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基于互动性的网络广告视觉传达设计的有效性。

The Validity of Visual Communication Design of Online Advertisement Based on Interactivity.

机构信息

Taiyuan Normal University, Taiyuan 030619, China.

出版信息

Comput Intell Neurosci. 2022 Jul 8;2022:2485809. doi: 10.1155/2022/2485809. eCollection 2022.

DOI:10.1155/2022/2485809
PMID:35845889
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9286999/
Abstract

Today's society is a society of Internet information, especially the rapid development of new media that is the most distinctive project today. New media has changed the way traditional media are disseminated, and the advertising industry has made new developments with the rapid development of new media, especially with the rise of online advertising, making the dissemination of advertising more influential. In modern advertising information, online advertising has become very influential. This study aims at how to achieve user-matching push and set the right price is the two major problems of Internet advertising push, through the analysis of the emergence and development of network advertising and visual elements in network advertising, starting from the problems appearing in modern online advertisements, and studying the visual communication design in online advertisements. In this paper, a neural network model and a fuzzy comprehensive evaluation decision model are designed; so as to make our online advertisements rich in national characteristics and really cause online users' active clicks. The experimental results show that the proposed method achieves good results and verifies the effectiveness of the model.

摘要

当今社会是一个互联网信息社会,尤其是新媒体的飞速发展是当今最具特色的项目。新媒体改变了传统媒体的传播方式,广告行业随着新媒体的飞速发展也有了新的发展,尤其是网络广告的兴起,使广告的传播更具影响力。在现代广告信息中,网络广告已经变得非常有影响力。本研究旨在如何实现用户匹配推送和设置正确的价格是互联网广告推送的两个主要问题,通过对网络广告的出现和发展以及网络广告中的视觉元素的分析,从现代网络广告中出现的问题出发,研究网络广告中的视觉传达设计。本文设计了神经网络模型和模糊综合评价决策模型;从而使我们的网络广告富有民族特色,真正引起网络用户的主动点击。实验结果表明,所提出的方法取得了良好的效果,验证了模型的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/d45aa189e148/CIN2022-2485809.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/d2b9840a5392/CIN2022-2485809.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/cb26c4e16ccb/CIN2022-2485809.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/297d446b1699/CIN2022-2485809.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/e40af3423801/CIN2022-2485809.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/b465b4f637b5/CIN2022-2485809.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/b14d4fb14960/CIN2022-2485809.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/d45aa189e148/CIN2022-2485809.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/d2b9840a5392/CIN2022-2485809.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/cb26c4e16ccb/CIN2022-2485809.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/297d446b1699/CIN2022-2485809.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/e40af3423801/CIN2022-2485809.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/b465b4f637b5/CIN2022-2485809.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/b14d4fb14960/CIN2022-2485809.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d1b/9286999/d45aa189e148/CIN2022-2485809.007.jpg

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