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- W3198517287 abstract "E-commerce platforms usually display a mixed list of ads and organic items in feed. One key problem is to allocate the limited slots in the feed to maximize the overall revenue as well as improve user experience, which requires a good model for user preference. Instead of modeling the influence of individual items on user behaviors, the arrangement signal models the influence of the arrangement of items and may lead to a better allocation strategy. However, most of previous strategies fail to model such a signal and therefore result in suboptimal performance. In addition, the percentage of ads exposed (PAE) is an important indicator in ads allocation. Excessive PAE hurts user experience while too low PAE reduces platform revenue. Therefore, how to constrain the PAE within a certain range while keeping personalized recommendation under the PAE constraint is a challenge." @default.
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- W3198517287 date "2022-04-25" @default.
- W3198517287 modified "2023-10-17" @default.
- W3198517287 title "Cross DQN: Cross Deep Q Network for Ads Allocation in Feed" @default.
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- W3198517287 doi "https://doi.org/10.1145/3485447.3512109" @default.
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