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232 articles · Page 3 of 3
Tencent Advertising Technology
Tencent Advertising Technology
May 8, 2019 · Artificial Intelligence

Experience Sharing of the 2019 Tencent Advertising Algorithm Competition – Week 1 Champion’s Insights

The week‑1 champion of the 2019 Tencent Advertising Algorithm Competition shares practical experience on data cleaning, feature engineering, model selection (including LightGBM and deep learning), validation strategies, and tips for handling massive ad exposure logs to achieve high SMAPE and monotonicity scores.

AdvertisingAlgorithm CompetitionLightGBM
0 likes · 6 min read
Experience Sharing of the 2019 Tencent Advertising Algorithm Competition – Week 1 Champion’s Insights
Hulu Beijing
Hulu Beijing
Apr 11, 2019 · Artificial Intelligence

Optimizing Real-Time Ad Bidding with Reinforcement Learning: A Deep Dive

This article explains how real‑time bidding works in computational advertising, defines the budget‑constrained bidding problem, models it with reinforcement learning, and presents a deep‑network implementation together with visual analysis and key references.

Advertisingbudget optimizationdeep learning
0 likes · 6 min read
Optimizing Real-Time Ad Bidding with Reinforcement Learning: A Deep Dive
HomeTech
HomeTech
Jan 29, 2019 · Backend Development

Design and Implementation of the PCMA Advertising Validation Automation Platform

This article describes the business background, requirements, multi‑layer architecture, implementation details, usage workflow, encountered issues, and future plans of PCMA, a platform that automates the validation of advertising placements across PC, mobile web, and app environments.

AdvertisingPlatformbackend
0 likes · 7 min read
Design and Implementation of the PCMA Advertising Validation Automation Platform
DataFunTalk
DataFunTalk
Jan 28, 2019 · Artificial Intelligence

Deep Interest Evolution Network (DIEN): Modeling User Interest Evolution for Click‑Through Rate Prediction

This article introduces the Deep Interest Evolution Network (DIEN), an advanced deep learning model that extracts and evolves user interests over time to improve click‑through rate prediction for display advertising, detailing its background, architecture, auxiliary loss, attention‑augmented GRU, and both offline and online performance gains.

AdvertisingDIENRecommendation Systems
0 likes · 15 min read
Deep Interest Evolution Network (DIEN): Modeling User Interest Evolution for Click‑Through Rate Prediction
58 Tech
58 Tech
Dec 21, 2018 · Artificial Intelligence

Insights from 58 Group Technical Salon: Recommendation Systems, Image Creative Optimization, and Deep Learning Online Prediction Service

The 58 Group technical salon presented detailed engineering practices on video recommendation system architecture, image creative optimization for search ads, a programmatic creative platform, and a Kubernetes‑based deep learning online prediction service, highlighting micro‑service design, distributed indexing, and real‑time model deployment.

AIAdvertisingarchitecture
0 likes · 8 min read
Insights from 58 Group Technical Salon: Recommendation Systems, Image Creative Optimization, and Deep Learning Online Prediction Service
Alibaba Cloud Developer
Alibaba Cloud Developer
Nov 28, 2018 · Artificial Intelligence

How Alibaba’s X-Deep Learning Framework Revolutionizes High‑Dimensional Sparse Data Processing

Alibaba's X-Deep Learning (XDL) framework, the first open‑source deep learning system designed for high‑dimensional sparse data, powers advertising, recommendation, and search workloads, delivering industrial‑scale performance and boosting revenue while offering an open, easy‑to‑use solution for the broader AI community.

AdvertisingXDLdeep learning
0 likes · 6 min read
How Alibaba’s X-Deep Learning Framework Revolutionizes High‑Dimensional Sparse Data Processing
iQIYI Technical Product Team
iQIYI Technical Product Team
Nov 2, 2018 · Artificial Intelligence

Intelligent Advertising Algorithm System at iQIYI: Architecture, Smart Bidding, Inventory Allocation, and TrueView

iQIYI’s intelligent advertising algorithm system unifies smart bidding, inventory allocation, and TrueView modules—leveraging KNN, XGBoost, ARIMA, LSTM, and Wide&Deep models—to dynamically price ads, forecast and allocate inventory, and predict user‑viewed video ads, thereby enhancing advertiser efficiency, platform revenue, and user experience.

