Tagged articles

8 articles

Page 1 of 1

Aug 27, 2025 · Artificial Intelligence

How Multi-Attribution Learning Boosts Conversion Rate Prediction in Display Ads

This article introduces Multi-Attribution Learning (MAL), a novel paradigm that jointly models multiple attribution labels to overcome the single-attribution bottleneck in conversion rate (CVR) prediction, detailing its architecture, auxiliary tasks, extensive offline and online experiments, and significant business gains.

advertising systemsconversion rate predictionmulti-attribution learning

0 likes · 24 min read

How Multi-Attribution Learning Boosts Conversion Rate Prediction in Display Ads

Zhuanzhuan Tech

Nov 6, 2024 · Artificial Intelligence

Multi-Task Learning for E-commerce Search: Overview, Practices, and Model Design in the Zhuanzhuan Scenario

This article reviews the necessity, benefits, and practical implementations of multi-task learning in e‑commerce search, detailing model selection, architecture extensions such as ESMM and ESM², and future directions for handling user behavior sequences and multi‑objective optimization.

Deep LearningESMMModel architecture

0 likes · 13 min read

Multi-Task Learning for E-commerce Search: Overview, Practices, and Model Design in the Zhuanzhuan Scenario

Alimama Tech

Jun 28, 2023 · Artificial Intelligence

Historical Data Reuse for Precise CVR Prediction during E‑commerce Promotions

Alibaba’s Advertising Ranking team introduced the Historical Data Reuse (HDR) algorithm, which automatically selects similar past promotion days, fine‑tunes the production CVR model with a TransBlock layer and distribution‑correction weighting, delivering up to 10 % AUC gains and double‑digit RPM, CVR, and ROI improvements during the 2022 Double‑11 event and offering a reusable solution for other domains facing abrupt user‑behavior shifts.

conversion rate predictiondistribution shifthistorical data reuse

0 likes · 30 min read

Historical Data Reuse for Precise CVR Prediction during E‑commerce Promotions

Alimama Tech

May 25, 2022 · Artificial Intelligence

AI‑Driven Solutions for External Advertising Effectiveness at Alibaba Mama

Alibaba Mama boosts external-media advertising ROI by deploying AI-driven models—privacy-preserving federated learning, hierarchical representation integration, uncertainty-regularized knowledge distillation, and calibrated DNNs—to overcome missing user-preference data, sparse post-click conversions, sample-selection bias, and probability-calibration challenges.

AIFederated Learningconversion rate prediction

0 likes · 13 min read

AI‑Driven Solutions for External Advertising Effectiveness at Alibaba Mama

JD Retail Technology

May 13, 2020 · Artificial Intelligence

JD's Two Papers Accepted at IJCAI2020 and SIGIR2020: Hierarchical Reinforcement Learning for Multi‑Goal Recommendation and Attention‑Based pCVR Prediction

JD announced that two of its research papers—one on a hierarchical reinforcement‑learning framework for multi‑objective recommendation (MaHRL) and another on an attention‑based model for delayed‑feedback conversion‑rate prediction (pCVR)—were accepted as full papers at the prestigious IJCAI2020 and SIGIR2020 conferences, highlighting the company's strong AI capabilities.

Recommendation Systemsartificial intelligenceconversion rate prediction

0 likes · 6 min read

JD's Two Papers Accepted at IJCAI2020 and SIGIR2020: Hierarchical Reinforcement Learning for Multi‑Goal Recommendation and Attention‑Based pCVR Prediction

Alibaba Cloud Developer

Dec 19, 2018 · Artificial Intelligence

How Cross‑Domain Embedding Boosts New User Recommendations in Alibaba’s Ecosystem

This article explains the design of a Cross‑Domain Embedding (CSDE) method that transfers Alipay user features to Taobao representations, details its learning and adaptive prediction stages, and shows experimental and online results demonstrating significant conversion‑rate improvements for new and inactive users.

Deep LearningGANconversion rate prediction

0 likes · 15 min read

How Cross‑Domain Embedding Boosts New User Recommendations in Alibaba’s Ecosystem

Tencent Advertising Technology

Apr 3, 2018 · Artificial Intelligence

Runner‑up Team’s Experience and Practical Tips from the First Tencent Social Advertising University Algorithm Competition

The article shares the runner‑up team’s reflections on the first Tencent Social Advertising university algorithm contest, covering data splitting, feature engineering, handling large datasets, model selection, ensemble techniques, and final advice to help future participants succeed in conversion‑rate prediction challenges.

Advertisingcompetitionconversion rate prediction

0 likes · 7 min read

Runner‑up Team’s Experience and Practical Tips from the First Tencent Social Advertising University Algorithm Competition

Tencent Advertising Technology

Mar 27, 2018 · Artificial Intelligence

Insights and Lessons from the First Tencent Social Advertising University Algorithm Competition

The article shares a Beijing University team's experience in the first Tencent Social Advertising algorithm contest, detailing their fourth‑place finish, best‑presentation award, and five key strategies—including business‑logic analysis, model innovation, multi‑model fusion, teamwork, and leveraging existing research—to improve conversion‑rate prediction performance.

AdvertisingModel Fusioncompetition

0 likes · 6 min read