Unveiling the Dynamics: Multimedia Analysis and its Impact on Internet, Multimedia, and Digital Media

Authors

  • Gourav Singh UG Student, CSE, Anurag University, Hyderabad

Keywords:

Multimedia, Innovation, Privacy Concerns, Ethical Considerations, Digital Future, Algorithms, Digital Ecosystem

Abstract

This article delves into the transformative impact of multimedia analysis on the interconnected domains of the internet, multimedia, and digital media. As the integration of multimedia content continues to shape our digital experiences, the need for effective analysis becomes paramount. Multimedia analysis involves the extraction of meaningful insights from diverse content forms, enabling a deeper understanding of user preferences, sentiments, and trends. The convergence of the internet and multimedia has given rise to a dynamic digital ecosystem, where personalized content recommendations, enhanced search algorithms, and improved content delivery are facilitated by advanced analysis techniques. The evolution of digital media, coupled with immersive technologies like virtual and augmented reality, underscores the pivotal role of multimedia analysis in refining user experiences. While presenting opportunities for innovation, the article also addresses challenges such as privacy concerns and ethical considerations. Navigating these challenges and harnessing the potential of multimedia analysis is crucial for shaping a rich and personalized digital future.

References

Pouyanfar S, Yang Y, Chen SC, Shyu ML, Iyengar SS. Multimedia big data analytics: A survey. ACM computing surveys (CSUR). 2018 Jan 10;51(1):1-34.

Bashir F, Khanvilkar S, Schonfeld D, Khokhar A. Multimedia systems: content-based indexing and retrieval. The Electrical Engineering Handbook, Sect. 2005 Jan 1;4.

Bhatt CA, Kankanhalli MS. Multimedia data mining: state of the art and challenges. Multimedia Tools and Applications. 2011 Jan;51:35-76.

Hanjalic A, Xu LQ. Affective video content representation and modeling. IEEE transactions on multimedia. 2005 Jan 24;7(1):143-54.

Datta R, Joshi D, Li J, Wang JZ. Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys (Csur). 2008 May 8;40(2):1-60.

Breuer R, Kimmel R. A deep learning perspective on the origin of facial expressions. arXiv preprint arXiv:1705.01842. 2017 May 4.

Schütze H, Manning CD, Raghavan P. Introduction to information retrieval. Cambridge: Cambridge University Press; 2008 Jun 24.

Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering. 2005 Apr 25;17(6):734-49.

Sarwar B, Karypis G, Konstan J, Riedl JT. Application of dimensionality reduction in recommender system-a case study.

Roma P, Aloini D. How does brand-related user-generated content differ across social media? Evidence reloaded. Journal of Business Research. 2019 Mar 1;96:322-39.

Van Dijck J. The culture of connectivity: A critical history of social media. Oxford University Press; 2013 Jan 2.

Koch T, Gerber C, De Klerk JJ. The impact of social media on recruitment: Are you LinkedIn?. SA Journal of Human Resource Management. 2018 May 7;16(1):1-4.

Pritch Y, Rav-Acha A, Peleg S. Video Synopsis and Indexing.

Published

2023-12-28