International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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From Multimedia Data Mining to Multimedia Big Data Mining

  • Received : 2022.11.05
  • Published : 2022.11.30
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Abstract

With the collection of huge volumes of text, image, audio, video or combinations of these, in a word multimedia data, the need to explore them in order to discover possible new, unexpected and possibly valuable information for decision making was born. Starting from the already existing data mining, but not as its extension, multimedia mining appeared as a distinct field with increased complexity and many characteristic aspects. Later, the concept of big data was extended to multimedia, resulting in multimedia big data, which in turn attracted the multimedia big data mining process. This paper aims to survey multimedia data mining, starting from the general concept and following the transition from multimedia data mining to multimedia big data mining, through an up-to-date synthesis of works in the field, which is a novelty, from our best of knowledge.

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References

  1. Emily Adler. 2016. Social media engagement: The surprising facts about how much time people spend on the major social networks. Retrieved from http://www.businessinsider.com/social-media-engagementstatistics-2013-12
  2. Paraschiv A, Danubianu M, Big Data - present Opportunities and Challenges, Broad Research in Artificial Intelligence and Neuroscience - BRAIN, vol. 10(2), 2019
  3. Cios K., Pedrycz W., Swiniarski R., Kurgan L. (2007) Data Mining. A Knowledge Discovery Approach, Springer Science-Business Media, ISBN 978-0-387-33333-5, New York
  4. Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI magazine, 17(3), 37-37.
  5. Wirth, R. and Hipp, J., CRISP-DM: Towards a standard process model for data mining. In Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining, pages 29-39, Manchester, UK, 2000
  6. Patel N., Sethi I., "Multimedia Data Mining: An Overview" 2007 DOI:10.1007/978-1-84628-799-2_2
  7. Addi Ait-Mlouk, Tarik Agouti, Fatima Gharnati "Multi-criteria decisional approach for extracting relevant association rules", 2016 International Journal of Computational Science and Engineering 15(3/4) DOI:10.1504/IJCSE.2017.10008087
  8. Danubianu, M., Pentiuc, S. G., & Danubianu, D. M. "Data dimensionality reduction for data mining: a combined filter-wrapper framework.", 2014 International Journal of Computers Communications & Control, 7(5), 824-831. https://doi.org/10.15837/ijccc.2012.5.1337
  9. Danubianu, M., Pentiuc, S. G. "Data dimensionality reduction framework for data mining", Elektronika ir Elektrotechnika, 19(4), 87-90, 2013
  10. Danubianu M., "A data preprocessing framework for students' outcome prediction by data mining techniques" In 2015 19th International Conference on System Theory, Control and Computing (ICSTCC) 2015 Oct 14 (pp. 836-841). IEEE
  11. Danubianu M., I. Tobolcea I., "Using data mining approach for personalizing the therapy of dyslalia," 2011 E-Health and Bioengineering Conference (EHB), 2011, pp. 1-4.
  12. Hall, M., Correlation-based feature selection for discrete and numeric class machine learning, Proc. Of International Conference on Machine Learning, 359-365, Morgan Kaufmann, 2000
  13. Douik A., Abdellaoui M., Cereal Grain Classification by Optimal Features and Intelligent Classifiers, International Journal of Computers Communications & Control, ISSN 1841-9836, 5(4):506-516, 2010. https://doi.org/10.15837/ijccc.2010.4.2508
  14. Yu, C., Williams, A., Lin, C. F., & Yu, W. C. (2008). Planning effective multimedia instruction. In Terry T. Kidd & Holim Song (Eds.), Instructional systems and technology (Vol. 1, pp. 216-231). Hershey, PA: Information Science Reference.
  15. Kalipsiz, O. (2000). Multimedia databases. Proceedings of IEEE International Conference, 111-115. Retrieved May4,2009, from: http://ieeexplore.ieee.org.proxy.library.msstate.edu/stamp/stamp.jsp?tp=&arnumber=859745&isnumber=18614
  16. Adjeroh, D.A. Nwosu, K.C. (1997). Multimedia database management: Requirements and issues. Multimedia, IEEE, 4(3), 24-33. Retrieved May 25, 2009, from http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=621580&isnumber=13526
  17. Manjunath BS, Salembier Ph, Sikora T (Eds.). Introduction to MPEG-7. Multimedia Content Description Interface. Wiley, New York, 2002, 371 p.
  18. https://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf
  19. https://www.elderresearch.com/blog/42-v-of-big-data
  20. Danubianu M., Barila A. (2014) Big Data vs. Data Mining for Social Media Analytics, International Conference of Social Media in Academia - Research and Teaching-SMART2014
  21. https://www.ibmbigdatahub.com/infographic/four-vs-big-data
  22. Petrushin V, Introduction into multimedia Data Mining and Knowledge Discovery, Multimedia Data Mining and Knowledge Discovery, Springer - Verlag, 2007
  23. https://www.javatpoint.com/what-is-multimedia-data-mining
  24. Vijayakumar.V, A. Sakila, "Multimedia Minig Research - an Overview", The International Journal of Computer Graphics & Animation (IJCGA) Vol.5, No.1, January 2015
  25. Wynne H, Lee ML, Zhang J (2002) Image mining: trends and developments. J Intell Inf Syst 19(1):7-23 https://doi.org/10.1023/A:1015508302797
  26. Bhatt, C.A., Kankanhalli, M.S. Multimedia data mining: state of the art and challenges. Multimed Tools Appl 51, 35-76(2011). https://doi.org/10.1007/s11042-010-0645-5
  27. Barnard K, Duygulu P, Forsyth D, Freitas N, Blei D, Jordan M. Matching words and pictures. J. Machine Learning Reearch 3, 3 (2003), 1107-1135.
  28. Feng S.L., Manmatha R, and Lavrenko V. Multiple Bernoulli relevance models for image and video annotation. In Proceedings International Conference on Computer Vision and Pattern Recognition, 2004.Washington, DC.
  29. Norvag K, Oivind Eriksen T, Skogstad KI (2006) Mining association rules in temporal document collections. In: International symposium on methodologies for intelligent systems (ISMIS), pp 745-754
  30. Zhang, Ji and Hsu, Wynne and Lee, Mong Li Image mining: issues, frameworks and techniques. In: 2nd ACM SIGKDD International Workshop on Multimedia Data Mining (MDM/KDD'01), 26 Aug 2001, San Francisco, CA, USA
  31. Ajmera J, McCowan I, Bourlard H (2002) Robust hmm-based speech/music segmentation. In: IEEE international conference on acoustics, speech and signal processing, pp 1746-1749
  32. Meinedo H, Neto J (2005) A stream-based audio segmentation, classification and clustering pre-processing system for broadcast news using ann models. In: Interspeech-Eurospeech
  33. Shirahama K, Sugihara C, Matsumura K, Matsuoka Y, Uehara K (2009) Mining event definitions from queries for video retrieval on the internet. In: International conference on data mining workshops, pp 176-183
  34. Lin L, Shyu ML (2009) Mining high-level features from video using associations and correlations. In: International conference on semantic computing, pp 137-144