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Ten Research Questions for Scalable Multimedia Analytics

Part of the Lecture Notes in Computer Science book series (LNISA,volume 9517)

Abstract

The scale and complexity of multimedia collections is ever increasing, as is the desire to harvest useful insight from the collections. To optimally support the complex quest for insight, multimedia analytics has emerged as a new research area that combines concepts and techniques from multimedia analysis and visual analytics into a single framework. State of the art multimedia analytics solutions are highly interactive and give users freedom in how they perform their analytics task, but they do not scale well. State of the art scalable database management solutions, on the other hand, are not yet designed for multimedia analytics workloads. In this position paper we therefore argue the need for research on scalable multimedia analytics, a new research area built on the three pillars of visual analytics, multimedia analysis and database management. We propose a specific goal for scalable multimedia analytics and present several important research questions that we believe must be addressed in order to achieve that goal.

Keywords

  • Query Processing
  • Database Management
  • Analytic Task
  • Multimedia Data
  • Business Analytic

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    The requirements are sometimes given as four, six or even seven Vs. The additional Vs—veracity, validity, viability and value—are not important for this discussion.

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Acknowledgments

This work was in part supported by the CNRS PICS grant “MMAnalytics” and by sabbatical support from Reykjavik University. Thanks go to the anonymous reviewers, for comments that helped improve the paper.

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Correspondence to Björn Þór Jónsson .

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Jónsson, B.Þ., Worring, M., Zahálka, J., Rudinac, S., Amsaleg, L. (2016). Ten Research Questions for Scalable Multimedia Analytics. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9517. Springer, Cham. https://doi.org/10.1007/978-3-319-27674-8_26

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  • DOI: https://doi.org/10.1007/978-3-319-27674-8_26

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