algorithm optimization

NetEase Cloud Music Tech Team

Apr 23, 2024 · Mobile Development

Cloud Music User Push Notification Optimization: Practices and Insights

Cloud Music revamped its push‑notification system by separating business and channel layers, integrating a unified delivery platform, tailoring messages to Android manufacturers, adding new push channels, refining frequency and copy controls, and using AI‑generated creatives, which together doubled click‑through rates and nearly doubled total click users within two months.

A/B testingAIGC Content GenerationCloud Music

0 likes · 23 min read

Cloud Music User Push Notification Optimization: Practices and Insights

HomeTech

Nov 8, 2023 · Artificial Intelligence

Cold Start Optimization for New Content in Autohome Recommendation System

The article details how Autohome tackled the cold‑start problem for newly generated content by redesigning the recommendation pipeline, introducing multi‑path recall, refining ranking and re‑ranking formulas, and applying strategic controls, resulting in a rise of cold‑start success rate from 27% to over 99% and a CTR increase from 5% to 14%.

AICold StartRanking

0 likes · 10 min read

Cold Start Optimization for New Content in Autohome Recommendation System

Tencent Architect

Aug 21, 2023 · Fundamentals

How Tencent Cloud’s V265/TXAV1 Revolutionizes 8K Live Streaming

This article details Tencent Cloud's V265/TXAV1 live streaming solution, covering its high‑efficiency 8K and low‑latency capabilities, performance gains over X265, MV‑HEVC 3D compression, extensive engineering and algorithmic optimizations, and the resulting speed‑up and quality improvements for ultra‑high‑definition live broadcasts.

8KLive StreamingLow Latency

0 likes · 18 min read

How Tencent Cloud’s V265/TXAV1 Revolutionizes 8K Live Streaming

Bilibili Tech

Aug 2, 2023 · Fundamentals

BILIVVC Secures Third Place in 2022 MSU Encoder Competition (1080p 1fps & 5fps)

Bilibili’s self‑developed VVC encoder, BILIVVC, earned third place in both the 1080p 1 fps and 5 fps tracks of the 2022 MSU Encoder Competition by leveraging extensive VVC‑tool optimizations, fast‑algorithm cooperation, adaptive pre‑analysis and efficient implementation that deliver high quality YUV‑SSIM performance despite its small‑team, one‑year development.

BILIVVCMSU Encoder CompetitionVVC

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BILIVVC Secures Third Place in 2022 MSU Encoder Competition (1080p 1fps & 5fps)

DaTaobao Tech

Jul 21, 2023 · Artificial Intelligence

A Year of Video‑Quality Engineering and Growth at Taobao Live

Over the past year, Taobao Live’s video‑quality team, led by former algorithm researcher Xiaocen, built an automated attribution system, real‑time low‑quality detection, and close streamer support, turning pure research into product‑focused engineering that boosted stream quality, trust, and business impact through cross‑domain collaboration.

Live Streamingalgorithm optimizationengineering growth

0 likes · 9 min read

A Year of Video‑Quality Engineering and Growth at Taobao Live

Python Programming Learning Circle

May 8, 2023 · Fundamentals

Comparing while and for Loop Performance in Python and Faster Alternatives

This article analyzes the execution speed differences between Python's while and for loops, demonstrates benchmark results using timeit, explains the underlying reasons for the performance gap, and shows how built‑in functions and mathematical formulas can achieve dramatically faster computations.

algorithm optimizationloop performancesum function

0 likes · 7 min read

Comparing while and for Loop Performance in Python and Faster Alternatives

Architect's Tech Stack

Dec 30, 2022 · Big Data

Distributed Computing Is Not a Panacea for Big Data: Prioritize Single‑Node Performance First

While distributed clusters are popular for big‑data processing, they are not a universal solution; tasks that are hard to partition or involve heavy cross‑node communication often perform better on a well‑optimized single machine, making a careful analysis of workload characteristics essential before scaling out.

