Reporting modeling results—whether to yourself or others—helps you organize thoughts, reflect on the process, improve communication, and gain fresh perspectives that enhance both your modeling thinking and overall expressive abilities.
This article explains why innovation matters in mathematical modeling, outlines how to achieve it through iterative improvement and solid knowledge foundations, and presents two main directions—vertical extension and horizontal combination—to create more novel and effective models for competitions and research.
The article explains why properly interpreting modeling results is essential, covering reader comprehension, the role of visualizations, guiding key insights, and how explanation fosters reflection and improves the overall significance of the research.
The article examines the challenges advertisers face in a monopolized traffic environment, presents a three‑layer audience insight system, explores graph‑based relationship network methods, and discusses various modeling approaches—including single‑stage, cross‑stage, and multi‑task learning—along with practical considerations for data security and platform integration.
This comprehensive guide explains data‑warehouse construction standards, covering model architecture principles, public development rules, layer‑by‑layer design specifications, and systematic naming conventions for tables, dimensions, and metrics to ensure consistency, scalability, and reliable data governance.
The article explores the true meaning of a technical expert by examining how abstract modeling of real‑world locations, hierarchical administrative divisions, and domain‑specific type systems—illustrated with OpenHAB examples—can transform a programmer’s understanding into expert‑level conceptual and communicative abilities.
This article explains how to select and use appropriate UML diagrams throughout a software project's lifecycle—covering project initiation, requirements analysis, system design, and detailed modeling—illustrated with electronic procurement and hospital admission case studies.
This article explains the principles of object‑oriented modeling, contrasting object and data models, illustrating with a simple account example, discussing composition versus aggregation, and providing Java code snippets for modeling processes such as eating, demonstrating how to design and implement domain objects and services.
This article presents a comprehensive overview of constructing an intelligent risk control tool system, detailing its evolution from manual processes to automated platforms, describing the core "three‑piece" suite (model, decision, and feature platforms) along with supporting data and monitoring platforms, and explaining the functions and interactions of each module such as data ingestion, feature engineering, automated modeling, decision flow, and real‑time monitoring.
Drawing on seven Kaggle and KDD Cup victories, the article outlines a multi‑domain modeling optimization strategy—covering recommendation, time‑series, and AutoML problems—alongside a three‑module AutoML pipeline and a three‑stage workflow that emphasize systematic evaluation, bias‑variance balance, and robust model‑fusion for competition and industry success.
This article explains the concept of feature engineering, illustrates it with a height‑weight classification example, compares kernel‑enhanced models to handcrafted features like BMI, discusses its impact on model performance, and highlights practical tips and domain‑specific considerations.
This article explains the fundamentals of object‑oriented modeling, contrasting data‑model and object‑model designs, illustrating attribute‑method composition, composition versus aggregation, and providing concrete Java and SQL examples such as a simple Account domain, an eating‑process model, and an open‑source e‑commerce reference.
This article explains how mismatched vocabularies between domain experts and developers hinder project progress, and how establishing a shared, model‑driven language can reduce misunderstandings, streamline communication, and improve the reliability of software built with Domain‑Driven Design.
This article explains the fundamentals of object‑oriented modeling, contrasts data‑model and object‑model designs with Java code examples such as a simple Account entity and an eating‑process simulation, and clarifies the difference between composition and aggregation while also touching on application services and a Spring‑Boot e‑commerce project.
This article shares eight months of hands‑on experience with Domain‑Driven Design, explaining why traditional waterfall approaches hinder true business understanding and presenting practical notes, mind‑map visualizations, and step‑by‑step guidance on effective modeling, knowledge digestion, continuous learning, and deep model design.
This article describes how Shuhe Technology leveraged graph neural networks to improve financial risk assessment by preparing massive relational graph data, selecting DGL as the development framework, designing a GraphSage‑GAT model, addressing data sparsity and imbalance, and achieving notable AUC gains over traditional methods.
