BestHub
Sign in
Tagged articles
7 articles
Page 1 of 1
DeWu Technology
DeWu Technology
Dec 20, 2023 · Artificial Intelligence

Coarse Ranking in Recommenders: Key Strategies, Metrics & Optimizations

This article systematically reviews the coarse‑ranking stage of recommendation systems, comparing it with recall and fine‑ranking, defining evaluation metrics, detailing sample design, presenting two technical routes, and exploring optimization directions such as dual‑tower models, knowledge distillation, lightweight fully‑connected layers, multi‑objective and multi‑scenario modeling, followed by practical case studies and results.

Evaluation Metricscoarse rankingdual-tower
0 likes · 22 min read
Coarse Ranking in Recommenders: Key Strategies, Metrics & Optimizations
Alimama Tech
Alimama Tech
Nov 15, 2023 · Artificial Intelligence

Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking (HC²)

The HC² framework enhances multi‑scenario ad ranking by jointly applying a generalized contrastive loss on shared representations and an individual contrastive loss on scenario‑specific layers, using label‑aware positive sampling, diffusion‑noise negative sampling, and inverse‑similarity weighting, achieving consistent offline gains and up to 2.5% CVR and 3.7% GMV improvements in Alibaba’s live system.

Recommendation Systemsad rankingcontrastive learning
0 likes · 16 min read
Hybrid Contrastive Constraints for Multi-Scenario Ad Ranking (HC²)
AntTech
AntTech
Oct 30, 2023 · Artificial Intelligence

AntM2C: A Large-Scale Multi‑Scenario Multi‑Modal CTR Prediction Dataset from Alipay

AntM2C is a publicly released, billion‑sample click‑through‑rate (CTR) dataset covering five distinct Alipay business scenarios, providing both ID and rich multi‑modal (text and image) features to enable comprehensive evaluation of multi‑scenario, cold‑start, and multi‑modal CTR models at industrial scale.

CTRlarge scalemulti-modal
0 likes · 14 min read
AntM2C: A Large-Scale Multi‑Scenario Multi‑Modal CTR Prediction Dataset from Alipay
DaTaobao Tech
DaTaobao Tech
Apr 28, 2023 · Artificial Intelligence

Multi-Scenario Recommendation Model

The paper introduces SASS, a scenario-adaptive self-supervised recommendation model that uses contrastive pre-training and multi-layer gating to expand global samples and transfer scene-aware parameters, enabling a single model to deliver personalized recommendations across diverse Taobao ‘SuoSuo’ scenarios while mitigating data sparsity and cross-domain challenges.

AIDeep LearningRecommendation Systems
0 likes · 23 min read
Multi-Scenario Recommendation Model
DaTaobao Tech
DaTaobao Tech
Jan 9, 2023 · Artificial Intelligence

Adaptive and Self-Supervised Multi-Scenario Modeling for Taobao Personalized Recommendation

On January 9 from 19:00 to 20:00, algorithm engineer Zhang Yuanliang will present Taobao’s scenario-adaptive, self-supervised multi-scenario recommendation model, detailing its architecture, experimental results, and practical deployment for improving personalized item recall across diverse user contexts.

algorithmmulti-scenariopersonalization
0 likes · 1 min read
Adaptive and Self-Supervised Multi-Scenario Modeling for Taobao Personalized Recommendation
JD Retail Technology
JD Retail Technology
Dec 11, 2017 · Big Data

Data Model Component Management Platform: Functions and Practices

The presentation introduces JD's Data Model Component Management Platform, detailing its four core functions—risk control, effect evaluation, model fusion, and multi‑scenario application—while explaining how these capabilities improve model reliability, commercial value, and operational efficiency across numerous business products.

JDModel Fusiondata-model
0 likes · 8 min read
Data Model Component Management Platform: Functions and Practices