AIAdvertisingTrueView
0 likes · 6 min read
Intelligent Advertising Algorithm System at iQIYI: Architecture, Smart Bidding, Inventory Allocation, and TrueView
iQIYI Technical Product Team
iQIYI Technical Product Team
Aug 24, 2018 · Artificial Intelligence

Lookalike Audience Extension Algorithms in iQIYI Advertising: Tag‑Based and Machine‑Learning Approaches

iQIYI uses two Lookalike audience extension methods—tag‑based using weighted tag scoring and supervised machine‑learning using logistic regression with engineered DMP and ad behavior features—both improving ad performance, e.g., 20% higher Trueview completion and up to 60% lower conversion cost.

AdvertisingAudience ExtensionLookalike
0 likes · 10 min read
Lookalike Audience Extension Algorithms in iQIYI Advertising: Tag‑Based and Machine‑Learning Approaches
JD Retail Technology
JD Retail Technology
Jun 13, 2018 · Artificial Intelligence

IJCAI 2018 International Advertising Algorithm Competition Champion Uses Transfer Learning and LightGBM for Ad Conversion Prediction

The IJCAI 2018 International Advertising Algorithm Competition was won by JD.com algorithm engineer Hua Zhixiang, who employed a two‑stage LightGBM model with transfer learning and carefully designed statistical, temporal, ranking, and representation features to achieve top conversion‑rate predictions on massive e‑commerce advertising data.

AdvertisingAlgorithm CompetitionIJCAI
0 likes · 5 min read
IJCAI 2018 International Advertising Algorithm Competition Champion Uses Transfer Learning and LightGBM for Ad Conversion Prediction
Tencent Advertising Technology
Tencent Advertising Technology
May 28, 2018 · Artificial Intelligence

Winning Approach of the Tencent Advertising Algorithm Competition: Feature Engineering, Model Selection, and Future Work

The team from Jilin University, Harbin Institute of Technology, and Beijing University of Posts and Telecommunications shares their winning strategy for the Tencent Advertising Algorithm Competition, detailing their feature engineering, model selection, and future work to handle large‑scale data challenges.

AdvertisingCompetitionModel Selection
0 likes · 4 min read
Winning Approach of the Tencent Advertising Algorithm Competition: Feature Engineering, Model Selection, and Future Work
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 16, 2018 · Artificial Intelligence

How Alibaba’s Deep Learning Transformed CTR Prediction: From MLR to Multi‑Interest Networks

This article recounts Alibaba‑Mama researcher Jing Shi’s presentation on the evolution of deep learning for click‑through‑rate (CTR) estimation, covering the shift from handcrafted features and linear models to piecewise linear MLR, end‑to‑end neural networks, multi‑interest user modeling, and large‑scale distributed training challenges.

AdvertisingCTR predictionLarge‑Scale Training
0 likes · 16 min read
How Alibaba’s Deep Learning Transformed CTR Prediction: From MLR to Multi‑Interest Networks
Tencent Advertising Technology
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
转转QA
转转QA
Apr 3, 2018 · Backend Development

Overview of the Commercial Testing Platform and Its Future Roadmap

The article introduces a commercial testing platform used by an advertising team, detailing its architecture, core components, monitoring and scheduling mechanisms, current advantages and shortcomings, and outlines planned enhancements to improve data construction, result recording, and anti‑fraud coverage.

AdvertisingAutomationMonitoring
0 likes · 8 min read
Overview of the Commercial Testing Platform and Its Future Roadmap
Tencent Advertising Technology
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.

