., and J.W. Layland. 1973. Scheduling Algorithms for Multiprogramming in a Hard-real-time Environment. Proceedings of the ACM Journal of the ACM 20(1): 46–61.

    Google Scholar 

  109. Liu, D., X.-S. Hua, L. Yang, M. Wang, and H.-J. Zhang. 2009. Tag Ranking. In Proceedings of the ACM World Wide Web Conference, 351–360.

    Google Scholar 

  110. Liu, T., C. Rosenberg, and H.A. Rowley. 2007. Clustering Billions of Images with Large Scale Nearest Neighbor Search. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 28–28.

    Google Scholar 

  111. Liu, X. and B. Huet. 2013. Event Representation and Visualization from Social Media. In Proceedings of the Springer Pacific-Rim Conference on Multimedia, 740–749.

    Google Scholar 

  112. Liu, Y., D. Zhang, G. Lu, and W.-Y. Ma. 2007. A Survey of Content-Based Image Retrieval with High-level Semantics. Proceedings of the Elsevier Pattern Recognition 40(1): 262–282.

    Article  Google Scholar 

  113. Livingston, S., and D.A.V. Belle. 2005. The Effects of Satellite Technology on Newsgathering from Remote Locations. Proceedings of the Taylor & Francis Political Communication 22(1): 45–62.

    Article  Google Scholar 

  114. Long, R., H. Wang, Y. Chen, O. Jin, and Y. Yu. 2011. Towards Effective Event Detection, Tracking and Summarization on Microblog Data. In Proceedings of the Springer Web-Age Information Management, 652–663.

    Google Scholar 

  115. L. Lu, H. You, and H. Zhang. 2001. A New Approach to Query by Humming in Music Retrieval. In Proceedings of the IEEE International Conference on Multimedia and Expo, 22–25.

    Google Scholar 

  116. Lu, Y., H. To, A. Alfarrarjeh, S.H. Kim, Y. Yin, R. Zimmermann, and C. Shahabi. 2016. GeoUGV: User-generated Mobile Video Dataset with Fine Granularity Spatial Metadata. In Proceedings of the ACM International Conference on Multimedia Systems, 43.

    Google Scholar 

  117. Mao, J., W. Xu, Y. Yang, J. Wang, Z. Huang, and A. Yuille. 2014. Deep Captioning with Multimodal Recurrent Neural Networks (M-RNN). In Proceedings of the arXiv preprint arXiv:1412.6632.

    Google Scholar 

  118. Matusiak, K.K. 2006. Towards User-Centered Indexing in Digital Image Collections. Proceedings of the OCLC Systems & Services: International Digital Library Perspectives 22(4): 283–298.

    Article  Google Scholar 

  119. McDuff, D., R. El Kaliouby, E. Kodra, and R. Picard. 2013. Measuring Voter’s Candidate Preference Based on Affective Responses to Election Debates. In Proceedings of the IEEE Humaine Association Conference on Affective Computing and Intelligent Interaction, 369–374.

    Google Scholar 

  120. McKeown, K.R., J.L. Klavans, and M.-Y. Kan. Method and System for Topical Segmentation, Segment Significance and Segment Function, 29 2002. US Patent 6,473,730.

    Google Scholar 

  121. Mezaris, V., A. Scherp, R. Jain, M. Kankanhalli, H. Zhou, J. Zhang, L. Wang, and Z. Zhang. 2011. Modeling and Rrepresenting Events in Multimedia. In Proceedings of the ACM International Conference on Multimedia, 613–614.

    Google Scholar 

  122. Mezaris, V., A. Scherp, R. Jain, and M.S. Kankanhalli. 2014. Real-life Events in Multimedia: Detection, Representation, Retrieval, and Applications. Proceedings of the Springer Multimedia Tools and Applications 70(1): 1–6.

    Article  Google Scholar 

  123. Miller, G., and C. Fellbaum. 1998. Wordnet: An Electronic Lexical Database. Cambridge, MA: MIT Press.

    Google Scholar 

  124. Miller, G.A. 1995. WordNet: A Lexical Database for English. Proceedings of the Communications of the ACM 38(11): 39–41.

    Article  Google Scholar 

  125. Moxley, E., J. Kleban, J. Xu, and B. Manjunath. 2009. Not All Tags are Created Equal: Learning Flickr Tag Semantics for Global Annotation. In Proceedings of the IEEE International Conference on Multimedia and Expo, 1452–1455.

