IMPROVING FASHION INDUSTRY USING ARTIFICIAL INTELLIGENCE-ENABLED IN-VIDEO ADVERTISEMENTS

Akshay Shah, S. Nasnodkar
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Abstract

It is crucial for advertisers to comprehend the video context when directing video adverts at consumers, given the growing audience for online video content. Important elements like ad relevancy to video content, where and how video advertisements are displayed, and non-intrusive user experience are required to be looked at in sequence to enhance the consumer experience and quality of commercials. We suggest a methodology for better ad suggestion that meets these requirements by understanding the video content semantically. The study focuses on how machine learning technology has significantly influenced the usage of in-video advertisements as a part of the content advertising approach for fashion brands. Every company wants to get in front of consumers when they are most receptive to persuasion. However, because there are so many options for customers, digital media are generating distinctive customer journeys that take an independent tack. Therefore, there is a need for more compelling advertising strategies to grab consumers' attention and make it possible for them to find companies at peak demand periods.
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利用人工智能视频广告改善时尚产业
考虑到在线视频内容的受众不断增长,广告商在向消费者投放视频广告时,理解视频上下文是至关重要的。广告与视频内容的相关性、视频广告的展示位置和方式、非侵入式用户体验等重要元素都需要依次考虑,以提高消费者体验和广告质量。我们提出了一种更好的广告建议方法,通过理解视频内容的语义来满足这些要求。这项研究的重点是机器学习技术如何显著影响视频广告的使用,作为时尚品牌内容广告方法的一部分。每个公司都想在消费者最容易接受说服的时候站在他们面前。然而,由于客户有如此多的选择,数字媒体正在产生独特的客户旅程,采取独立的策略。因此,需要更有说服力的广告策略来吸引消费者的注意力,并使他们有可能在需求高峰期找到公司。
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