2021
DOI: 10.48550/arxiv.2110.06475
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SAR-Net: A Scenario-Aware Ranking Network for Personalized Fair Recommendation in Hundreds of Travel Scenarios

Qijie Shen,
Wanjie Tao,
Jing Zhang
et al.

Abstract: The travel marketing platform of Alibaba serves an indispensable role for hundreds of different travel scenarios from Fliggy, Taobao, Alipay apps, etc. To provide personalized recommendation service for users visiting different scenarios, there are two critical issues to be carefully addressed. First, since the traffic characteristics of different scenarios, e.g., individual data scale or representative topic, are significantly different, it is very challenging to train a unified model to serve all. Second, du… Show more

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“…As we know, CTR is playing a crucial role in recommendation [2,12,15,16,29,30], which aims to predict the probability of users clicking items. Recently, inspired by the success of deep learning in various research fields, ๐‘’.๐‘”., natural language processing [5,11,27] and computer vision [6,9,20], deep learning based methods also have been proposed for the CTR prediction task, such as PNN [14], DeepFM [4], and DCN [21].…”
Section: Introductionmentioning
confidence: 99%
“…As we know, CTR is playing a crucial role in recommendation [2,12,15,16,29,30], which aims to predict the probability of users clicking items. Recently, inspired by the success of deep learning in various research fields, ๐‘’.๐‘”., natural language processing [5,11,27] and computer vision [6,9,20], deep learning based methods also have been proposed for the CTR prediction task, such as PNN [14], DeepFM [4], and DCN [21].…”
Section: Introductionmentioning
confidence: 99%