Big DataPerformance TuningSPL

0 likes · 14 min read

Distributed Computing Is Not a Panacea for Big Data: Prioritize Single‑Node Performance First

Rare Earth Juejin Tech Community

Aug 30, 2022 · Fundamentals

Pattern-Defeating Quicksort (pdqsort) in Go: Design, Implementation, and Performance

This article explains the design and Go‑language implementation of the pattern‑defeating quicksort (pdqsort), a hybrid unstable sorting algorithm that leverages generics and multiple pivot‑selection strategies to achieve 2×‑60× speedups over the standard library in most cases.

GoSortingalgorithm optimization

0 likes · 17 min read

Pattern-Defeating Quicksort (pdqsort) in Go: Design, Implementation, and Performance

Architecture Digest

Jul 8, 2022 · Fundamentals

Sensitive Word Matching in Vivo's Content Review System: Algorithm Selection and Practical Implementations

The article describes how Vivo's content moderation platform, DiTing, uses algorithm selection—including Aho‑Corasick automaton, combination word matching, and pinyin‑based matching—to efficiently detect sensitive terms in large‑scale text streams, while addressing challenges such as homophones, multi‑character patterns, and performance constraints.

Aho-CorasickPinyin MatchingSensitive Word Matching

0 likes · 14 min read

Sensitive Word Matching in Vivo's Content Review System: Algorithm Selection and Practical Implementations

HelloTech

Mar 28, 2022 · Artificial Intelligence

Algorithmic Optimization for Information Flow Advertising at Hello Travel

Hello Travel tackles information‑flow advertising challenges by using LightGBM‑based models to predict order conversion, creative performance, and pre‑bid user quality, augmenting sparse data with feature engineering and uplift techniques, while planning future fully automated delivery, richer pre‑screening, and cross‑channel reinforcement‑learning enhancements.

Feature EngineeringLightGBMadvertising

0 likes · 18 min read

Algorithmic Optimization for Information Flow Advertising at Hello Travel

DataFunTalk

Mar 27, 2022 · Artificial Intelligence

Algorithmic Optimization for Information‑Flow Advertising at Hello Travel

This talk explains how Hello Travel tackles challenges in information‑flow advertising by describing the market landscape, their business background, and detailed algorithmic optimization across plan, creative, and pre‑bid dimensions, including data‑driven modeling, feature engineering, LightGBM and uplift models, and outlines future directions.

LightGBMadvertisingalgorithm optimization

0 likes · 16 min read

Tencent Cloud Developer

Sep 15, 2021 · Frontend Development

Deep Dive into Vue.js Virtual DOM Diff Algorithm and Source Code Analysis

The article thoroughly explains Vue.js’s virtual‑DOM diff algorithm, detailing its depth‑first traversal, same‑level node comparison, the sameVnode key/selector check, index map creation, O(n) head‑tail and index‑based matching loops, Vue 3 static‑type optimizations, and a practical implementation for array change detection.

Diff AlgorithmFrontend DevelopmentVirtual DOM

0 likes · 6 min read

Deep Dive into Vue.js Virtual DOM Diff Algorithm and Source Code Analysis

DataFunTalk

Aug 9, 2021 · Artificial Intelligence

Calibration Techniques for User Behavior Prediction in Online Advertising: Background, Algorithm Evolution, and Engineering Practice

This article introduces the concept of calibration in trustworthy machine learning, explains why accurate probability estimates are crucial for online advertising, reviews related research and evaluation metrics, and details the evolution of calibration algorithms such as Smoothed Isotonic Regression, Bayes‑SIR, real‑time optimizations, and post‑click conversion models, concluding with engineering deployment and future directions.

algorithm optimizationcalibrationclick-through rate

0 likes · 18 min read

Calibration Techniques for User Behavior Prediction in Online Advertising: Background, Algorithm Evolution, and Engineering Practice

Tencent Cloud Developer

Nov 27, 2020 · Game Development

Jump Point Search (JPS) and Four Optimized Variants for High‑Performance Pathfinding

The article presents Jump Point Search and four high‑performance variants—JPS‑Bit, JPS‑BitPrune, JPS‑BitPre, and JPS‑BitPrunePre—that combine bitwise acceleration, pruning, preprocessing, and compact multithreaded memory structures to achieve up to 273× faster pathfinding than classic A* on a 200‑grid benchmark.

