Abstract
In a fast-changing media ecosystem, professionals and enterprises in the News and Media industry face new challenges that they should address to maximize their productivity and improve their services. The rise of alternative news sources, such as social media, the leading news source, especially for young people, has led to emerging requirements in the News and Media industry. A core requirement is publishing articles as fast as possible on various platforms, combining visual and textual content. Accompanying news with images raises the readers’ interest, improves engagement, and recall. Therefore, the News and Media industry professionals must adapt their publication strategies to meet this requirement and the media consumers’ expectations. However, the selection of the appropriate images is a time-consuming and manual task. Towards this direction, we propose VIREO, which addresses this challenge by providing professionals (e.g., journalists) with an integrated digital solution that automatically recommends a collection of images that could accompany an article. VIREO implements text and image analysis and matching processes leveraging AI techniques in real time to achieve this. VIREO aims to benefit both professionals (e.g., journalists) by suggesting appealing images that accompany the textual content of their articles and create breath-taking stories and the media consumers (e.g., readers) by delivering an enhanced reading experience, engagement, and recall.
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Acknowledgment
VIREO has indirectly received funding from the European Union’s Horizon 2020 research and innovation action programme, via the AI4Media Open Call #2 issued and executed under the AI4Media project (Grant Agreement no. 951911).
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Raptis, G.E., Theodorou, V., Katsini, C. (2023). Towards Enhancing the Media Industry Through AI-Driven Image Recommendations. In: Abdelnour Nocera, J., Kristín Lárusdóttir, M., Petrie, H., Piccinno, A., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2023. INTERACT 2023. Lecture Notes in Computer Science, vol 14145. Springer, Cham. https://doi.org/10.1007/978-3-031-42293-5_75
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DOI: https://doi.org/10.1007/978-3-031-42293-5_75
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