This article explains ArchiMate's basic views—including composition, support, collaboration, and implementation—detailing their names, viewpoints, and concerns across business, application, and technology layers, and provides examples of information structure and service implementation views with stakeholder and purpose information.
This article describes how a financial company leveraged deep‑learning sequence models to automatically extract features from massive time‑series data, improving risk‑assessment models and operational efficiency through a unified framework that includes data preprocessing, embedding, field and item aggregation, and end‑to‑end deployment.
The article examines the ongoing debate about whether Enterprise Architecture (EA) is a subset of Systems Engineering (SE), discusses major architecture frameworks such as TOGAF, DoDAF, and UPDM, and highlights the role of model‑based engineering and SysML in bridging EA and SE practices.
The article explains how enterprise applications have evolved to web‑centric, three‑layer architectures and describes the purpose and components of network computing hardware diagrams using UML/BPMN EAP Profile and Archimate to map logical application components to physical deployment nodes.
This article explains how environment and location diagrams depict where applications run, defines headquarters, site, server, workstation, and application components, and illustrates these concepts using UML/BPMN EAP profile and Archimate diagrams, while also providing community links for further architectural discussion.
The article explains the purpose and structure of application communication diagrams, describes SOA‑oriented application components, outlines the UML/BPMN EAP profile and Archimate modeling elements, and provides guidance on layering interaction, process, and entity components within logical enterprise architectures.
This article explains object‑oriented fundamentals, contrasts object and data models with Java and SQL examples, discusses application services, and clarifies composition versus aggregation through real‑world analogies and code demonstrations.
This article explains the philosophical basis of object‑oriented thinking, contrasts object models with data models using a simple account example, demonstrates how to design services and sequence diagrams, and clarifies the difference between composition and aggregation in software design.
This article explains how software architects can use UML modeling and design documentation to capture both functional and non‑functional requirements, communicate with stakeholders, and guide developers through requirement analysis, high‑level design, and detailed design phases.
This article explains how software architects can conduct effective software design through modeling, documentation, and UML diagrams to satisfy functional, non‑functional, and cost requirements while ensuring clear communication among developers, testers, and operations teams.
This article presents the mechanisms of Taobao’s detail‑page full‑network distribution, introducing background, scenario description, and a series of algorithmic explorations—including CIDM, DTIN, and Tri‑tower models—that leverage the main product (trigger) to reinforce users’ instant interests, improve recall, coarse‑ranking, and fine‑ranking performance, and achieve notable online metric gains.
The article outlines practical business analysis approaches—including flowcharts, sequence diagrams, prototype sketches, business and data model diagrams—and recommends modeling tools, emphasizing the importance of selecting appropriate visualizations to clarify complex requirements and improve communication between stakeholders and technical teams.
This article explains the theoretical foundations of CTR modeling, why click‑through rates are intrinsically unpredictable at the micro level, the simplifying assumptions that make binary classification feasible, and how evaluation metrics like AUC, contradictory samples, theoretical AUC bounds, and calibration affect model performance.
The article explains why architects need to master mind maps, UML diagrams (class, sequence, activity, state) and architecture diagrams, outlines key principles for each, provides concrete examples and visual illustrations, and shares practical insights on using these diagrams to improve design communication and business alignment.
This article explains the concept, purpose, and essential practices of domain modeling, covering UML relationship types, code examples, model simplification tips, and common pitfalls to help developers create clear, business‑focused class diagrams.
This article explains the fundamentals of Domain-Driven Design, describing how a shared ubiquitous language and a well‑crafted domain model drive software architecture across presentation, application, domain, and infrastructure layers, and it covers key patterns such as aggregates, entities, value objects, repositories, CQRS, Event Sourcing, and DCI.
This article explains the importance of data‑warehouse modeling, outlines a layered architecture (DWD, DWS, DIM, ADS), describes a systematic modeling process, and presents design principles and practical examples to achieve high‑quality, stable, and efficient data models for large‑scale analytics.
This article explains how abstract thinking underpins software engineering, covering definitions, the relationship between language and abstraction, levels of abstraction, layered design, the pitfalls of duplicate code and forced casts, and practical ways to strengthen one’s abstract reasoning skills.
