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MM2RTB: Bringing Multimedia Metrics to Real-Time Bidding

Xiang Chen (National University of Singapore), Bowei Chen (University of Lincoln), Mohan Kankanhalli (National University of Singapore)

In display advertising, users’ online ad experiences are important for the advertising eectiveness. However, users have not been well accommodated in real-time bidding (RTB). is further inu- ences their site visits and perception of the displayed banner ads. In this paper, we propose a novel computational framework which brings multimedia metrics, like the contextual relevance, the visual saliency and the ad memorability into RTB to improve the users’ ad experiences as well as maintain the benets of the publisher and the advertiser. We aim at developing a vigorous ecosystem by optimizing the trade-os among all stakeholders. e frame- work considers the scenario of a webpage with multiple ad slots. Our experimental results show that the benets of the advertiser and the user can be signicantly improved if the publisher would slightly sacrice his short-term revenue. e improved benets will increase the advertising requests (demand) and the site visits (supply), which can further boost the publisher’s revenue in the long run.