    Google Scholar 

  126. Mulhem, P., M.S. Kankanhalli, J. Yi, and H. Hassan. 2003. Pivot Vector Space Approach for Audio-Video Mixing. Proceedings of the IEEE MultiMedia 2: 28–40.

    Article  Google Scholar 

  127. Naaman, M. 2012. Social Multimedia: Highlighting Opportunities for Search and Mining of Multimedia Data in Social Media Applications. Proceedings of the Springer Multimedia Tools and Applications 56(1): 9–34.

    Article  Google Scholar 

  128. Natarajan, P., P.K. Atrey, and M. Kankanhalli. 2015. Multi-Camera Coordination and Control in Surveillance Systems: A Survey. Proceedings of the ACM Transactions on Multimedia Computing, Communications, and Applications 11(4): 57.

    Google Scholar 

  129. Nayak, M.G. 2004. Music Synthesis for Home Videos. PhD thesis.

    Google Scholar 

  130. Neo, S.-Y., J. Zhao, M.-Y. Kan, and T.-S. Chua. 2006. Video Retrieval using High Level Features: Exploiting Query Matching and Confidence-Based Weighting. In Proceedings of the Springer International Conference on Image and Video Retrieval, 143–152.

    Google Scholar 

  131. Ngo, C.-W., F. Wang, and T.-C. Pong. 2003. Structuring Lecture Videos for Distance Learning Applications. In Proceedings of the IEEE International Symposium on Multimedia Software Engineering, 215–222.

    Google Scholar 

  132. Nguyen, V.-A., J. Boyd-Graber, and P. Resnik. 2012. SITS: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, 78–87.

    Google Scholar 

  133. Nwana, A.O. and T. Chen. 2016. Who Ordered This?: Exploiting Implicit User Tag Order Preferences for Personalized Image Tagging. In Proceedings of the arXiv preprint arXiv:1601.06439.

    Google Scholar 

  134. Papagiannopoulou, C. and V. Mezaris. 2014. Concept-Based Image Clustering and Summarization of Event-related Image Collections. In Proceedings of the Workshop on HuEvent at the ACM International Conference on Multimedia, 23–28.

    Google Scholar 

  135. Park, M.H., J.H. Hong, and S.B. Cho. 2007. Location-Based Recommendation System using Bayesian User’s Preference Model in Mobile Devices. In Proceedings of the Springer Ubiquitous Intelligence and Computing, 1130–1139.

    Google Scholar 

  136. Petkos, G., S. Papadopoulos, V. Mezaris, R. Troncy, P. Cimiano, T. Reuter, and Y. Kompatsiaris. 2014. Social Event Detection at MediaEval: a Three-Year Retrospect of Tasks and Results. In Proceedings of the Workshop on Social Events in Web Multimedia at ACM International Conference on Multimedia Retrieval.

    Google Scholar 

  137. Pevzner, L., and M.A. Hearst. 2002. A Critique and Improvement of an Evaluation Metric for Text Segmentation. Proceedings of the Computational Linguistics 28(1): 19–36.

    Article  Google Scholar 

  138. Picard, R.W., and J. Klein. 2002. Computers that Recognise and Respond to User Emotion: Theoretical and Practical Implications. Proceedings of the Interacting with Computers 14(2): 141–169.

    Article  Google Scholar 

  139. Picard, R.W., E. Vyzas, and J. Healey. 2001. Toward machine emotional intelligence: Analysis of affective physiological state. Proceedings of the IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10): 1175–1191.

    Article  Google Scholar 

  140. Poisson, S.D. and C.H. Schnuse. 1841. Recherches Sur La Pprobabilité Des Jugements En Mmatieré Criminelle Et En Matieré Civile. Meyer.

    Google Scholar 

  141. Poria, S., E. Cambria, R. Bajpai, and A. Hussain. 2017. A Review of Affective Computing: From Unimodal Analysis to Multimodal Fusion. Proceedings of the Elsevier Information Fusion 37: 98–125.

    Article  Google Scholar 

  142. Poria, S., E. Cambria, and A. Gelbukh. 2016. Aspect Extraction for Opinion Mining with a Deep Convolutional Neural Network. Proceedings of the Elsevier Knowledge-Based Systems 108: 42–49.

    Article  Google Scholar 

  143. Poria, S., E. Cambria, A. Gelbukh, F. Bisio, and A. Hussain. 2015. Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns. Proceedings of the IEEE Computational Intelligence Magazine 10(4): 26–36.