This article explains ArchiMate's basic views—including composition, support, collaboration, and implementation viewpoints—as well as detailed descriptions of the physical and layered views, their stakeholders, concerns, purposes, scope, and example diagrams.
This article explains how software architects can perform effective software design by modeling domain problems and system architecture, outlines the essential UML diagram types, and shows how to use them across requirement analysis, conceptual design, and detailed design to communicate and control development costs.
The article explains how value chain diagrams provide a high‑level perspective of an enterprise’s direction and external interactions, outlines their purpose in linking stakeholders to change activities, and introduces UML/BPMN EAP profiles and Archimate as modeling approaches, while also promoting related community channels.
This article presents a thorough exploration of system design and architecture, covering core concepts, thinking models, analysis techniques, design processes, modeling methods, TOGAF framework, and practical tools to help architects transform complex business requirements into clear, implementable system solutions.
This comprehensive guide walks you through the fundamentals of system design, covering core concepts, analytical thinking, modeling techniques, architecture classification, design tools, and best‑practice principles to help you build robust, scalable software systems.
This article explains how software architects can use UML modeling to capture domain problems and system designs, produce clear design documents, and communicate functional, non‑functional, and cost requirements across all stakeholders throughout the development lifecycle.
This guide explains why architecture diagrams matter, introduces the C4 modeling method, shows how to use C4PlantUML with PlantUML to create context, container, component, and code‑level diagrams, and provides step‑by‑step instructions and example code for practical implementation.
Software design, essential for architects, involves modeling domain problems and the resulting system using UML diagrams such as class, sequence, component, deployment, use‑case, state, and activity charts, applied across requirement, conceptual, and detailed design phases to communicate functional, non‑functional, and cost requirements.
This article outlines a comprehensive approach to building a financial data warehouse, covering background needs, modeling methodologies, a layered architecture (I, C, S, R), data quality monitoring, metadata management, and detailed naming and coding standards to ensure maintainable, high‑quality data pipelines.
This article outlines agile software development design strategies, covering practical agile design activities, underlying design philosophies, and how design fits throughout the entire agile lifecycle, emphasizing iterative modeling, test‑driven development, and the balance between documentation and flexibility.
This article explains how to correctly draw UML class diagrams by describing the six main relationship types—generalization, realization, aggregation, composition, association, and dependency—using clear examples and visual illustrations to help readers understand and apply each relationship in software modeling.
Business capability modeling creates an organization‑wide anchor model that describes distinct capabilities independent of structure, systems, processes, or people, enabling leaders to explore "what we do" and make informed decisions about "how we do it" through collaborative, business‑driven analysis.
This article explains what an architecture diagram is, why it matters, and provides a step‑by‑step methodology—including business and system modeling, abstraction techniques, diagram classification, drawing guidelines, and quality evaluation—to help engineers produce clear, purposeful diagrams that improve communication and collaboration.
This article explains what an architecture diagram is, why it matters, and provides a step‑by‑step methodology—including business and system modeling, abstraction techniques, and quality criteria—to create clear, purposeful diagrams for software projects.
This article explains what an architecture diagram is, why it’s essential for communication and efficiency, and provides practical guidance on defining architecture, modeling processes, abstraction techniques, drawing methods, evaluation criteria, and the role of an architect in software development.
This article explains a Java‑based epidemic simulation that models virus transmission using a normal distribution, demonstrates how parameters like initial infections, transmission rate, hospital capacity, and mobility affect outbreak curves, and shows how adjusting these values can illustrate the impact of public health interventions.
The article explains a Java epidemic simulation that models virus transmission with normal distribution, demonstrates how parameters like movement intention, hospital bed capacity, response time, and incubation period affect outbreak dynamics, and emphasizes staying home as the most effective protection.
This article introduces UML as a standardized visual modeling language, focusing on commonly used class, sequence, and state diagrams, and explains the symbols and relationships—such as dependency, generalization, association, aggregation, and composition—along with practical examples and tool recommendations for effective software design.
