Fourteenth ACM Conference on Recommender Systems 2020
DOI: 10.1145/3383313.3412234
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Contextual User Browsing Bandits for Large-Scale Online Mobile Recommendation

Abstract: Online recommendation services recommend multiple commodities to users. Nowadays, a considerable proportion of users visit e-commerce platforms by mobile devices. Due to the limited screen size of mobile devices, positions of items have a significant influence on clicks: 1) Higher positions lead to more clicks for one commodity. 2) The 'pseudo-exposure' issue: Only a few recommended items are shown at first glance and users need to slide the screen to browse other items. Therefore, some recommended items ranke… Show more

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Cited by 6 publications
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