    Article  Google Scholar 

  144. Poria, S., E. Cambria, and A.F. Gelbukh. 2015. Deep Convolutional Neural Network Textual Features and Multiple Kernel Learning for Utterance-level Multimodal Sentiment Analysis. In Proceedings of the EMNLP, 2539–2544.

    Google Scholar 

  145. Poria, S., E. Cambria, D. Hazarika, N. Mazumder, A. Zadeh, and L.-P. Morency. 2017. Context-Dependent Sentiment Analysis in User-Generated Videos. In Proceedings of the Association for Computational Linguistics.

    Google Scholar 

  146. Poria, S., E. Cambria, D. Hazarika, and P. Vij. 2016. A Deeper Look into Sarcastic Tweets using Deep Convolutional Neural Networks. In Proceedings of the International Conference on Computational Linguistics (COLING).

    Google Scholar 

  147. Poria, S., E. Cambria, N. Howard, G.-B. Huang, and A. Hussain. 2016. Fusing Audio Visual and Textual Clues for Sentiment Analysis from Multimodal Content. Proceedings of the Elsevier Neurocomputing 174: 50–59.

    Article  Google Scholar 

  148. Poria, S., E. Cambria, N. Howard, and A. Hussain. 2015. Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining: Extended Abstract. In Proceedings of the International Joint Conference on Artificial Intelligence.

    Google Scholar 

  149. Poria, S., E. Cambria, A. Hussain, and G.-B. Huang. 2015. Towards an Intelligent Framework for Multimodal Affective Data Analysis. Proceedings of the Elsevier Neural Networks 63: 104–116.

    Article  Google Scholar 

  150. Poria, S., E. Cambria, L.-W. Ku, C. Gui, and A. Gelbukh. 2014. A Rule-Based Approach to Aspect Extraction from Product Reviews. In Proceedings of the Second Workshop on Natural Language Processing for Social Media (SocialNLP), 28–37.

    Google Scholar 

  151. Poria, S., I. Chaturvedi, E. Cambria, and F. Bisio. 2016. Sentic LDA: Improving on LDA with Semantic Similarity for Aspect-Based Sentiment Analysis. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), 4465–4473.

    Google Scholar 

  152. Poria, S., I. Chaturvedi, E. Cambria, and A. Hussain. 2016. Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis. In Proceedings of the IEEE International Conference on Data Mining (ICDM), 439–448.

    Google Scholar 

  153. Poria, S., A. Gelbukh, B. Agarwal, E. Cambria, and N. Howard. 2014. Sentic Demo: A Hybrid Concept-level Aspect-Based Sentiment Analysis Toolkit. In Proceedings of the ESWC.

    Google Scholar 

  154. Poria, S., A. Gelbukh, E. Cambria, D. Das, and S. Bandyopadhyay. 2012. Enriching SenticNet Polarity Scores Through Semi-Supervised Fuzzy Clustering. In Proceedings of the IEEE International Conference on Data Mining Workshops (ICDMW), 709–716.

    Google Scholar 

  155. Poria, S., A. Gelbukh, E. Cambria, A. Hussain, and G.-B. Huang. 2014. EmoSenticSpace: A Novel Framework for Affective Common-sense Reasoning. Proceedings of the Elsevier Knowledge-Based Systems 69: 108–123.

    Article  Google Scholar 

  156. Poria, S., A. Gelbukh, E. Cambria, P. Yang, A. Hussain, and T. Durrani. 2012. Merging SenticNet and WordNet-Affect Emotion Lists for Sentiment Analysis. Proceedings of the IEEE International Conference on Signal Processing (ICSP) 2: 1251–1255.

    Google Scholar 

  157. Poria, S., A. Gelbukh, A. Hussain, S. Bandyopadhyay, and N. Howard. 2013. Music Genre Classification: A Semi-Supervised Approach. In Proceedings of the Springer Mexican Conference on Pattern Recognition, 254–263.

    Google Scholar 

  158. Poria, S., N. Ofek, A. Gelbukh, A. Hussain, and L. Rokach. 2014. Dependency Tree-Based Rules for Concept-level Aspect-Based Sentiment Analysis. In Proceedings of the Springer Semantic Web Evaluation Challenge, 41–47.

    Google Scholar 

  159. Poria, S., H. Peng, A. Hussain, N. Howard, and E. Cambria. 2017. Ensemble Application of Convolutional Neural Networks and Multiple Kernel Learning for Multimodal Sentiment Analysis. In Proceedings of the Elsevier Neurocomputing.