This article explains how software architects can use UML‑based modeling to translate functional and non‑functional requirements into clear design documents, covering the essential steps, key concepts, and the seven major UML diagram types across requirement, conceptual, and detailed design phases.
This article explains the origins and challenges of scattered enterprise data, defines the data warehouse concept, details its four core characteristics, compares entity, normalization, and dimensional modeling methods, and illustrates Maoyan’s three‑stage data‑warehouse evolution with practical examples and diagrams.
This article explores the fundamentals of architecture and model thinking, defining their core elements, principles, and roles, and shows how architects and model thinkers use structured frameworks and abstract models to identify contradictions, devise optimal solutions, and guide system improvement across software, organizations, and broader contexts.
This article provides a comprehensive introduction to data warehouses, covering their definition, architectural layers, characteristics, modeling approaches such as Inmon and Kimball, fact and dimension table design, star and snowflake schemas, and best‑practice principles for building scalable, maintainable warehouse solutions in the big‑data ecosystem.
This article introduces recommendation ranking, breaks down its components, explains how to build ranking models, and provides additional insights, while also presenting the author's background and related job opportunities in the e‑commerce recommendation field.
This article shares a step‑by‑step experience report for newcomers to the Tencent Advertising Algorithm competition, covering how to obtain the dataset, understand the problem, build simple rule‑based baselines, choose models and features, and apply practical tricks to achieve scores above 85.
This article explains the six core UML class diagram relationships—generalization, realization, aggregation, composition, association, and dependency—illustrating each with clear diagrams and practical examples, and also recommends popular UML tools for creating these models.
EventStorming is a rapid, lightweight group modeling practice that accelerates shared domain understanding and domain‑driven design by using domain events, commands, bounded contexts, and collaborative workshops, making it applicable to any complex technical or business domain.
This article explains the essential steps of requirement analysis, covering how to decompose and refine business needs, choose appropriate modeling structures, create effective UML diagrams, and avoid common mistakes that can lower requirement quality and increase change risk.
This article explains how to bridge product ideas and development by performing business analysis, creating entity models, designing overall and functional architectures, and considering key concerns such as security, performance, scalability, and maintainability for complex software systems.
This guide walks you through defining clear objectives, identifying key business problems, selecting appropriate frameworks, modeling essential domains, creating a meta‑model, and integrating and analyzing your enterprise architecture, offering practical tips, examples, and best‑practice recommendations to ensure your EA project succeeds.
This article explains the importance of modeling stability, describes how to assess feature and model stability using the Population Stability Index (PSI), provides step‑by‑step calculation methods, and shares practical monitoring practices such as rank mapping and daily SQL‑based checks.
The article explains what a user satisfaction model is, why it matters for product evaluation, and outlines a step‑by‑step methodology—including defining dimensions, collecting questionnaire data, applying statistical techniques, creating a two‑dimensional evaluation matrix, and deriving actionable improvement plans—to quantitatively assess and enhance user experience.
The article outlines twenty‑five practical principles for becoming an excellent software model designer, emphasizing the importance of people over technology, thorough requirement analysis, humility, low coupling, high cohesion, portability, scalability, performance, proper documentation, and continuous learning to build robust, maintainable systems.
Classifying teaching environments helps simplify complex educational contexts, identify key variables, and build models—whether statistical, numerical, or mechanistic—to understand how factors like classroom dynamics, teacher‑student relationships, and colleague interactions influence a novice teacher’s development.
This talk explores the challenges of building and maintaining a CMDB, proposes a goal‑driven, industry‑referenced modeling approach, and outlines practical steps such as tagging, relationship mapping, dynamic attributes, automation, and visualization to create a service‑oriented, scalable configuration management database.
The article explores how mathematical thinking—ideas, techniques, and abstraction—underpins software architecture, shaping problem‑solving, modeling, and design, and argues that a solid mathematical foundation can elevate an architect’s ability to create elegant, scalable systems.
