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Alimama Tech
Alimama Tech
Dec 1, 2021 · Big Data

Optimization Algorithms for Guaranteed Delivery Advertising in Double‑11 Interactive Campaign

During Double‑11, the team created two specialized allocation algorithms—a brand‑score‑driven primal‑dual method for guaranteed‑downline contracts and a guarantee‑and‑balance flow‑re‑ranking approach for guaranteed‑non‑downline contracts—both using near‑line dual adjustments to meet contract volumes while boosting interaction depth, repeat visits, and browsing time.

Allocation AlgorithmOptimizationbig data
0 likes · 14 min read
Optimization Algorithms for Guaranteed Delivery Advertising in Double‑11 Interactive Campaign
JD Retail Technology
JD Retail Technology
Nov 16, 2021 · Artificial Intelligence

Intelligent Online Selling Point Extraction for E‑Commerce Recommendation (IOSPE) Wins AAAI 2022 Innovation Award

The IOSPE system, which uses BERT‑based scoring, transformer‑pointer generation, and personalized distribution to automatically extract and generate selling points for millions of e‑commerce products, earned the AAAI 2022 Artificial Intelligence Innovation Application Award and has boosted click‑through rates and user dwell time across JD.com platforms.

AIBERTInnovation Award
0 likes · 6 min read
Intelligent Online Selling Point Extraction for E‑Commerce Recommendation (IOSPE) Wins AAAI 2022 Innovation Award
JD Tech
JD Tech
Jul 5, 2024 · Artificial Intelligence

Generative Recommendation Systems for JD Alliance Advertising: Architecture, Implementation, and Experimental Evaluation

This article surveys how large language models reshape recommendation systems, presents a generative RS framework tailored for JD Alliance advertising, details material representation, model input, training and inference pipelines, and reports extensive offline and online experiments demonstrating its effectiveness on sparse user data.

Generative RecommendationLLMe-commerce advertising
0 likes · 27 min read
Generative Recommendation Systems for JD Alliance Advertising: Architecture, Implementation, and Experimental Evaluation
Alimama Tech
Alimama Tech
Feb 9, 2022 · Artificial Intelligence

Alibaba Mama Team Papers Selected for The Web Conference 2023 – Summaries of Five AI Research Works

The Alibaba Mama technical team secured five paper acceptances at The Web Conference 2023, presenting advances in unbiased delayed‑feedback conversion modeling, uncertainty‑regularized knowledge‑distilled CVR debiasing, feature‑aware probability calibration, coordinated two‑stage ad auctions, and scalable decoupled graph neural networks for large‑scale e‑commerce retrieval.

AIAuction DesignCVR
0 likes · 12 min read
Alibaba Mama Team Papers Selected for The Web Conference 2023 – Summaries of Five AI Research Works
DaTaobao Tech
DaTaobao Tech
Apr 13, 2022 · Artificial Intelligence

Machine‑Learning Based Bandwidth Prediction and Adaptive Streaming for Taobao Live: Concerto, OnRL, and Loki

Alibaba’s Taobao Live team replaced rule‑based bandwidth estimators with three machine‑learning solutions—Concerto, OnRL, and Loki—trained on over a million hours of global live‑stream data, achieving up to 13% throughput gain, threefold stall reduction, and up to 44% lower 95th‑percentile stalls, now deployed commercially.

Real-time VideoReinforcement learningadaptive bitrate
0 likes · 14 min read
Machine‑Learning Based Bandwidth Prediction and Adaptive Streaming for Taobao Live: Concerto, OnRL, and Loki
NewBeeNLP
NewBeeNLP
Sep 9, 2024 · Artificial Intelligence

Can Real‑Time Learning at Serving Time Transform Recommendation Re‑ranking?

This article introduces LAST, a novel online learning approach that updates recommendation models instantly at serving time, addressing real‑time learning challenges, re‑ranking complexities, and demonstrating superior offline and online performance in industrial e‑commerce scenarios.

AILASTOnline Learning
0 likes · 12 min read
Can Real‑Time Learning at Serving Time Transform Recommendation Re‑ranking?
Java Backend Technology
Java Backend Technology
Oct 9, 2019 · Information Security

How I Traced a Porn Site Operator Using OSINT Techniques

In this detailed case study, the author discovers a pornographic website, uses WHOIS and email reverse‑lookup to uncover a network of 28 related sites, registers an account, follows payment and contact clues, obtains the operator’s IP, phone and address, and ultimately pressures the owner until the sites disappear.

OSINTcyber investigationtrace
0 likes · 6 min read
How I Traced a Porn Site Operator Using OSINT Techniques
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 20, 2018 · Artificial Intelligence

How Reinforcement Learning Powers Interactive Search in E‑Commerce

This article explains how reinforcement learning can be modeled and deployed to enable intelligent, interactive product search on e‑commerce platforms, detailing problem definition, system architecture, training methodology, online results, and future research directions.

Reinforcement learningdeep learningdialogue system
0 likes · 17 min read
How Reinforcement Learning Powers Interactive Search in E‑Commerce
DataFunTalk
DataFunTalk
Nov 20, 2022 · Artificial Intelligence

Construction of Generalized Causal Forests and Their Application in Online Transaction Markets

On November 26, 2022, at the DataFun Summit 2022 online causal inference conference, PhD candidate Wan Shu from Arizona State University will present a talk titled “Construction of Generalized Causal Forests and Their Application in Online Transaction Markets,” covering treatment effect estimation, model building, performance comparison, and practical use cases.