    Google Scholar 

  160. Pye, D., N.J. Hollinghurst, T.J. Mills, and K.R. Wood. 1998. Audio-visual Segmentation for Content-Based Retrieval. In Proceedings of the International Conference on Spoken Language Processing.

    Google Scholar 

  161. Qiao, Z., P. Zhang, C. Zhou, Y. Cao, L. Guo, and Y. Zhang. 2014. Event Recommendation in Event-Based Social Networks.

    Google Scholar 

  162. Raad, E.J. and R. Chbeir. 2014. Foto2Events: From Photos to Event Discovery and Linking in Online Social Networks. In Proceedings of the IEEE Big Data and Cloud Computing, 508–515, .

    Google Scholar 

  163. Radsch, C.C.. 2013. The Revolutions will be Blogged: Cyberactivism and the 4th Estate in Egypt. Doctoral Disseration. American University.

    Google Scholar 

  164. Rae, A., B. Sigurbjörnssön, and R. van Zwol. 2010. Improving Tag Recommendation using Social Networks. In Proceedings of the Adaptivity, Personalization and Fusion of Heterogeneous Information, 92–99.

    Google Scholar 

  165. Rahmani, H., B. Piccart, D. Fierens, and H. Blockeel. 2010. Three Complementary Approaches to Context Aware Movie Recommendation. In Proceedings of the ACM Workshop on Context-Aware Movie Recommendation, 57–60.

    Google Scholar 

  166. Rattenbury, T., N. Good, and M. Naaman. 2007. Towards Automatic Extraction of Event and Place Semantics from Flickr Tags. In Proceedings of the ACM Special Interest Group on Information Retrieval.

    Google Scholar 

  167. Rawat, Y. and M. S. Kankanhalli. 2016. ConTagNet: Exploiting User Context for Image Tag Recommendation. In Proceedings of the ACM International Conference on Multimedia, 1102–1106.

    Google Scholar 

  168. Repp, S., A. Groß, and C. Meinel. 2008. Browsing within Lecture Videos Based on the Chain Index of Speech Transcription. Proceedings of the IEEE Transactions on Learning Technologies 1(3): 145–156.

    Article  Google Scholar 

  169. Repp, S. and C. Meinel. 2006. Semantic Indexing for Recorded Educational Lecture Videos. In Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops, 5.

    Google Scholar 

  170. Repp, S., J. Waitelonis, H. Sack, and C. Meinel. 2007. Segmentation and Annotation of Audiovisual Recordings Based on Automated Speech Recognition. In Proceedings of the Springer Intelligent Data Engineering and Automated Learning, 620–629.

    Google Scholar 

  171. Russell, J.A. 1980. A Circumplex Model of Affect. Proceedings of the Journal of Personality and Social Psychology 39: 1161–1178.

    Article  Google Scholar 

  172. Sahidullah, M., and G. Saha. 2012. Design, Analysis and Experimental Evaluation of Block Based Transformation in MFCC Computation for Speaker Recognition. Proceedings of the Speech Communication 54: 543–565.

    Article  Google Scholar 

  173. Salamon, J., J. Serra, and E. Gomez. 2013. Tonal Representations for Music Retrieval: From Version Identification to Query-by-Humming. In Proceedings of the Springer International Journal of Multimedia Information Retrieval 2(1): 45–58.

    Google Scholar 

  174. Schedl, M. and D. Schnitzer. 2014. Location-Aware Music Artist Recommendation. In Proceedings of the Springer MultiMedia Modeling, 205–213.

    Google Scholar 

  175. M. Schedl and F. Zhou. 2016. Fusing Web and Audio Predictors to Localize the Origin of Music Pieces for Geospatial Retrieval. In Proceedings of the Springer European Conference on Information Retrieval, 322–334.

    Google Scholar 

  176. Scherp, A., and V. Mezaris. 2014. Survey on Modeling and Indexing Events in Multimedia. Proceedings of the Springer Multimedia Tools and Applications 70(1): 7–23.

    Article  Google Scholar 

  177. Scherp, A., V. Mezaris, B. Ionescu, and F. De Natale. 2014. HuEvent ‘14: Workshop on Human-Centered Event Understanding from Multimedia. In Proceedings of the ACM International Conference on Multimedia, 1253–1254.

