Volume 18 • Issue 4 • PP: 344-354 • 2022
Application of new media retrieval system based on Neutrosophic in marketing
Open Access & Copyright
© 2022 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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The new media is a crucial ply role in the market. The new media growth rapidly in the market so, select consumers and companies for competition. So, the new media is a complex task for companies and firms. The new media retrieval contains much content such as image retrieval, audio and video retrieval. The new media retrieval contains many criteria, and each criterion contains sub-criteria. So, use an MCDM method for dealing with this problem. The new media retrieval system is analyzing under a neutrosophic environment. The Decision-making trial and evaluation laboratory (DEMATEL) integrated with single-valued neutrosophic. DEMATEL method used to show importance and impact criteria of new media retrieval for helping companies in market competition. An example is provided for showing calculations.
Keywords
References
[1] N. C. Maddage, C. Xu, M. S. Kankanhalli, and X. Shao, ―Content-based music structure analysis with
applications to music semantics understanding,‖ in Proceedings of the 12th annual ACM international
conference on Multimedia, 2004, pp. 112–119.
[2] X. He, W.-Y. Ma, and H.-J. Zhang, ―Learning an image manifold for retrieval,‖ in Proceedings of the
12th annual ACM international conference on Multimedia, 2004, pp. 17–23.
[3] E. Chang, K. Goh, G. Sychay, and G. Wu, ―CBSA: content-based soft annotation for multimodal image
retrieval using Bayes point machines,‖ IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 1, pp.
26–38, 2003.
[4] J. Z. Wang, G. Wiederhold, O. Firschein, and S. X. Wei, ―Content-based image indexing and searching
using Daubechies’ wavelets,‖ Int. J. Digit. Libr., vol. 1, no. 4, pp. 311–328, 1998.
[5] Y. Zhuang, C. Wu, F. Wu, and X. Liu, ―Improving web-based learning: Automatic annotation of
multimedia semantics and cross-media indexing,‖ in International Conference on Web-Based
Learning, 2004, pp. 255–262.
[6] M. Müller, T. Röder, and M. Clausen, ―Efficient content-based retrieval of motion capture data,‖ in
ACM SIGGRAPH 2005 Papers, 2005, pp. 677–685.
[7] J. Fan, A. K. Elmagarmid, X. Zhu, W. G. Aref, and L. Wu, ―ClassView: hierarchical video shot
classification, indexing, and accessing,‖ IEEE Trans. Multimed., vol. 6, no. 1, pp. 70–86, 2004.
[8] S. W. Smoliar and H. Zhang, ―Content based video indexing and retrieval,‖ IEEE Multimed., vol. 1, no.
2, pp. 62–72, 1994.
[9] G. Guo and S. Z. Li, ―Content-based audio classification and retrieval by support vector machines,‖
IEEE Trans. Neural Networks, vol. 14, no. 1, pp. 209–215, 2003.
[10] E. Triantaphyllou, ―Multi-criteria decision making methods,‖ in Multi-criteria decision making
methods: A comparative study, Springer, 2000, pp. 5–21.
[11] R. Şahin and A. Küçük, ―Subsethood measure for single valued neutrosophic sets,‖ J. Intell. Fuzzy
Syst., vol. 29, no. 2, pp. 525–530, 2015.
[12] W. Ho, X. Xu, and P. K. Dey, ―Multi-criteria decision making approaches for supplier evaluation and
selection: A literature review,‖ Eur. J. Oper. Res., vol. 202, no. 1, pp. 16–24, 2010.
[13] E. Triantaphyllou, B. Shu, S. N. Sanchez, and T. Ray, ―Multi-criteria decision making: an operations
research approach,‖ Encycl. Electr. Electron. Eng., vol. 15, no. 1998, pp. 175–186, 1998.
[14] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, and J.-H. Zhao, ―Review on multi-criteria decision analysis aid in
sustainable energy decision-making,‖ Renew. Sustain. energy Rev., vol. 13, no. 9, pp. 2263–2278, 2009.
[15] M. Velasquez and P. T. Hester, ―An analysis of multi-criteria decision making methods,‖ Int. J. Oper.
Res., vol. 10, no. 2, pp. 56–66, 2013.
[16] H. Huang, ―New distance measure of single‐valued neutrosophic sets and its application,‖ Int. J. Intell.
Syst., vol. 31, no. 10, pp. 1021–1032, 2016.
[17] S. Broumi, M. Talea, A. Bakali, and F. Smarandache, ―Single valued neutrosophic graphs,‖ J. New
theory, no. 10, pp. 86–101, 2016.
[18] M. Saqlain, N. Jafar, S. Moin, M. Saeed, and S. Broumi, ―Single and multi-valued neutrosophic
hypersoft set and tangent similarity measure of single valued neutrosophic hypersoft sets,‖
Neutrosophic Sets Syst., vol. 32, no. 1, pp. 317–329, 2020.
[19] H. Wang, F. Smarandache, Y. Zhang, and R. Sunderraman, Single valued neutrosophic sets. Infinite
study, 2010.
[20] M. Abdel-Basset, A. Gamal, N. Moustafa, A. Abdel-Monem, and N. El-Saber, ―A Security-by-Design
Decision-Making Model for Risk Management in Autonomous Vehicles,‖ IEEE Access, 2021.
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