Artificial IntelligenceGame developmentJump Point Search

0 likes · 35 min read

Jump Point Search (JPS) and Four Optimized Variants for High‑Performance Pathfinding

DataFunTalk

Sep 15, 2020 · Information Security

Optimizing Regular Expression Engines for High‑Performance Deep Packet Inspection

This article presents a series of algorithmic innovations—including efficient NFA construction, reduced epsilon‑transitions, prefix/suffix optimizations, fast NFA‑to‑DFA conversion, space‑compressed automata, hybrid finite automata, and large‑scale regex matching techniques—designed to improve regular‑expression matching speed and memory usage in deep packet inspection systems.

DFANFAalgorithm optimization

0 likes · 27 min read

Optimizing Regular Expression Engines for High‑Performance Deep Packet Inspection

58 Tech

Sep 7, 2020 · Artificial Intelligence

Optimizing Individual Diversity in Recommendation Systems: Architecture, MMR and DPP Implementation at 58 Tribe

This article presents a comprehensive study on improving individual diversity in recommendation systems by detailing architectural optimizations across recall, rule, and re‑ranking layers, explaining the principles and practical deployment of MMR and DPP algorithms, and demonstrating their impact on key business metrics through extensive experiments.

Custom DistanceDPPMMR

0 likes · 18 min read

Optimizing Individual Diversity in Recommendation Systems: Architecture, MMR and DPP Implementation at 58 Tribe

Qunar Tech Salon

Jun 3, 2020 · Fundamentals

Optimizing International Hotel Data Aggregation Algorithms at Qunar

The article outlines Qunar’s challenges in aggregating international hotel data, analyzes issues such as localized address formats and limited text similarity parsing, and presents a pattern‑matching and weighted scoring approach that improves aggregation accuracy across multiple countries.

Pattern Matchingalgorithm optimizationdata integration

0 likes · 7 min read

Optimizing International Hotel Data Aggregation Algorithms at Qunar

Selected Java Interview Questions

Feb 13, 2020 · Fundamentals

Quick Sort: Overview, Naïve Implementation, Optimizations, and Non‑Recursive Version

This article explains the quick sort algorithm, covering its basic divide‑and‑conquer principle, a naïve C implementation, improvements such as two‑way partitioning, random and median‑of‑three pivot selection, and a non‑recursive version using an explicit stack, with full source code examples.

C languagealgorithm optimizationdivide and conquer

0 likes · 9 min read

Quick Sort: Overview, Naïve Implementation, Optimizations, and Non‑Recursive Version

Snowball Engineer Team

Sep 4, 2019 · Artificial Intelligence

Advancing Recommendation Systems at Xueqiu: Transitioning from Point-Wise CTR Prediction to Pair-Wise TF-Ranking

This article explores the evolution of recommendation algorithms at Xueqiu, highlighting the limitations of traditional point-wise click-through rate prediction models and detailing the ongoing transition to a pair-wise TF-Ranking framework designed to mitigate user and content biases while significantly enhancing overall recommendation accuracy and user experience.

CTR predictionPair-Wise LearningRecommendation systems

0 likes · 5 min read

Advancing Recommendation Systems at Xueqiu: Transitioning from Point-Wise CTR Prediction to Pair-Wise TF-Ranking

JD Retail Technology

Jun 15, 2019 · Artificial Intelligence

Comprehensive 6.18 Preparation: Load Testing, Deep Personalization, and Recommendation Algorithm Optimizations

The department’s extensive 6.18 preparation involved systematic load‑testing, deep learning‑driven personalization of search recommendations, and multiple algorithmic enhancements to improve relevance and conversion, supported by detailed planning, cross‑team coordination, and dedicated night‑shift logistics.

AIRecommendation systemsalgorithm optimization

0 likes · 6 min read

Comprehensive 6.18 Preparation: Load Testing, Deep Personalization, and Recommendation Algorithm Optimizations