    Google Scholar 

  178. Schmitz, P.. 2006. Inducing Ontology from Flickr Tags. In Proceedings of the Collaborative Web Tagging Workshop at ACM World Wide Web Conference, vol 50.

    Google Scholar 

  179. Schuller, B., C. Hage, D. Schuller, and G. Rigoll. 2010. Mister DJ, Cheer Me Up!: Musical and Textual Features for Automatic Mood Classification. Proceedings of the Journal of New Music Research 39(1): 13–34.

    Article  Google Scholar 

  180. Shah, R.R., M. Hefeeda, R. Zimmermann, K. Harras, C.-H. Hsu, and Y. Yu. 2016. NEWSMAN: Uploading Videos over Adaptive Middleboxes to News Servers In Weak Network Infrastructures. In Proceedings of the Springer International Conference on Multimedia Modeling, 100–113.

    Google Scholar 

  181. Shah, R.R., A. Samanta, D. Gupta, Y. Yu, S. Tang, and R. Zimmermann. 2016. PROMPT: Personalized User Tag Recommendation for Social Media Photos Leveraging Multimodal Information. In Proceedings of the ACM International Conference on Multimedia, 486–492.

    Google Scholar 

  182. Shah, R.R., A.D. Shaikh, Y. Yu, W. Geng, R. Zimmermann, and G. Wu. 2015. EventBuilder: Real-time Multimedia Event Summarization by Visualizing Social Media. In Proceedings of the ACM International Conference on Multimedia, 185–188.

    Google Scholar 

  183. Shah, R.R., Y. Yu, A.D. Shaikh, S. Tang, and R. Zimmermann. 2014. ATLAS: Automatic Temporal Segmentation and Annotation of Lecture Videos Based on Modelling Transition Time. In Proceedings of the ACM International Conference on Multimedia, 209–212.

    Google Scholar 

  184. Shah, R.R., Y. Yu, A.D. Shaikh, and R. Zimmermann. 2015. TRACE: A Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts. In Proceedings of the IEEE International Symposium on Multimedia, 217–220.

    Google Scholar 

  185. Shah, R.R., Y. Yu, S. Tang, S. Satoh, A. Verma, and R. Zimmermann. 2016. Concept-Level Multimodal Ranking of Flickr Photo Tags via Recall Based Weighting. In Proceedings of the MMCommon’s Workshop at ACM International Conference on Multimedia, 19–26.

    Google Scholar 

  186. Shah, R.R., Y. Yu, A. Verma, S. Tang, A.D. Shaikh, and R. Zimmermann. 2016. Leveraging Multimodal Information for Event Summarization and Concept-level Sentiment Analysis. In Proceedings of the Elsevier Knowledge-Based Systems, 102–109.

    Google Scholar 

  187. Shah, R.R., Y. Yu, and R. Zimmermann. 2014. ADVISOR: Personalized Video Soundtrack Recommendation by Late Fusion with Heuristic Rankings. In Proceedings of the ACM International Conference on Multimedia, 607–616.

    Google Scholar 

  188. Shah, R.R., Y. Yu, and R. Zimmermann. 2014. User Preference-Aware Music Video Generation Based on Modeling Scene Moods. In Proceedings of the ACM International Conference on Multimedia Systems, 156–159.

    Google Scholar 

  189. Shaikh, A.D., M. Jain, M. Rawat, R.R. Shah, and M. Kumar. 2013. Improving Accuracy of SMS Based FAQ Retrieval System. In Proceedings of the Springer Multilingual Information Access in South Asian Languages, 142–156.

    Google Scholar 

  190. Shaikh, A.D., R.R. Shah, and R. Shaikh. 2013. SMS Based FAQ Retrieval for Hindi, English and Malayalam. In Proceedings of the ACM Forum on Information Retrieval Evaluation, 9.

    Google Scholar 

  191. Shamma, D.A., R. Shaw, P.L. Shafton, and Y. Liu. 2007. Watch What I Watch: Using Community Activity to Understand Content. In Proceedings of the ACM International Workshop on Multimedia Information Retrieval, 275–284.

    Google Scholar 

  192. Shaw, B., J. Shea, S. Sinha, and A. Hogue. 2013. Learning to Rank for Spatiotemporal Search. In Proceedings of the ACM International Conference on Web Search and Data Mining, 717–726.

    Google Scholar 

  193. Sigurbjörnsson, B. and R. Van Zwol. 2008. Flickr Tag Recommendation Based on Collective Knowledge. In Proceedings of the ACM World Wide Web Conference, 327–336.

