activity
20182021
most citedEstimating Individual Advertising Effect in E-Commerce

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.AI2021

Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search

Ziyu Guan, Hongchang Wu, Qingyu Cao +7

Bid optimization for online advertising from single advertiser's perspective has been thoroughly investigated in both academic research and industrial practice. However, existing w…

cs.IR2019

IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

Jun Zhao, Zhou Zhou, Ziyu Guan +4

The remarkable progress of network embedding has led to state-of-the-art algorithms in recommendation. However, the sparsity of user-item interactions (i.e., explicit preferences)…

cs.IR2019

Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Wei Zhao, Boxuan Zhang, Beidou Wang +6

We study a novel problem of sponsored search (SS) for E-Commerce platforms: how we can attract query users to click product advertisements (ads) by presenting them features of prod…

cs.GT20191 cited

Estimating Individual Advertising Effect in E-Commerce

Hao Liu, Yunze Li, Qinyu Cao +2

Online advertising has been the major monetization approach for Internet companies. Advertisers invest budgets to bid for real-time impressions to gain direct and indirect returns.…

cs.GT2018

CIA-Towards a Unified Marketing Optimization Framework for e-Commerce Sponsored Search

Hao Liu, Qinyu Cao, Xinru Liao +3

As the largest e-commerce platform, Taobao helps advertisers reach billions of search queries each day via sponsored search, which has also contributed considerable revenue to the…

cs.AI2018

Deep Reinforcement Learning for Sponsored Search Real-time Bidding

Jun Zhao, Guang Qiu, Ziyu Guan +2

Bidding optimization is one of the most critical problems in online advertising. Sponsored search (SS) auction, due to the randomness of user query behavior and platform nature, us…