Interactive Multimodal Television Media Adaptive Visual Communication Based on Clustering Algorithm

This article starts with the environmental changes in human cognition, analyzes the virtual as the main feature of visual perception under digital technology, and explores the transition from passive to active human cognitive activities. With the diversified understanding of visual information, huma...

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Veröffentlicht in:Complexity (New York, N.Y.) Jg. 2020; H. 2020; S. 1 - 9
Hauptverfasser: Yang, Huayuan, Zhang, Xin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Publishing Corporation 30.12.2020
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John Wiley & Sons, Inc
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ISSN:1076-2787, 1099-0526
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Abstract This article starts with the environmental changes in human cognition, analyzes the virtual as the main feature of visual perception under digital technology, and explores the transition from passive to active human cognitive activities. With the diversified understanding of visual information, human contradiction of memory also began to become prominent. Aiming at the problem that the existing multimodal TV media recognition methods have low recognition rate of unknown application layer protocols, an adaptive clustering method for identifying unknown application layer protocols is proposed. This method clusters application layer protocols based on similarity of the load characteristics of network stream application layer protocol data. The method divides the similarity calculation in the clustering algorithm to improve the clustering efficiency of the algorithm. Experimental results show that the proposed method can efficiently and accurately recognize unknown visual communication. This article proposes that, in the interactive multimodal visual information transmission, human visual perception experience has changed, the diversity of visual information content expression makes the aesthetic subject more personalized and stylized.
AbstractList This article starts with the environmental changes in human cognition, analyzes the virtual as the main feature of visual perception under digital technology, and explores the transition from passive to active human cognitive activities. With the diversified understanding of visual information, human contradiction of memory also began to become prominent. Aiming at the problem that the existing multimodal TV media recognition methods have low recognition rate of unknown application layer protocols, an adaptive clustering method for identifying unknown application layer protocols is proposed. This method clusters application layer protocols based on similarity of the load characteristics of network stream application layer protocol data. The method divides the similarity calculation in the clustering algorithm to improve the clustering efficiency of the algorithm. Experimental results show that the proposed method can efficiently and accurately recognize unknown visual communication. This article proposes that, in the interactive multimodal visual information transmission, human visual perception experience has changed, the diversity of visual information content expression makes the aesthetic subject more personalized and stylized.
Audience Academic
Author Zhang, Xin
Yang, Huayuan
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ContentType Journal Article
Copyright Copyright © 2020 Huayuan Yang and Xin Zhang.
COPYRIGHT 2020 John Wiley & Sons, Inc.
Copyright © 2020 Huayuan Yang and Xin Zhang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Adaptive algorithms
Aesthetics
Algorithms
Classification
Clustering
Cognition
Cognition & reasoning
Design techniques
Digital technology
Information dissemination
Information management
Light
Methods
Neural networks
Protocol
Protocol (computers)
Recognition
Similarity
Television
User behavior
Visual communication
Visual perception
Visual perception driven algorithms
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Title Interactive Multimodal Television Media Adaptive Visual Communication Based on Clustering Algorithm
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