    Google Scholar 

  194. Snoek, C.G., M. Worring, and A.W. Smeulders. 2005. Early versus Late Fusion in Semantic Video Analysis. In Proceedings of the ACM International Conference on Multimedia, 399–402.

    Google Scholar 

  195. Snoek, C.G., M. Worring, J.C. Van Gemert, J.-M. Geusebroek, and A.W. Smeulders. 2006. The Challenge Problem for Automated Detection of 101 Semantic Concepts in Multimedia. In Proceedings of the ACM International Conference on Multimedia, 421–430.

    Google Scholar 

  196. Soleymani, M., J.J.M. Kierkels, G. Chanel, and T. Pun. 2009. A Bayesian Framework for Video Affective Representation. In Proceedings of the IEEE International Conference on Affective Computing and Intelligent Interaction and Workshops, 1–7.

    Google Scholar 

  197. Stober, S., and A. . Nürnberger. 2013. Adaptive Music Retrieval – A State of the Art. Proceedings of the Springer Multimedia Tools and Applications 65(3): 467–494.

    Article  Google Scholar 

  198. Stoyanov, V., N. Gilbert, C. Cardie, and E. Riloff. 2009. Conundrums in Noun Phrase Coreference Resolution: Making Sense of the State-of-the-art. In Proceedings of the ACL International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 656–664.

    Google Scholar 

  199. Stupar, A. and S. Michel. 2011. Picasso: Automated Soundtrack Suggestion for Multimodal Data. In Proceedings of the ACM Conference on Information and Knowledge Management, 2589–2592.

    Google Scholar 

  200. Thayer, R.E. 1989. The Biopsychology of Mood and Arousal. New York: Oxford University Press.

    Google Scholar 

  201. Thomee, B., B. Elizalde, D.A. Shamma, K. Ni, G. Friedland, D. Poland, D. Borth, and L.-J. Li. 2016. YFCC100M: The New Data in Multimedia Research. Proceedings of the Communications of the ACM 59(2): 64–73.

    Article  Google Scholar 

  202. Tirumala, A., F. Qin, J. Dugan, J. Ferguson, and K. Gibbs. 2005. Iperf: The TCP/UDP Bandwidth Measurement Tool. http://dast.nlanr.net/Projects/Iperf/

  203. Torralba, A., R. Fergus, and W.T. Freeman. 2008. 80 Million Tiny Images: A Large Data set for Nonparametric Object and Scene Recognition. Proceedings of the IEEE Transactions on Pattern Analysis and Machine Intelligence 30(11): 1958–1970.

    Article  Google Scholar 

  204. Toutanova, K., D. Klein, C.D. Manning, and Y. Singer. 2003. Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. In Proceedings of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, 173–180.

    Google Scholar 

  205. Toutanova, K. and C.D. Manning. 2000. Enriching the Knowledge Sources used in a Maximum Entropy Part-of-Speech Tagger. In Proceedings of the Annual Meeting of the Association for Computational Linguistics, 63–70.

    Google Scholar 

  206. Utiyama, M. and H. Isahara. 2001. A Statistical Model for Domain-Independent Text Segmentation. In Proceedings of the Annual Meeting on Association for Computational Linguistics, 499–506.

    Google Scholar 

  207. Vishal, K., C. Jawahar, and V. Chari. 2015. Accurate Localization by Fusing Images and GPS Signals. In Proceedings of the IEEE Computer Vision and Pattern Recognition Workshops, 17–24.

    Google Scholar 

  208. Wang, C., F. Jing, L. Zhang, and H.-J. Zhang. 2008. Scalable Search-Based Image Annotation. Proceedings of the Springer Multimedia Systems 14(4): 205–220.

    Article  Google Scholar 

  209. Wang, H.L., and L.F. Cheong. 2006. Affective Understanding in Film. Proceedings of the IEEE Transactions on Circuits and Systems for Video Technology 16(6): 689–704.

    Article  Google Scholar 

  210. Wang, J., J. Zhou, H. Xu, T. Mei, X.-S. Hua, and S. Li. 2014. Image Tag Refinement by Regularized Latent Dirichlet Allocation. Proceedings of the Elsevier Computer Vision and Image Understanding 124: 61–70.

    Article  CAS  Google Scholar 

  211. Wang, P., H. Wang, M. Liu, and W. Wang. 2010. An Algorithmic Approach to Event Summarization. In Proceedings of the ACM Special Interest Group on Management of Data, 183–194.

