online training

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.

advertisingconversion rate predictiondistribution shift

0 likes · 30 min read

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

Bilibili Tech

Jun 27, 2023 · Artificial Intelligence

Design and Implementation of a Real-Time Advertising Feature Platform for CTR Prediction at Bilibili

To eliminate data fragmentation, feature inconsistencies, and multi‑language implementation challenges, Bilibili built a unified real‑time advertising feature platform that aligns offline, hourly, and online pipelines via a shared C++ library and JNI, boosting CTR prediction accuracy, cutting training costs, and increasing ad revenue by over 1 %.

CTR predictionDeep LearningFlink

0 likes · 11 min read

Design and Implementation of a Real-Time Advertising Feature Platform for CTR Prediction at Bilibili

Ctrip Technology

May 18, 2023 · Artificial Intelligence

LSTM‑Based Advertising Inventory Forecasting with Embedding and Incremental Training at Ctrip

This article presents Ctrip's end‑to‑end solution for precise ad‑inventory forecasting using an LSTM model combined with entity embedding, covering data preprocessing, K‑means clustering, model architecture, offline‑online incremental training, early‑stop mechanisms, evaluation metrics, and Python service deployment.

LSTMPyTorchadvertising

0 likes · 19 min read

LSTM‑Based Advertising Inventory Forecasting with Embedding and Incremental Training at Ctrip

Xiaohongshu Tech REDtech

Nov 11, 2022 · Artificial Intelligence

Large-Scale Deep Learning Systems and Their Application at Xiaohongshu (RED)

Xiaohongshu’s in‑house LarC platform powers real‑time, multimodal recommendation, life‑search, and generative‑AI commercial content for its 200 million‑user community by processing billions of daily feedback samples, employing conflict‑free parameter servers, diversified sequence modeling, and large‑scale representation learning to deliver personalized, fresh, and diverse user experiences.

AI InfrastructureXiaohongshularge-scale deep learning

0 likes · 13 min read

Large-Scale Deep Learning Systems and Their Application at Xiaohongshu (RED)

DataFunTalk

Jun 17, 2020 · Artificial Intelligence

Deep Recall and Vector Retrieval in 58 Recruitment Recommendation System

This article presents a comprehensive overview of 58's recruitment recommendation system, detailing business challenges, multi‑stage recall strategies, vector‑based deep retrieval, cost‑sensitive loss design, session optimization, online incremental training, extensive offline and online evaluations, and practical lessons for future improvements.

AIDeep LearningVector Retrieval

0 likes · 15 min read

Deep Recall and Vector Retrieval in 58 Recruitment Recommendation System

Tencent Advertising Technology

May 14, 2020 · Artificial Intelligence

2020 Tencent Advertising Algorithm Contest: TI-ONE & Angel Platform Live Training

The 2020 Tencent Advertising Algorithm Contest has launched a series of live training sessions to help participants master the TI-ONE and Angel platforms, featuring expert demonstrations on May 15th.

Angel deep learning engineTI-ONE platformTencent Advertising Algorithm Contest

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2020 Tencent Advertising Algorithm Contest: TI-ONE & Angel Platform Live Training

58 Tech

Nov 29, 2019 · Artificial Intelligence

Ranking Strategy Optimization Practices for Commercial Traffic at 58.com

This article details the end‑to‑end optimization of 58.com’s commercial traffic ranking system, covering data‑flow upgrades, advanced feature engineering, real‑time and multi‑task model improvements, and a multi‑factor ranking mechanism, while sharing practical results and future directions.

Feature EngineeringRankingmachine learning

0 likes · 17 min read

Ranking Strategy Optimization Practices for Commercial Traffic at 58.com

58 Tech

Oct 28, 2019 · Artificial Intelligence

Ranking Strategy Optimization Practice in 58 Commercial Traffic

This article details the comprehensive optimization of 58's commercial traffic ranking system, covering data‑flow upgrades, advanced feature engineering, model enhancements—including online training, multi‑task and relevance models—and a multi‑factor ranking mechanism that together improve monetization efficiency and user experience.

Feature EngineeringRankinge-commerce

0 likes · 16 min read

Ranking Strategy Optimization Practice in 58 Commercial Traffic

Architecture Digest

Sep 9, 2019 · Artificial Intelligence

Overview of Recommendation System Architecture, Algorithms, and Evaluation

This article provides a comprehensive introduction to recommendation systems, covering their definition, overall offline and online architectures, feature engineering, collaborative filtering, latent semantic models, ranking algorithms, and evaluation methods including A/B testing and offline metrics.

A/B testingFeature EngineeringRanking

0 likes · 28 min read

Overview of Recommendation System Architecture, Algorithms, and Evaluation