mlsanityData to 7 Oct 2026

Optimized Cost per Click in Taobao Display Advertising

arXiv 1703.02091 ↗First posted 27 Feb 2017cs.GT stat.MLcited by 57

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Abstract (arXiv)

Taobao, as the largest online retail platform in the world, provides billions of online display advertising impressions for millions of advertisers every day. For commercial purposes, the advertisers bid for specific spots and target crowds to compete for business traffic. The platform chooses the most suitable ads to display in tens of milliseconds. Common pricing methods include cost per mille (CPM) and cost per click (CPC). Traditional advertising systems target certain traits of users and ad placements with fixed bids, essentially regarded as coarse-grained matching of bid and traffic quality. However, the fixed bids set by the advertisers competing for different quality requests cannot fully optimize the advertisers' key requirements. Moreover, the platform has to be responsible for the business revenue and user experience. Thus, we proposed a bid optimizing strategy called optimized cost per click (OCPC) which automatically adjusts the bid to achieve finer matching of bid and traffic quality of page view (PV) request granularity. Our approach optimizes advertisers' demands, platform business revenue and user experience and as a whole improves traffic allocation efficiency. We have validated our approach in Taobao display advertising system in production. The online A/B test shows our algorithm yields substantially better results than previous fixed bid manner.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Feb 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 8; 2022: 11; 2023: 8; 2024: 10; 2025: 10; 2026: 10.

57 papers.

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  1. 2021One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Predictioncited by 78
  2. 2021Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertisingcited by 31
  3. 2024Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insightscited by 23
  4. 2022Joint Optimization of Ranking and Calibration with Contextualized Hybrid Modelcited by 22
  5. 2021Hierarchically Modeling Micro and Macro Behaviors via Multi-Task Learning for Conversion Rate Predictioncited by 21
  6. 2023Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendationscited by 15
  7. 2022Vertical Semi-Federated Learning for Efficient Online Advertisingcited by 12
  8. 2022KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Pluggingcited by 11
  9. 2022Challenges and approaches to privacy preserving post-click conversion predictioncited by 10
  10. 2023Natural Language Generation for Advertising: A Surveycited by 10
  11. 2024An Automatic Graph Construction Framework based on Large Language Models for Recommendationcited by 8
  12. 2021Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Searchcited by 7
38 more
  1. 2022Hierarchically Constrained Adaptive Ad Exposure in Feedscited by 6
  2. 2024Conditional Quantile Estimation for Uncertain Watch Time in Short-Video Recommendationcited by 6
  3. 2021We Know What You Want: An Advertising Strategy Recommender System for Online Advertisingcited by 5
  4. 2021Online Advertising Revenue Forecasting: An Interpretable Deep Learning Approachcited by 5
  5. 2023Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge Conceptscited by 5
  6. 2025See Beyond a Single View: Multi-Attribution Learning Leads to Better Conversion Rate Predictioncited by 5
  7. 2025Generative Auto-Bidding in Large-Scale Competitive Auctions via Diffusion Completer-Alignercited by 5
  8. 2023HiBid: A Cross-Channel Constrained Bidding System with Budget Allocation by Hierarchical Offline Deep Reinforcement Learningcited by 4
  9. 2024Deep Ensemble Shape Calibration: Multi-Field Post-hoc Calibration in Online Advertisingcited by 4
  10. 2024Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendationcited by 4
  11. 2025Relative Advantage Debiasing for Watch-Time Prediction in Short-Video Recommendationcited by 4
  12. 2021Truncation-Free Matching System for Display Advertising at Alibabacited by 3
  13. 2024Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Modelcited by 3
  14. 2022On-Device Model Fine-Tuning with Label Correction in Recommender Systemscited by 2
  15. 2023Enhancing Personalized Ranking With Differentiable Group AUC Optimizationcited by 2
  16. 2023Graph Based Long-Term And Short-Term Interest Model for Click-Through Rate Predictioncited by 2
  17. 2023Contrastive Learning for Conversion Rate Predictioncited by 2
  18. 2024UnifiedRL: A Reinforcement Learning Algorithm Tailored for Multi-Task Fusion in Large-Scale Recommender Systemscited by 2
  19. 2024Multi-Task Combinatorial Bandits for Budget Allocationcited by 2
  20. 2025Collaborative Learning of On-Device Small Model and Cloud-Based Large Model: Advances and Future Directionscited by 2
  21. 2025Are We Really Measuring Progress? Transferring Insights from Evaluating Recommender Systems to Temporal Link Predictioncited by 2
  22. 2026Delayed Feedback Modeling for Post-Click Gross Merchandise Volume Prediction: Benchmark, Insights and Approachescited by 2
  23. 2026AGPO: Asymmetric Group Policy Optimization for Verifiable Reasoning and Search Ads Relevance at JDcited by 2
  24. 2021A General Framework for Debiasing in CTR Predictioncited by 1
  25. 2022Do not Waste Money on Advertising Spend: Bid Recommendation via Concavity Changescited by 1
  26. 2025Lightweight Auto-bidding based on Traffic Prediction in Live Advertisingcited by 1
  27. 2025Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithmscited by 1
  28. 2025Bid2X: Revealing Dynamics of Bidding Environment in Online Advertising from A Foundation Model Lenscited by 1
  29. 2026PRO-Bid: Pareto-Prioritized Regret Optimization for Constraint-Aware Generative Auto-Biddingcited by 1
  30. 2026PlatformBid: An Auto-Bidding Benchmark from a Unified Advertising Platform's Perspectivecited by 1
  31. 2022A Unified Framework for Campaign Performance Forecasting in Online Display Advertisingcited by 0
  32. 2022An Analysis of Selection Bias Issue for Online Advertisingcited by 0
  33. 2022Functional Optimization Reinforcement Learning for Real-Time Biddingcited by 0
  34. 2022Demystifying Advertising Campaign Bid Recommendation: A Constraint target CPA Goal Optimizationcited by 0
  35. 2023COUPA: An Industrial Recommender System for Online to Offline Service Platformscited by 0
  36. 2024Calibration-then-Calculation: A Variance Reduced Metric Framework in Deep Click-Through Rate Prediction Modelscited by 0
  37. 2024EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systemscited by 0
  38. 2025Bidding-Aware Retrieval for Multi-Stage Consistency in Online Advertisingcited by 0

50 most cited of 57 All 57 (JSON)