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JD Retail Technology

Official platform of JD Retail Technology, delivering insightful R&D news and a deep look into the lives and work of technologists.

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Latest from JD Retail Technology

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JD Retail Technology

Jan 21, 2025 · Artificial Intelligence

Tech Insight: Selected JD Retail Technology Papers in Artificial Intelligence (2024)

Tech Insight highlights ten 2024 JD Retail Technology AI papers presented at top conferences—including CVPR, SIGIR, WWW, AAAI and IJCAI—that advance open‑vocabulary object detection, unified search‑recommendation, pre‑ranking consistency, diversity‑aware re‑ranking, a diversified product‑search dataset, graph‑based query classification, plug‑in CTR models, parallel ad‑ranking, trajectory‑based CTR stability, and task‑aware decoding for large language models.

Artificial IntelligenceCTR predictionComputer Vision

0 likes · 20 min read

JD Retail Technology

Jan 15, 2025 · Industry Insights

JD Retail’s 2024 Tech Innovations: AI, Supply‑Chain Algorithms, and Development

In 2024 JD Retail Technology delivered a series of breakthroughs—including a major JD APP redesign, a data‑driven inventory selection and allocation algorithm that cut stockouts, an AIGC platform for marketing content, a low‑code national‑subsidy system, a large‑scale Apache Hudi data lake, the Taro‑on‑Harmony cross‑platform framework, immersive XR shopping experiences, and a domestic‑chip AI engine—showcasing how advanced AI, cloud, and operations engineering are reshaping e‑commerce.

AIAIGCCross-Platform Development

0 likes · 17 min read

JD Retail’s 2024 Tech Innovations: AI, Supply‑Chain Algorithms, and Development

JD Retail Technology

Jan 10, 2025 · Fundamentals

Clean Code: Principles and Practices for Writing Maintainable Software

The article argues that clean code—characterized by readable naming, minimal comments, short single‑purpose functions, simple control flow, and well‑encapsulated classes—is essential for maintainable software, contrasting it with design patterns and architecture, and demonstrates its benefits through practical refactoring examples and a real‑world case study.

best practicesclean codecode quality

0 likes · 20 min read

Clean Code: Principles and Practices for Writing Maintainable Software

JD Retail Technology

Jan 7, 2025 · Fundamentals

Handling Outliers in Internet A/B Experiments: Concepts, Methods, and Practical Recommendations

The article explains why outliers destabilize internet A/B tests, outlines their causes, compares trimming and winsorizing, presents lightweight detection (e.g., kurtosis) and risk‑control strategies, and offers practical recommendations for bias‑aware removal and variance‑reduction techniques to improve experimental precision.

A/B testingexperiment designoutlier detection

0 likes · 10 min read

Handling Outliers in Internet A/B Experiments: Concepts, Methods, and Practical Recommendations

JD Retail Technology

Jan 3, 2025 · Backend Development

Improving Software Architecture Efficiency: Stability, Performance, and Code Quality

Improving software architecture efficiency requires stable, orthogonal module design, performance‑focused refactoring that avoids tactical shortcuts, and disciplined layered code that balances business and domain responsibilities, while fostering modularization, decoupling, strict quality standards, and a collaborative culture of continuous improvement.

Software Architecturebackend designsystem stability

0 likes · 12 min read

Improving Software Architecture Efficiency: Stability, Performance, and Code Quality

JD Retail Technology

Dec 27, 2024 · Industry Insights

How JD’s Data‑Driven Inventory Selection Boosted Fulfillment Efficiency

This article details JD Retail's award‑winning, data‑driven inventory selection and allocation algorithms, explains their mathematical models, heuristic and end‑to‑end learning solutions, presents experimental results on real‑world data, and quantifies the operational gains achieved after deployment.

e‑commerceinventory optimizationlogistics

0 likes · 21 min read

How JD’s Data‑Driven Inventory Selection Boosted Fulfillment Efficiency

JD Retail Technology

Dec 26, 2024 · Artificial Intelligence

Multi‑Objective Deep Reinforcement Learning Framework for E‑commerce Traffic Allocation (MODRL‑TA)

MODRL‑TA is a multi‑objective deep reinforcement learning framework that unites independent Q‑learning agents, a cross‑entropy‑based decision‑fusion module, and progressive data‑augmentation to overcome cold‑start and multi‑objective trade‑offs in e‑commerce traffic allocation, delivering up to 18% more impressions, 4% higher CTR and 5% higher CVR in live tests.

Deep LearningE-commercemulti-objective

0 likes · 14 min read

Multi‑Objective Deep Reinforcement Learning Framework for E‑commerce Traffic Allocation (MODRL‑TA)

JD Retail Technology

Dec 24, 2024 · Industry Insights

How JD Retail Automates AB Experiment Data Pipelines with Data Weaving

This article analyzes JD Retail's approach to automating AB experiment workflows by introducing a data‑weaving framework that unifies metric definitions, streamlines logical data modeling, and enables scalable, real‑time DAG orchestration across multiple experiment scenarios.

AB testingAutomationData Governance

0 likes · 21 min read

How JD Retail Automates AB Experiment Data Pipelines with Data Weaving

JD Retail Technology

Dec 19, 2024 · Big Data

JD.com Data Governance: Architecture, Key Technologies, and Future Directions

JD.com’s data‑governance framework combines a health‑score‑driven, automated platform that cross‑verifies audit logs, builds full‑link and operator‑level lineage, introduces standard fields, and optimizes resource mixing, task staggering, and cross‑datacenter scheduling, while targeting real‑time AI‑enhanced detection and full automation.

Data GovernanceJD.comResource Optimization

0 likes · 15 min read

JD.com Data Governance: Architecture, Key Technologies, and Future Directions

JD Retail Technology

Dec 17, 2024 · Mobile Development

JDImage: JD’s Self‑Developed HarmonyOS Image Library – Architecture, Implementation, and Performance Optimizations

This article introduces JD’s self‑developed HarmonyOS image library, explaining the background, research on existing solutions, the decision to build a C++‑based cross‑platform library, its modular architecture, performance optimizations, quality assurance mechanisms, and future development plans.

C++HarmonyOSTaRO

0 likes · 13 min read

JDImage: JD’s Self‑Developed HarmonyOS Image Library – Architecture, Implementation, and Performance Optimizations