Revolutionizing E-Commerce - Deep Learning and Distributed Expression for Cutting-Edge Product Advertising

P, Elantheraiyan and K, Vinayagam and P, Sasikumar and M, Kotteeswaran and K S, Thirunavukkarasu and K, Sankar Singh (2023) Revolutionizing E-Commerce - Deep Learning and Distributed Expression for Cutting-Edge Product Advertising. In: 2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), Chennai, India.

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Revolutionizing E-Commerce - Deep Learning and Distributed Expression for Cutting-Edge Product Advertising _ IEEE Conference Publication _ IEEE Xplore.pdf

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Abstract

This research paper explores the revolutionary potential of leveraging deep learning techniques and distributed expression strategies to transform the landscape of e-commerce product advertising. With the exponential growth of online shopping, effective product advertising has become a critical aspect of capturing consumer attention and driving sales. In this study, the research delves into the application of deep learning algorithms for analyzing vast amounts of product data, enabling automated content generation, personalized recommendations, and improved understanding of consumer behavior. Additionally, the research investigates the benefits of employing distributed expression methods to enhance the reach and impact of product advertisements across various online platforms. By combining the power of deep learning with distributed expression, businesses can create cutting-edge advertising campaigns that are not only highly engaging but also tailored to individual customer preferences. Through real-world case studies and performance evaluations, the research highlights the significant potential of this approach in revolutionizing e-commerce product advertising and its implications for the future of online retail.

Item Type: Conference or Workshop Item (Paper)
Subjects: Management Studies > Decision-Making
Divisions: Management Studies
Depositing User: Mr IR Admin
Date Deposited: 21 Sep 2024 05:53
Last Modified: 21 Sep 2024 05:53
URI: https://ir.vistas.ac.in/id/eprint/6796

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