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Test Development Learning Exchange
Test Development Learning Exchange
Nov 30, 2023 · Operations

Comprehensive Test Plan, Strategy, Acceptance, and Deployment Plan for an E‑commerce Double‑11 Event

This document outlines a complete test plan, testing strategies, resource allocation, schedule, risk management, acceptance criteria, and deployment procedures for an e‑commerce Double‑11 promotion, emphasizing functional, interface, and performance testing to ensure system stability and high‑quality user experience.

Deploymentacceptance testinge-commerce
0 likes · 8 min read
Comprehensive Test Plan, Strategy, Acceptance, and Deployment Plan for an E‑commerce Double‑11 Event
Kuaishou Tech
Kuaishou Tech
Sep 26, 2023 · Artificial Intelligence

Cross-Domain Product Representation (COPE): A Large-Scale Dataset and Baseline Model for Rich‑Content E‑Commerce

The paper introduces ROPE, the first large‑scale cross‑domain product recognition dataset covering detail pages, short videos and live streams, and proposes COPE, a dual‑tower multimodal model that learns unified product embeddings using contrastive and classification losses, achieving superior retrieval and few‑shot classification performance across domains.

contrastive learningcross-domaindataset
0 likes · 13 min read
Cross-Domain Product Representation (COPE): A Large-Scale Dataset and Baseline Model for Rich‑Content E‑Commerce
政采云技术
政采云技术
Aug 31, 2021 · Frontend Development

Minimal Inventory in E‑commerce: SKU and Algorithm Implementation

This article explains the theory and practice of handling SKU (Stock Keeping Unit) in e‑commerce platforms, covering product creation, cart selection, Cartesian‑product based SKU generation, adjacency‑matrix and set‑theory approaches, and provides complete JavaScript implementations for front‑end developers.

JavaScriptSKUalgorithm
0 likes · 18 min read
Minimal Inventory in E‑commerce: SKU and Algorithm Implementation
JD Tech
JD Tech
May 22, 2024 · Artificial Intelligence

AI Multi‑Agent System for E‑commerce Merchant Assistance: Design, ReAct Architecture, and Implementation

The article describes JD Retail's AI‑driven multi‑agent platform that models real‑world merchant decision‑making with ReAct‑based LLM agents, detailing the system architecture, agent roles, reasoning loops, workflow examples, training pipelines, monitoring, and future directions for e‑commerce support.

AIAgent ArchitectureDecision Support
0 likes · 21 min read
AI Multi‑Agent System for E‑commerce Merchant Assistance: Design, ReAct Architecture, and Implementation
JD Tech
JD Tech
Jan 18, 2023 · Backend Development

Best Practices for JD Retail Reverse Order Fulfillment: B‑PaaS Architecture, Domain Modeling, and System Upgrade

This article presents JD Retail's reverse order fulfillment platform, detailing the business background, product and system support, comprehensive domain‑modeling methodology, challenges, verification, and the practical B‑PaaS engineering architecture that enables high‑concurrency, multi‑role processing and streamlined maintenance of complex legacy systems.

B-PaaSdomain modelinge-commerce
0 likes · 16 min read
Best Practices for JD Retail Reverse Order Fulfillment: B‑PaaS Architecture, Domain Modeling, and System Upgrade
JD Tech
JD Tech
Jul 21, 2022 · Artificial Intelligence

Improving JD Retail Recommendation Advertising Ranking with Variational Feature Learning, User Interest Network Optimization, and Global Collaborative Modeling

This article presents JD's comprehensive technical solution for boosting recommendation ad ranking by addressing cold‑start, shallow user interest extraction, and insufficient global data through a variational feature learning framework, enhanced user‑interest networks, and full‑domain collaborative modeling, achieving over 1% AUC gain and notable revenue growth.

CTR predictiondeep learninge-commerce
0 likes · 21 min read
Improving JD Retail Recommendation Advertising Ranking with Variational Feature Learning, User Interest Network Optimization, and Global Collaborative Modeling
JD Tech
JD Tech
May 9, 2021 · Artificial Intelligence

Design and Architecture of JD’s User Growth “Machine” for Scalable Intelligent Operations

The article explains how JD’s retail user growth team built a data‑driven, AI‑powered “machine” that automates user insight, operation planning, conflict resolution, external touchpoint, and real‑time strategy engines to achieve precise, large‑scale user acquisition and retention.

AIdata-drivene-commerce
0 likes · 7 min read
Design and Architecture of JD’s User Growth “Machine” for Scalable Intelligent Operations
JD Tech
JD Tech
Apr 30, 2021 · Artificial Intelligence

Smart DMP: A Next‑Generation Intelligent Targeting System for E‑commerce Advertising

This article reviews the limitations of traditional DMP and AI‑driven intelligent targeting in e‑commerce, introduces JD.com's Smart DMP framework that combines merchant intent with high‑relevance modeling, and presents experimental results showing over 15% CTR improvement and widespread merchant adoption.

AISmart DMPadvertising
0 likes · 9 min read
Smart DMP: A Next‑Generation Intelligent Targeting System for E‑commerce Advertising
JD Tech
JD Tech
Jan 3, 2019 · Operations

Comprehensive Monitoring Strategies for E‑commerce Platforms: Black‑Box and White‑Box Approaches

This article systematically explains how to enhance e‑commerce platform availability by implementing both black‑box monitoring to detect functional failures and white‑box monitoring to pinpoint root causes, detailing core order‑process metrics, common issues, mitigation strategies, and illustrative Grafana dashboards.

