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Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure by Chen, Jin; Ge, Tiezheng; Jiang, Gangwei; Zhang, Zhiqiang; Lian, Defu; Zheng, Kai is a scholarly article available to read on EtoBox.

What is Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure about?

Ad creatives are one of the prominent mediums for online e-commerce advertisements. Ad creatives with enjoyable visual appearance may increase the click-through rate (CTR) of products. Ad creatives are typically handcrafted by advertisers and then delivered to the advertising platforms for advertisement. In recent years, advertising platforms are capable of instantly compositing ad creatives with arbitrarily designated elements of each ingredient, so advertisers are only required to provide basic materials. While facilitating the advertisers, a great number of potential ad creatives can be composited, making it difficult to accurately estimate CTR for them given limited real-time feedback. To this end, we propose an Adaptive and Efficient ad creative Selection (AES) framework based on a tree structure. The tree structure on compositing ingredients enables dynamic programming for efficient ad creative selection on the basis of CTR. Due to limited feedback, the CTR estimator is usually of high variance. Exploration techniques based on Thompson sampling are widely used for reducing variances of the CTR estimator, alleviating feedback sparsity. Based on the tree structure, Thompson sam

Author

Chen, Jin; Ge, Tiezheng; Jiang, Gangwei; Zhang, Zhiqiang; Lian, Defu; Zheng, Kai

Published

2021

Language

EN