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NetEase LeiHuo UX Big Data Technology

The NetEase LeiHuo UX Data Team creates practical data‑modeling solutions for gaming, offering comprehensive analysis and insights to enhance user experience and enable precise marketing for development and operations. This account shares industry trends and cutting‑edge data knowledge with students and data professionals, aiming to advance the ecosystem together with enthusiasts.

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Latest from NetEase LeiHuo UX Big Data Technology

37 recent articles

NetEase LeiHuo UX Big Data Technology

Jun 21, 2024 · Game Development

Data-Driven Causal Analysis Methods for Game Updates When A/B Testing Is Not Feasible

When large‑scale A/B testing is impractical for high‑traffic, socially intensive games, developers can rely on methods such as Difference‑in‑Differences, hypothesis proportion analysis, and differential‑ratio comparison to infer the causal impact of content updates on key performance metrics.

Data AnalysisGame AnalyticsHypothesis Proportion

0 likes · 7 min read

Data-Driven Causal Analysis Methods for Game Updates When A/B Testing Is Not Feasible

NetEase LeiHuo UX Big Data Technology

Mar 5, 2024 · Frontend Development

Improving React Application Rendering Performance: Monitoring Tools and Optimization Techniques

This article explains why rendering performance is crucial for React applications and provides a comprehensive guide on monitoring tools such as Profiler and Developer Tools, followed by practical optimization methods including component update control, data handling hooks, code‑splitting, lazy loading, and concurrent mode.

PerformanceReactRendering

0 likes · 7 min read

Improving React Application Rendering Performance: Monitoring Tools and Optimization Techniques

NetEase LeiHuo UX Big Data Technology

Jan 17, 2024 · Backend Development

Understanding DPDK: Background, Architecture, High‑Performance Techniques, and Real‑World Applications

This article explains the origins of DPDK, describes its modular architecture and performance‑enhancing mechanisms such as UIO, hugepages, and CPU affinity, and reviews popular user‑space networking frameworks like F‑Stack and Seastar that leverage DPDK for high‑throughput cloud services.

DPDKF-StackHigh‑Performance Networking

0 likes · 9 min read

Understanding DPDK: Background, Architecture, High‑Performance Techniques, and Real‑World Applications

NetEase LeiHuo UX Big Data Technology

Jan 9, 2024 · Artificial Intelligence

Accelerating Recommendation System Development with MindsDB

The article explains how the data team adopted the open‑source machine‑learning platform MindsDB to simplify data integration, enable SQL‑based model training and inference, manage model versions, and dramatically shorten recommendation system development cycles, achieving up to 30% efficiency gains.

Data IntegrationMindsDBModel Management

0 likes · 5 min read

Accelerating Recommendation System Development with MindsDB

NetEase LeiHuo UX Big Data Technology

Aug 23, 2023 · Artificial Intelligence

Model-Based Collaborative Filtering Algorithms for Game Item Recommendation

This article explains the principles of collaborative filtering, outlines its three main types—user‑based, item‑based, and model‑based—and focuses on model‑based approaches such as matrix factorization, clustering, and deep‑learning techniques for recommending personalized game items to improve player experience and monetization.

Model-BasedRecommendation Systemsartificial intelligence

0 likes · 7 min read

Model-Based Collaborative Filtering Algorithms for Game Item Recommendation

NetEase LeiHuo UX Big Data Technology

Aug 15, 2023 · Frontend Development

Understanding React Router v6: Route Order, Nesting, Loaders, and Permissions

This article compares React Router v5 and v6, highlighting v6’s new Routes component, simplified nesting, loader functions for pre‑render data fetching, error handling, permission checks, and integration with defer and Suspense, providing code examples and practical migration insights for frontend developers.

React RouterRoutingloader

0 likes · 18 min read

Understanding React Router v6: Route Order, Nesting, Loaders, and Permissions

NetEase LeiHuo UX Big Data Technology

Apr 3, 2023 · Artificial Intelligence

Understanding Causal Inference and How to Use the DoWhy Library

This article explains why causal inference is essential for moving beyond correlation to decision‑making, introduces the structural causal model framework, and provides a step‑by‑step guide to using Microsoft’s DoWhy Python library for modeling, identification, estimation, and counterfactual analysis.

DoWhyPythonartificial intelligence

0 likes · 7 min read

Understanding Causal Inference and How to Use the DoWhy Library

NetEase LeiHuo UX Big Data Technology

Jan 4, 2023 · Game Development

Handling Time Zones in Game Development: Consistency, Storage, and Presentation

This article explains why time‑zone consistency is crucial in games, illustrates common pitfalls with UTC and local times—including daylight‑saving effects—and provides best‑practice guidelines for storing timestamps in UTC, preserving zone information, and displaying user‑friendly times to avoid data errors and user confusion.

UTCdaylight savingtime zones

0 likes · 8 min read

Handling Time Zones in Game Development: Consistency, Storage, and Presentation

NetEase LeiHuo UX Big Data Technology

Nov 22, 2022 · Artificial Intelligence

Sample Weighting in Machine Learning: From YouTube Playback Duration to Game Recommendation Optimization

This article explains why and how sample weighting is used in machine learning, illustrates YouTube's conversion of video watch time into sample weights to align with its commercial goals, and describes practical weighted‑logistic‑regression techniques applied to improve game recommendation systems.

AIRecommendation SystemsYouTube

0 likes · 8 min read

Sample Weighting in Machine Learning: From YouTube Playback Duration to Game Recommendation Optimization

NetEase LeiHuo UX Big Data Technology

Oct 17, 2022 · Big Data

Understanding Data Skew and Its Mitigation Strategies in Distributed Computing

The article explains what data skew is in distributed computing, analyzes its logical and data‑level causes, and presents preventive and remedial techniques such as data partitioning, logical replacement, two‑stage aggregation, increasing parallelism, and data cleaning to improve processing efficiency.

Data SkewPerformance OptimizationSpark

0 likes · 8 min read

Understanding Data Skew and Its Mitigation Strategies in Distributed Computing