AdvertisingCompetitionconversion rate prediction
0 likes · 6 min read
Insights and Lessons from the First Tencent Social Advertising University Algorithm Competition
360 Zhihui Cloud Developer
360 Zhihui Cloud Developer
Dec 28, 2017 · Backend Development

How 360’s SSP Engine Delivers Billions of Ads with Microservices and High‑Performance Architecture

This article explains the architecture and key technologies of 360’s SSP advertising engine—including flexible micro‑service layers, DAG‑based topology, rule and template management, and high‑performance Go‑based HTTP frameworks—that enable billion‑scale ad delivery with low latency and high concurrency.

AdvertisingBackend ArchitectureGo
0 likes · 16 min read
How 360’s SSP Engine Delivers Billions of Ads with Microservices and High‑Performance Architecture
58UXD
58UXD
Dec 22, 2017 · Product Management

What Business Models Power Popular Games? Lessons from PUBG for Product Designers

This article explores how the wildly successful game PUBG illustrates various internet business models, explains the components of a business model, examines common ecosystem and freemium models, details advertising and revenue streams of 58.com, and shares design strategies for large‑scale B‑end products.

AdvertisingB2B designbusiness model
0 likes · 7 min read
What Business Models Power Popular Games? Lessons from PUBG for Product Designers
Meituan Technology Team
Meituan Technology Team
Dec 1, 2017 · Artificial Intelligence

Meituan-Dianping DSP Advertising Coarse Ranking Mechanisms and Scenario‑Based Targeting

Meituan‑Dianping’s DSP coarse‑ranking filters large ad candidate sets by scoring ads with user‑profile, weather, and keyword scenario models—using frequent‑itemset mining, AdaBoost, and TF/IDF—then aggregates these scores via a linear‑regression model to select high‑relevance ads for fine‑ranking, boosting click‑through and conversion rates.

Advertisingcoarse rankingkeyword targeting
0 likes · 23 min read
Meituan-Dianping DSP Advertising Coarse Ranking Mechanisms and Scenario‑Based Targeting
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 15, 2017 · Artificial Intelligence

How Alibaba’s Mixed Logistic Regression Revolutionizes CTR Prediction

This article explains the technical background of click‑through‑rate (CTR) prediction, critiques traditional linear models, introduces Alibaba’s Mixed Logistic Regression (MLR) algorithm with its advanced features and large‑scale distributed implementation, and reviews its successful deployment and remaining challenges in advertising systems.

AdvertisingCTR predictionMLR
0 likes · 13 min read
How Alibaba’s Mixed Logistic Regression Revolutionizes CTR Prediction
Tencent Advertising Technology
Tencent Advertising Technology
May 27, 2017 · Artificial Intelligence

Weekly Champion Interview: Groot Team Shares Competition Strategies

The article introduces the Tencent Social Ads university algorithm contest weekly champion team Groot, details their background, and outlines their practical machine‑learning approach—including training set construction, XGBoost model selection, and feature engineering—while encouraging broader participation in such competitions.

AIAdvertisingCompetition
0 likes · 4 min read
Weekly Champion Interview: Groot Team Shares Competition Strategies
Meituan Technology Team
Meituan Technology Team
May 5, 2017 · Artificial Intelligence

Meituan DSP Strategy: Real‑time Bidding, Recall, CTR and Value Prediction

Meituan’s demand‑side platform combines real‑time bidding with a two‑service architecture—RecServer for multi‑scenario ad recall and PredictorServer for CTR and conversion‑value prediction—leveraging behavior, location, collaborative‑filtering and matrix‑factorization features, logistic‑regression and GBDT models, and continuous A/B and metric monitoring to optimize ROI.

AdvertisingDSPmachine learning
0 likes · 20 min read
Meituan DSP Strategy: Real‑time Bidding, Recall, CTR and Value Prediction
High Availability Architecture
High Availability Architecture
Apr 13, 2017 · Backend Development

Designing a High‑Availability Advertising System: Architecture, Scaling, and Real‑Time Monitoring at Weibo

This article examines the architecture of Weibo's high‑availability advertising platform, covering match service design with OpenResty, index sharding, business logic optimization, dynamic auto‑scaling, and a real‑time monitoring pipeline to ensure stable, high‑performance ad delivery at massive scale.

