Tagged articles

10 articles

Page 1 of 1

Oct 10, 2024 · Artificial Intelligence

Global User Modeling and Explicit Interest Transfer Framework for Meituan Home Page Recommendation

Meituan’s home‑page recommendation system adopts a multi‑stage global user‑modeling pipeline culminating in the EXIT framework, which explicitly transfers cross‑domain interests via interest‑combination labels and a scene‑selector network, thereby mitigating data sparsity and negative transfer and delivering significant offline and online performance gains.

Meituancross-domain recommendationglobal user modeling

0 likes · 34 min read

Global User Modeling and Explicit Interest Transfer Framework for Meituan Home Page Recommendation

DaTaobao Tech

Aug 30, 2022 · Artificial Intelligence

CTNet: Continual Transfer Learning for Cross-Domain Recommendation

CTNet is a continual transfer learning framework that uses a lightweight Adapter to map source‑domain features onto evolving target‑domain recommendation tasks, preserving all model parameters to avoid catastrophic forgetting and delivering substantial gains in click‑through rate, conversion, and overall business performance in Taobao’s cross‑domain e‑commerce scenario.

Adapter ModuleRecommendation Systemscontinual learning

0 likes · 12 min read

CTNet: Continual Transfer Learning for Cross-Domain Recommendation

IEG Growth Platform Technology Team

Aug 25, 2022 · Artificial Intelligence

Adversarial Adaptive Framework for Cold-Start Cross-Domain Recommendation

This article presents an adversarial adaptive framework that aligns source and target domains to address domain shift and severe data imbalance in cold-start cross-domain recommendation, demonstrating significant CTR and CVR performance gains when combined with various state‑of‑the‑art single‑domain models.

CTRCVRadversarial adaptation

0 likes · 9 min read

Adversarial Adaptive Framework for Cold-Start Cross-Domain Recommendation

IEG Growth Platform Technology Team

Aug 10, 2022 · Artificial Intelligence

Two Tencent IEG Papers Accepted at CIKM: Actor‑Critic Reinforcement Learning for Optimal Bidding and Adversarial Adaptation for Cross‑Domain Recommendation

Tencent's IEG Growth Middle Platform team announced that two of its research papers—one presenting an actor‑critic reinforcement learning model for real‑time bidding in online display advertising and the other proposing an adversarial adaptation framework for cross‑domain recommendation—were accepted at the top‑tier CIKM conference, highlighting novel algorithms that achieve state‑of‑the‑art performance and have been deployed to serve billions of daily impressions.

Advertisingadversarial adaptationcross-domain recommendation

0 likes · 4 min read

Two Tencent IEG Papers Accepted at CIKM: Actor‑Critic Reinforcement Learning for Optimal Bidding and Adversarial Adaptation for Cross‑Domain Recommendation

AntTech

May 12, 2022 · Artificial Intelligence

Privacy-Preserving Cross-Domain Recommendation via Differential Privacy and Subspace Embedding

The article reviews a TheWebConf 2022 paper that introduces a two‑stage framework combining differential‑privacy‑based random subspace publishing (using Johnson‑Lindenstrauss and sparse‑aware transforms) with asymmetric deep models to achieve accurate, privacy‑preserving cross‑domain recommendation, and discusses broader differential‑privacy applications.

Privacy-Preserving Machine LearningRecommendation SystemsSubspace Embedding

0 likes · 9 min read

Privacy-Preserving Cross-Domain Recommendation via Differential Privacy and Subspace Embedding

DataFunSummit

Mar 17, 2022 · Artificial Intelligence

Optimizing QQ Music Ranking Model: From User Perception to Multi‑Category Traffic Exploration

This talk presents the evolution of QQ Music's ranking system, detailing background challenges, user‑perception modeling, multi‑objective and causal learning to mitigate the Matthew effect, long‑tail content support, cross‑domain recommendation, and module personalization for diversified traffic, concluding with future research directions.

causal inferencecross-domain recommendationmulti-objective learning

0 likes · 16 min read

Optimizing QQ Music Ranking Model: From User Perception to Multi‑Category Traffic Exploration

DataFunTalk

Feb 14, 2022 · Artificial Intelligence

Optimizing QQ Music Ranking Models: From Pairwise Methods to Multi‑Objective Learning and Causal Inference

This talk details the evolution of QQ Music's ranking system, covering background, user‑perception modeling, pairwise optimization, advanced model architectures, multi‑objective learning with causal inference to mitigate the Matthew effect, cross‑domain recommendation, and module personalization that together boost user engagement and platform traffic.

cross-domain recommendationmulti-objective learningpairwise learning

0 likes · 16 min read

Optimizing QQ Music Ranking Models: From Pairwise Methods to Multi‑Objective Learning and Causal Inference

DataFunTalk

Sep 18, 2020 · Artificial Intelligence

MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction

This article reviews the MiNet model, which leverages cross‑domain information by modeling long‑term, source‑domain short‑term, and target‑domain short‑term user interests with hierarchical attention and an auxiliary task to improve CTR prediction and alleviate cold‑start issues.

Attention MechanismCTR predictionMiNet

0 likes · 12 min read

MiNet: Mixed Interest Network for Cross-Domain Click-Through Rate Prediction

DataFunTalk

Jul 9, 2020 · Artificial Intelligence

Cross‑Domain Recommendation and Heterogeneous Mixed‑Feed Ranking Practices in 58 Community

This article presents a comprehensive overview of 58 Community's recommendation ecosystem, detailing its business background, cross‑domain recommendation concepts, three key challenges, practical solutions such as cross‑domain collaborative filtering with factorization machines, attribute‑mapping and multi‑view DSSM approaches, as well as the engineering of heterogeneous mixed‑feed ranking using scoring alignment, MMR and DPP diversity algorithms, and reports significant online performance gains.

Diversitycross-domain recommendationheterogeneous feed

0 likes · 27 min read

Cross‑Domain Recommendation and Heterogeneous Mixed‑Feed Ranking Practices in 58 Community

Ctrip Technology

Jan 22, 2017 · Artificial Intelligence

Cross-Domain Recommendation: Concepts, Methods, and Novel Approaches

This article reviews the fundamentals of cross-domain recommendation, explains the limitations of single‑domain personalized recommendation, surveys existing collaborative‑filtering, transfer‑learning, and knowledge‑based methods, and introduces two novel tensor‑factorization and bilinear multilevel models that achieve superior performance on real datasets.

collaborative filteringcross-domain recommendationknowledge-based recommendation

0 likes · 17 min read

Cross-Domain Recommendation: Concepts, Methods, and Novel Approaches