This article explores how to apply Domain‑Driven Design principles to structure and simplify a complex e‑commerce transaction system, detailing sub‑domain division, model refinement, core order‑service design, and the use of design patterns to achieve a maintainable backend architecture.
This article explains the core concepts and architecture of an e‑commerce product center, covering SPU, SKU, sales and non‑sales attributes, pricing models, inventory control, scheduled on/off‑shelf operations, and optimization techniques for querying product data.
This article presents a comprehensive technical case study of a three‑layer product‑tagging platform that addresses the challenges of fine‑grained operations, ensures real‑time tag updates, guarantees data consistency, and eliminates read bottlenecks through traffic separation, event‑driven processing, deduplication MQ, and multi‑level caching.
This article introduces multi‑task learning, reviews industry category‑prediction methods, and details Zhaozhuan's practical application of MTL to improve e‑commerce search intent understanding through hierarchical category, brand, and model prediction using RoBERTa and contrastive learning.
This article reviews the necessity, benefits, and practical implementations of multi-task learning in e‑commerce search, detailing model selection, architecture extensions such as ESMM and ESM², and future directions for handling user behavior sequences and multi‑objective optimization.
This article examines the characteristics of ZhaiZhai's B2B auction scenario, defines core pricing metrics, presents a step‑by‑step methodology for determining optimal starting prices, reviews early practices and their shortcomings, and details the current modular machine‑learning model architecture that improves transaction rates and reduces price premiums for second‑hand smartphones.
This article explains how ZuanZuan calculates and displays expected delivery times, outlines the system architecture across order, OMS, WMS, and TMS modules, and describes caching and high‑concurrency techniques used to support millions of delivery‑time queries per second.
This article explains the rules of platform coupons, demonstrates a concrete example, and details three generations of algorithms—from a Cartesian‑product approach to Map‑based and array‑index methods—highlighting their implementations, performance trade‑offs, and a comparative benchmark.
The article explains how an e‑commerce risk‑control team leverages OpenAI's CLIP model to generate image and text embeddings and stores them in the Milvus cloud‑native vector database to enable fast, scalable similarity searches for compliance verification and risk detection.
The article presents a comprehensive pricing solution for an e‑commerce platform that combines Bayesian statistical modeling, MCMC sampling, and causal inference (including Dragonnet) to achieve controllable, fine‑grained SKU‑level price estimation and optimization.
This article presents a comprehensive design for Zhuanzhuan's home‑page recommendation pipeline, detailing the system architecture, challenges of traffic efficiency and diversity, and a two‑stage solution that applies Proximal Policy Optimization reinforcement learning in the re‑ranking module and Determinantal Point Process optimization in the coarse‑ranking and traffic‑pool stages, followed by offline simulation, online deployment, and evaluation metrics.
This article describes the background, design goals, core technical solution, versioned implementation process, and performance improvements of a real‑time final‑price calculation module that integrates product price, coupons, and promotions to deliver up‑to‑date pricing for e‑commerce users.
This article describes how a second‑hand e‑commerce company built a fast, modular image‑classification pipeline using small binary classifiers, efficientNet‑b0, and active‑learning‑driven data annotation to detect prohibited items while keeping inference latency under 200 ms and reducing labeling costs dramatically.
This article introduces the fundamentals of recommendation systems, explains Zhuanzhuan's main recommendation scenarios and pipeline, and details three graph embedding methods—DeepWalk, node2vec, and EGES—along with their practical implementations in recall and coarse‑ranking stages.
This article presents a comprehensive case study of how the ZhuangZhuang QA team designed, built, and deployed a payment verification tool to automate and accelerate testing of complex e‑commerce payment scenarios, detailing the business background, requirements analysis, system architecture, core functionalities, generic service invocation, and measurable efficiency gains.
This paper presents an end‑to‑end approach that combines an improved TextCNN with character‑level embeddings and a specific‑shared adversarial transfer‑learning framework to predict the helpfulness of e‑commerce reviews, demonstrating superior performance especially when target‑domain labeled data are scarce.
This article presents the design concepts, transaction flow, core components, and practical experience of building a scalable e‑commerce payment architecture, illustrated with detailed diagrams of transaction sequencing, system modules, and operational considerations for high‑traffic sales events.
The article presents recent statistics showing PHP still dominates web development, powering 77% of the top 10 million sites, most major CMS platforms, and a large share of e‑commerce solutions, while highlighting its use in large‑scale services such as Slack and Wikipedia.
This article explains the role of an order system in traditional e‑commerce enterprises, outlines its main functional modules and architectural design, and discusses future development directions, covering system relationships, core processes, inventory and payment strategies, state‑machine management, and scalability considerations.
This article explains the fundamental concepts, design requirements, and modeling techniques for payment accounts and transaction flows in e‑commerce systems, covering distinctions between payment and login accounts, internal vs. external accounts, and detailed entity, account, and transaction models.