Generalized Causal ForestOnline Marketdata science
0 likes · 3 min read
Construction of Generalized Causal Forests and Their Application in Online Transaction Markets
Alimama Tech
Alimama Tech
Apr 27, 2022 · Artificial Intelligence

DEFUSE and Bi-DEFUSE: Unbiased Delayed‑Feedback Modeling for CVR Prediction

The paper introduces DEFUSE and its multi‑task extension Bi‑DEFUSE, unbiased delayed‑feedback CVR models that correct label bias via rigorous importance‑sampling and a latent fake‑negative variable, achieving superior offline performance and a 2 % CVR lift in online deployment compared with existing industry baselines.

Bi-DEFUSECVRDEFUSE
0 likes · 25 min read
DEFUSE and Bi-DEFUSE: Unbiased Delayed‑Feedback Modeling for CVR Prediction
Machine Heart
Machine Heart
Apr 2, 2026 · Artificial Intelligence

From Tokens to Revenue: Kuaishou’s GR4AD Pioneers Full‑Stack Generative Recommendation for Ads

GR4AD, Kuaishou’s generative recommendation system, redesigns the entire ad pipeline—from tokenizing multimodal ad material to value‑aware learning, lazy decoding, and dynamic beam search—delivering over 4 % revenue lift, higher eCPM, and sub‑100 ms latency for more than 400 million users.

AdvertisingGenerative RecommendationOnline Learning
0 likes · 17 min read
From Tokens to Revenue: Kuaishou’s GR4AD Pioneers Full‑Stack Generative Recommendation for Ads
Model Perspective
Model Perspective
Nov 6, 2022 · Operations

Master Evaluation & Optimization Models: Concepts, Methods, and Algorithms

This curated guide compiles recent articles on evaluation and optimization models, covering concepts, preprocessing techniques, weighting methods such as TOPSIS and entropy, as well as linear/integer programming, graph theory, shortest‑path, max‑flow, simulated annealing, and genetic algorithms.

Linear Programmingevaluation modelsoperations research
0 likes · 6 min read
Master Evaluation & Optimization Models: Concepts, Methods, and Algorithms
Alimama Tech
Alimama Tech
Jul 29, 2024 · Artificial Intelligence

Generative Auto-bidding via Diffusion Modeling (AIGB)

The paper presents AIGB, a generative auto‑bidding framework that replaces reinforcement‑learning with a conditional diffusion model to generate optimal bidding trajectories, and demonstrates through offline benchmarks and Alibaba’s online A/B tests that it consistently outperforms RL baselines, boosting buy count, GMV, and ROI while maintaining low latency.

Marketing AIReinforcement learningauto-bidding
0 likes · 18 min read
Generative Auto-bidding via Diffusion Modeling (AIGB)
Java Architect Essentials
Java Architect Essentials
Feb 25, 2023 · Information Security

Analysis of Phone and Electricity Recharge Money‑Laundering Schemes in Illicit Apps

The article investigates how certain illicit mobile applications use phone‑bill and electricity‑bill recharge interfaces to launder money, describing the hidden industry chain, the roles of unsuspecting users, the various payment methods involved, and the challenges of tracing the illicit funds.

Information Securityillicit appsmoney laundering
0 likes · 11 min read
Analysis of Phone and Electricity Recharge Money‑Laundering Schemes in Illicit Apps
iQIYI Technical Product Team
iQIYI Technical Product Team
Oct 31, 2019 · Artificial Intelligence

Online Learning for Large‑Scale DNN Ranking Models in iQIYI Feed Recommendation

iQIYI’s feed recommendation system adopts an online‑learning framework that continuously trains a massive Wide‑and‑Deep DNN on billions of streaming samples, handling dynamic user interests, OOV embeddings, delayed labels, and non‑convex optimization, enabling hourly model refreshes and delivering up to 3.8 % higher consumption versus offline baselines.

DNNOnline LearningReal-time Training
0 likes · 17 min read
Online Learning for Large‑Scale DNN Ranking Models in iQIYI Feed Recommendation
Alimama Tech
Alimama Tech
Aug 25, 2021 · Artificial Intelligence

Calibration Techniques for User Response Prediction in Online Advertising

Alibaba Mama’s talk explains how calibrated probability models—evolving from simple Platt scaling to Bayesian isotonic regression and real‑time wave‑adjusted variants—improve click‑through and conversion predictions, enabling more accurate bidding, stable auctions, and fairer ad allocation despite data drift and sparsity.

Calibrationalgorithmonline advertising
0 likes · 20 min read
Calibration Techniques for User Response Prediction in Online Advertising
Meituan Technology Team
Meituan Technology Team
Aug 10, 2023 · Artificial Intelligence

Selected Meituan Technical Papers from KDD 2023: Summaries of Seven Research Works

The article showcases seven Meituan research papers accepted at KDD 2023—spanning feed‑stream, cross‑domain, takeaway, bonus allocation, contour‑based segmentation, living‑needs prediction, and multilingual recommendation—detailing their novel methods, real‑world deployments, and concluding with an invitation for academic collaboration.

Artificial IntelligenceKDD 2023Meituan
0 likes · 17 min read
Selected Meituan Technical Papers from KDD 2023: Summaries of Seven Research Works
DataFunTalk
DataFunTalk
Aug 9, 2021 · Artificial Intelligence

Calibration Techniques for User Behavior Prediction in Online Advertising: Background, Algorithm Evolution, and Engineering Practice

This article introduces the concept of calibration in trustworthy machine learning, explains why accurate probability estimates are crucial for online advertising, reviews related research and evaluation metrics, and details the evolution of calibration algorithms such as Smoothed Isotonic Regression, Bayes‑SIR, real‑time optimizations, and post‑click conversion models, concluding with engineering deployment and future directions.

Algorithm OptimizationCalibrationclick-through rate
0 likes · 18 min read
Calibration Techniques for User Behavior Prediction in Online Advertising: Background, Algorithm Evolution, and Engineering Practice