    Google Scholar 

  212. Wang, X., Y. Jia, R. Chen, and B. Zhou. 2015. Ranking User Tags in Micro-Blogging Website. In Proceedings of the IEEE ICISCE, 400–403.

    Google Scholar 

  213. Wang, X., L. Tang, H. Gao, and H. Liu. 2010. Discovering Overlapping Groups in Social Media. In Proceedings of the IEEE International Conference on Data Mining, 569–578.

    Google Scholar 

  214. Wang, Y. and M.S. Kankanhalli. 2015. Tweeting Cameras for Event Detection. In Proceedings of the IW3C2 International Conference on World Wide Web, 1231–1241.

    Google Scholar 

  215. Webster, A.A., C.T. Jones, M.H. Pinson, S.D. Voran, and S. Wolf. 1993. Objective Video Quality Assessment System Based on Human Perception. In Proceedings of the IS&T/SPIE’s Symposium on Electronic Imaging: Science and Technology, 15–26. International Society for Optics and Photonics.

    Google Scholar 

  216. Wei, C.Y., N. Dimitrova, and S.-F. Chang. 2004. Color-Mood Analysis of Films Based on Syntactic and Psychological Models. In Proceedings of the IEEE International Conference on Multimedia and Expo, 831–834.

    Google Scholar 

  217. Whissel, C. 1989. The Dictionary of Affect in Language. In Emotion: Theory, Research and Experience. Vol. 4. The Measurement of Emotions, ed. R. Plutchik and H. Kellerman, 113–131. New York: Academic.

    Google Scholar 

  218. Wu, L., L. Yang, N. Yu, and X.-S. Hua. 2009. Learning to Tag. In Proceedings of the ACM World Wide Web Conference, 361–370.

    Google Scholar 

  219. Xiao, J., W. Zhou, X. Li, M. Wang, and Q. Tian. 2012. Image Tag Re-ranking by Coupled Probability Transition. In Proceedings of the ACM International Conference on Multimedia, 849–852.

    Google Scholar 

  220. Xie, D., B. Qian, Y. Peng, and T. Chen. 2009. A Model of Job Scheduling with Deadline for Video-on-Demand System. In Proceedings of the IEEE International Conference on Web Information Systems and Mining, 661–668.

    Google Scholar 

  221. Xu, M., L.-Y. Duan, C. Xu, M. Kankanhalli, and Q. Tian. 2003. Event Detection in Basketball Video using Multiple Modalities. Proceedings of the IEEE Joint Conference of the Fourth International Conference on Information, Communications and Signal Processing, and Fourth Pacific Rim Conference on Multimedia 3: 1526–1530.

    Google Scholar 

  222. Xu, M., N.C. Maddage, C. Xu, M. Kankanhalli, and Q. Tian. 2003. Creating Audio Keywords for Event Detection in Soccer Video. In Proceedings of the IEEE International Conference on Multimedia and Expo, 2:II–281.

    Google Scholar 

  223. Yamamoto, N., J. Ogata, and Y. Ariki. 2003. Topic Segmentation and Retrieval System for Lecture Videos Based on Spontaneous Speech Recognition. In Proceedings of the INTERSPEECH, 961–964.

    Google Scholar 

  224. Yang, H., M. Siebert, P. Luhne, H. Sack, and C. Meinel. 2011. Automatic Lecture Video Indexing using Video OCR Technology. In Proceedings of the IEEE International Symposium on Multimedia, 111–116.

    Google Scholar 

  225. Yang, Y.H., Y.C. Lin, Y.F. Su, and H.H. Chen. 2008. A Regression Approach to Music Emotion Recognition. Proceedings of the IEEE Transactions on Audio, Speech, and Language Processing 16(2): 448–457.

    Article  Google Scholar 

  226. Ye, G., D. Liu, I.-H. Jhuo, and S.-F. Chang. 2012. Robust Late Fusion with Rank Minimization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3021–3028.

    Google Scholar 

  227. Ye, Q., Q. Huang, W. Gao, and D. Zhao. 2005. Fast and Robust Text Detection in Images and Video Frames. Proceedings of the Elsevier Image and Vision Computing 23(6): 565–576.

    Article  Google Scholar 

  228. Yin, Y., Z. Shen, L. Zhang, and R. Zimmermann. 2015. Spatial temporal Tag Mining for Automatic Geospatial Video Annotation. Proceedings of the ACM Transactions on Multimedia Computing, Communications, and Applications 11(2): 29.