GrafanaSREblack box
0 likes · 9 min read
Comprehensive Monitoring Strategies for E‑commerce Platforms: Black‑Box and White‑Box Approaches
JD Tech
JD Tech
Apr 28, 2018 · Backend Development

Evolution of JD.com Product Architecture: From Database Replication to Platformized Service Architecture (V1.0‑V3.0)

The article chronicles JD.com's product system evolution—from early SQL Server replication bottlenecks, through Redis‑based read services and full service‑oriented redesign with MySQL clustering, to a decoupled, multi‑layered platform that achieves high availability, scalability, and operational efficiency for billions of SKUs.

BackendMySQLRedis
0 likes · 12 min read
Evolution of JD.com Product Architecture: From Database Replication to Platformized Service Architecture (V1.0‑V3.0)
JD Tech
JD Tech
Feb 1, 2018 · Artificial Intelligence

Telepath: A Vision‑Based Recommender Model Inspired by Human Visual Perception

The Telepath model, presented at AAAI 2018, leverages a biologically‑inspired visual extraction pipeline and dual interest‑understanding networks to improve ranking in large‑scale e‑commerce recommendation and advertising, achieving significant offline and online gains in CTR, GMV, and ROI.

AAAI 2018TelepathVisual Perception
0 likes · 13 min read
Telepath: A Vision‑Based Recommender Model Inspired by Human Visual Perception
JD Tech Talk
JD Tech Talk
Aug 29, 2024 · Artificial Intelligence

Content Compliance Domain Overview and Technical Solutions for Price Governance

The article outlines the role of the content compliance domain in e‑commerce, detailing user‑facing issues, business responsibilities, challenges in detection and mitigation, and technical solutions such as comparable‑price models, large‑scale price prediction, and merchant outreach, while also offering personal growth advice for compliance engineers.

AINLPcomputer vision
0 likes · 9 min read
Content Compliance Domain Overview and Technical Solutions for Price Governance
JD Tech Talk
JD Tech Talk
Apr 25, 2024 · Artificial Intelligence

Evolution of JD Recommendation Advertising Ranking and Auction Mechanisms

This article reviews the evolution of JD’s recommendation advertising ranking mechanism, covering its economic auction origins, challenges of multi‑material valuation, user interest uncertainty, and multi‑item auction fairness, and describes AI‑driven solutions such as deep auction models and reinforcement‑learning‑based ListVCG.

Recommendation Systemsadvertisingauction
0 likes · 19 min read
Evolution of JD Recommendation Advertising Ranking and Auction Mechanisms
JD Tech Talk
JD Tech Talk
Aug 7, 2020 · Information Security

Fraudar: Graph-Based Fraud Detection in Bipartite Transaction Networks

The article explains how e‑commerce fraud such as fake order brushing can be modeled as a bipartite transaction network and tackled with the Fraudar algorithm, which iteratively removes low‑suspicion nodes using a global suspiciousness metric and priority‑tree structures to uncover dense suspicious sub‑graphs.

bipartite graphe-commercefraud detection
0 likes · 14 min read
Fraudar: Graph-Based Fraud Detection in Bipartite Transaction Networks
Ctrip Technology
Ctrip Technology
Nov 10, 2022 · Artificial Intelligence

Improving Search Intent Recognition and Term Weighting with Deep Learning and Model Distillation at Ctrip

This article describes how Ctrip's R&D team applied deep‑learning models, BERT‑based embeddings, knowledge distillation, and term‑weighting techniques to enhance e‑commerce search intent recognition and term importance estimation, achieving high accuracy while meeting sub‑10 ms latency requirements.

BERTModel Distillationdeep learning
0 likes · 12 min read
Improving Search Intent Recognition and Term Weighting with Deep Learning and Model Distillation at Ctrip
Ctrip Technology
Ctrip Technology
Oct 19, 2017 · Artificial Intelligence

Intelligent Human‑Computer Interaction: Technical Practices of Alibaba’s “Ali Xiaomi” Chatbot

This article presents a comprehensive overview of Alibaba’s intelligent chatbot “Ali Xiaomi”, covering industry context, e‑commerce deployment, NLU architecture, intent‑matching layers, deep‑learning‑based intent classification, reinforcement‑learning‑driven recommendation, knowledge‑graph‑enhanced services, and hybrid retrieval‑generation dialogue models, with future outlooks for AI‑driven interaction.

Chatbotdeep learninge-commerce
0 likes · 18 min read
Intelligent Human‑Computer Interaction: Technical Practices of Alibaba’s “Ali Xiaomi” Chatbot
Ctrip Technology
Ctrip Technology
May 6, 2017 · Artificial Intelligence

Product Matching in E‑commerce: Rule‑based, Feature‑Engineering, and Pure Data‑driven Approaches Using Factorization Machines

This article examines e‑commerce product matching, comparing rule‑based methods, feature‑engineering models, and a pure data‑driven Factorization Machine approach, detailing their advantages, challenges, training techniques, and successive optimizations to improve matching accuracy and operational efficiency.

Factorization Machinese-commercefeature engineering
0 likes · 12 min read
Product Matching in E‑commerce: Rule‑based, Feature‑Engineering, and Pure Data‑driven Approaches Using Factorization Machines
Ctrip Technology
Ctrip Technology
Aug 4, 2014 · Product Management

The Evolution and Business Strategies of China’s Online Travel Giant Ctrip

This article analyzes how Ctrip transformed from a simple flight and hotel booking platform into a dominant, integrated travel ecosystem through aggressive pricing wars, strategic investments, mobile expansion, and partnerships, reshaping the Chinese online travel market and its profit structures.

Business StrategyCtripe-commerce
0 likes · 18 min read
The Evolution and Business Strategies of China’s Online Travel Giant Ctrip
58 Tech
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.

e-commercefeature engineeringmachine learning
0 likes · 16 min read
Ranking Strategy Optimization Practice in 58 Commercial Traffic