AdvertisingBackend ArchitectureHigh Availability
0 likes · 11 min read
Designing a High‑Availability Advertising System: Architecture, Scaling, and Real‑Time Monitoring at Weibo
Architecture Digest
Architecture Digest
Jan 28, 2017 · Backend Development

Design and Implementation of a High‑Performance, High‑Availability OTT Advertising System

This article presents the research and implementation of a high‑performance, highly available OTT advertising platform, detailing its system architecture, key technologies such as multi‑domain routing, containerized modules, two‑level caching, double‑layer Boolean retrieval, dynamic CDN scheduling, graceful degradation, and comprehensive disaster‑recovery strategies.

AdvertisingOTT
0 likes · 27 min read
Design and Implementation of a High‑Performance, High‑Availability OTT Advertising System
Hulu Beijing
Hulu Beijing
Dec 22, 2016 · Big Data

How Hulu Uses Big Data and Algorithms to Supercharge Its Ad System

This article explains how Hulu’s advertising platform leverages big‑data pipelines, time‑series forecasting, bipartite‑graph optimization, linear‑model targeting, and real‑time allocation to improve sales, delivery, reporting, and planning of guaranteed‑delivery brand ads.

AdvertisingAlgorithminventory optimization
0 likes · 11 min read
How Hulu Uses Big Data and Algorithms to Supercharge Its Ad System
Ctrip Technology
Ctrip Technology
Aug 12, 2016 · Artificial Intelligence

Deep Learning Meetup Recap: Applications in Travel, Advertising, NLP, Computer Vision, and Knowledge Graphs

Last month Ctrip Technology Center hosted a deep‑learning meetup featuring academic and industry experts from UCL, Fudan, Southeast University, Nanjing University, Huawei, Sogou and others, who presented real‑world applications of deep learning in travel, advertising, natural language processing, computer vision, and knowledge graphs.

AI ApplicationsAdvertisingKnowledge Graph
0 likes · 6 min read
Deep Learning Meetup Recap: Applications in Travel, Advertising, NLP, Computer Vision, and Knowledge Graphs
Ctrip Technology
Ctrip Technology
Jul 29, 2016 · Artificial Intelligence

Deep Learning for Multi‑field Categorical Data: Click‑Through Rate Prediction and Model Comparisons

This article presents a deep‑learning‑based approach to multi‑field categorical data, explains FM and FNN embeddings, compares several click‑through‑rate prediction models on Criteo and iPinYou datasets, and demonstrates that factorisation‑machine‑supported neural networks significantly outperform logistic regression and other baselines.

Advertisingclick-through rate predictionfactorisation machine
0 likes · 15 min read
Deep Learning for Multi‑field Categorical Data: Click‑Through Rate Prediction and Model Comparisons
Meituan Technology Team
Meituan Technology Team
Mar 18, 2016 · Artificial Intelligence

Why FM and FFM Still Dominate Large‑Scale Sparse CTR Prediction

This article explains the principles of Factorization Machines (FM) and Field‑aware Factorization Machines (FFM), their implementation details, and how Meituan‑Dianping applied FFM in a DSP platform to achieve superior CTR and CVR estimation for sparse, high‑dimensional advertising data.

AdvertisingCTR predictionDSP
0 likes · 4 min read
Why FM and FFM Still Dominate Large‑Scale Sparse CTR Prediction
dbaplus Community
dbaplus Community
Dec 4, 2015 · Big Data

Big Data Insights from the 2015 Internet+ Summit: Advertising, Finance & Security

The article compiles detailed notes from the 2015 Internet+ Big Data Summit, highlighting how data monetization reshapes advertising, drives financial analytics, improves operational efficiency, and strengthens security, while presenting real‑world case studies, models, and practical recommendations from industry experts.

AdvertisingData GovernanceData Monetization
0 likes · 17 min read
Big Data Insights from the 2015 Internet+ Summit: Advertising, Finance & Security