    Google Scholar 

  229. Yoon, S. and V. Pavlovic. 2014. Sentiment Flow for Video Interestingness Prediction. In Proceedings of the Workshop on HuEvent at the ACM International Conference on Multimedia, 29–34.

    Google Scholar 

  230. Yu, Y., K. Joe, V. Oria, F. Moerchen, J.S. Downie, and L. Chen. 2009. Multiversion Music Search using Acoustic Feature Union and Exact Soft Mapping. Proceedings of the World Scientific International Journal of Semantic Computing 3(02): 209–234.

    Article  Google Scholar 

  231. Yu, Y., Z. Shen, and R. Zimmermann. 2012. Automatic Music Soundtrack Generation for Outdoor Videos from Contextual Sensor Information. In Proceedings of the ACM International Conference on Multimedia, 1377–1378.

    Google Scholar 

  232. Zaharieva, M., M. Zeppelzauer, and C. Breiteneder. 2013. Automated Social Event Detection in Large Photo Collections. In Proceedings of the ACM International Conference on Multimedia Retrieval, 167–174.

    Google Scholar 

  233. Zhang, J., X. Liu, L. Zhuo, and C. Wang. 2015. Social Images Tag Ranking Based on Visual Words in Compressed Domain. Proceedings of the Elsevier Neurocomputing 153: 278–285.

    Article  Google Scholar 

  234. Zhang, J., S. Wang, and Q. Huang. 2015. Location-Based Parallel Tag Completion for Geo-tagged Social Image Retrieval. In Proceedings of the ACM International Conference on Multimedia Retrieval, 355–362.

    Google Scholar 

  235. Zhang, M., J. Wong, W. Tavanapong, J. Oh, and P. de Groen. 2004. Media Uploading Systems with Hard Deadlines. In Proceedings of the Citeseer International Conference on Internet and Multimedia Systems and Applications, 305–310.

    Google Scholar 

  236. Zhang, M., J. Wong, W. Tavanapong, J. Oh, and P. de Groen. 2008. Deadline-constrained Media Uploading Systems. Proceedings of the Springer Multimedia Tools and Applications 38(1): 51–74.

    Google Scholar 

  237. Zhang, W., J. Lin, X. Chen, Q. Huang, and Y. Liu. 2006. Video Shot Detection using Hidden Markov Models with Complementary Features. Proceedings of the IEEE International Conference on Innovative Computing, Information and Control 3: 593–596.

    Google Scholar 

  238. Zheng, L., V. Noroozi, and P.S. Yu. 2017. Joint Deep Modeling of Users and Items using Reviews for Recommendation. In Proceedings of the ACM International Conference on Web Search and Data Mining, 425–434.

    Google Scholar 

  239. Zhou, X.S. and T.S. Huang. 2000. CBIR: from Low-level Features to High-level Semantics. In Proceedings of the International Society for Optics and Photonics Electronic Imaging, 426–431.

    Google Scholar 

  240. Zhuang, J. and S.C. Hoi. 2011. A Two-view Learning Approach for Image Tag Ranking. In Proceedings of the ACM International Conference on Web Search and Data Mining, 625–634.

    Google Scholar 

  241. Zimmermann, R. and Y. Yu. 2013. Social Interactions over Geographic-aware Multimedia Systems. In Proceedings of the ACM International Conference on Multimedia, 1115–1116.

    Google Scholar 

  242. Shah, R.R. 2016. Multimodal-based Multimedia Analysis, Retrieval, and Services in Support of Social Media Applications. In Proceedings of the ACM International Conference on Multimedia, 1425–1429.

    Google Scholar 

  243. Shah, R.R. 2016. Multimodal Analysis of User-Generated Content in Support of Social Media Applications. In Proceedings of the ACM International Conference in Multimedia Retrieval, 423–426.

    Google Scholar 

  244. Yin, Y., R.R. Shah, and R. Zimmermann. 2016. A General Feature-based Map Matching Framework with Trajectory Simplification. In Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming, 7.

    Google Scholar 

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  1. School of Computing, National University of Singapore, Singapore, Singapore

    Rajiv Shah & Roger Zimmermann

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  1. Rajiv Shah
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  2. Roger Zimmermann
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Shah, R., Zimmermann, R. (2017). Conclusion and Future Work. In: Multimodal Analysis of User-Generated Multimedia Content. Socio-Affective Computing, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-61807-4_8

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