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AntTech
AntTech
Sep 10, 2024 · Artificial Intelligence

Exploring the Mysteries of the Biological Brain and Digital Brain: Insights from Ant Group’s Graph Computing Lab and Fudan University

In a 2024 Inclusion conference talk, researchers from Ant Group’s Graph Computing Lab and Fudan University discussed the structure and limited understanding of the human brain, introduced the concept and challenges of building a digital brain, and highlighted a joint graph‑based brain simulation project aimed at advancing both neuroscience and artificial intelligence.

Artificial IntelligenceDigital Brainbrain simulation
0 likes · 4 min read
Exploring the Mysteries of the Biological Brain and Digital Brain: Insights from Ant Group’s Graph Computing Lab and Fudan University
DataFunTalk
DataFunTalk
Mar 14, 2024 · Big Data

Applying TuGraph-Analytics for Graph Computing and Data Warehouse Acceleration

This article introduces TuGraph-Analytics, a real‑time stream‑graph engine and its DSL, explains its architecture and core capabilities, demonstrates how graph modeling can accelerate data‑warehouse workloads, and outlines future plans for SQL‑to‑graph translation, performance optimizations, and open‑source development.

DSLTuGraph-Analyticsgraph computing
0 likes · 13 min read
Applying TuGraph-Analytics for Graph Computing and Data Warehouse Acceleration
DataFunSummit
DataFunSummit
Mar 8, 2024 · Databases

Ant TuGraph Computing Engine Architecture and Applications

Ant TuGraph’s open‑source graph computing engine, led by Fang Zhihong, will be introduced covering its development history, architectural design, technical principles, integrated stream‑batch‑graph processing capabilities, real‑world large‑scale graph use cases, and future roadmap, offering insights into design, implementation, and value.

Big DataDistributed SystemsTuGraph
0 likes · 2 min read
Ant TuGraph Computing Engine Architecture and Applications
AntTech
AntTech
Sep 15, 2023 · Artificial Intelligence

Ant Group Unveils Large Graph Model (LGM) Merging Graph Computing with Large Language Models

At the 2023 Bund Conference, Ant Group presented the Large Graph Model (LGM), a research effort that combines graph computing, graph learning, and large language models to enrich heterogeneous graph data and enable more precise insights for complex digital applications, with results accepted at WWW 2023.

AI researchAnt GroupLarge Graph Model
0 likes · 6 min read
Ant Group Unveils Large Graph Model (LGM) Merging Graph Computing with Large Language Models
DataFunSummit
DataFunSummit
Sep 12, 2023 · Backend Development

Xiaohongshu Recommendation Engineering Architecture: Graph Architecture, Hot Deployment, and Practices

This article presents Xiaohongshu's evolving recommendation engineering architecture, detailing its modular backend design, graph-based Ark framework, hot deployment mechanisms, and the challenges and solutions for scaling personalized content delivery in a fast‑growing mobile platform.

Backend ArchitectureHot DeploymentScalable Systems
0 likes · 13 min read
Xiaohongshu Recommendation Engineering Architecture: Graph Architecture, Hot Deployment, and Practices
Data Thinking Notes
Data Thinking Notes
Sep 10, 2023 · Big Data

How ID‑Mapping Connects Data Silos Across Industries

This article explains the fundamentals of ID‑Mapping, its importance for unifying fragmented user and device data, showcases industry solutions from Alibaba, NetEase, 58.com and Meituan, and outlines technical approaches such as priority‑based rules and graph‑based computation.

Cross-device TrackingID-Mappinggraph computing
0 likes · 10 min read
How ID‑Mapping Connects Data Silos Across Industries
JD Tech
JD Tech
Jul 24, 2023 · Artificial Intelligence

An Introduction to Graph Computing: Concepts, History, and Real‑World Applications

This article provides a comprehensive overview of graph computing, covering its fundamental concepts, historical development from Euler's bridges to modern graph neural networks, various algorithmic techniques, and practical applications in search, recommendation, finance, fraud detection, and many other AI‑driven domains.

graph computinggraph neural networksgraph theory
0 likes · 12 min read
An Introduction to Graph Computing: Concepts, History, and Real‑World Applications
WeChat Backend Team
WeChat Backend Team
Jun 7, 2023 · Artificial Intelligence

How TransE+ Boosts Knowledge Graph Embedding on WeChat’s Plato Framework

This article presents the development and deployment of the TransE+ knowledge‑graph embedding model on the Plato graph‑computing platform, detailing its architectural upgrades, training optimizations, performance gains, and business‑oriented adaptations for large‑scale real‑world applications.

EmbeddingTransE+ai
0 likes · 22 min read
How TransE+ Boosts Knowledge Graph Embedding on WeChat’s Plato Framework
DataFunTalk
DataFunTalk
May 29, 2023 · Artificial Intelligence

Applying Graph Computing for Risk Control in Wing Pay: Architecture, Algorithms, and Future Directions

The presentation details how Wing Pay leverages graph computing and graph neural networks to detect and mitigate financial fraud across payment, e‑commerce, and credit scenarios, describing business background, system architecture, algorithmic approaches, real‑time subgraph mining, and future research directions.

distributed graph databasefinancial fraud detectiongraph computing
0 likes · 15 min read
Applying Graph Computing for Risk Control in Wing Pay: Architecture, Algorithms, and Future Directions
JD Cloud Developers
JD Cloud Developers
May 17, 2023 · Artificial Intelligence

Why Graph Computing Is the Hidden Powerhouse Behind AI and Fraud Detection

This article introduces graph computing, explaining its fundamentals, historical origins, key concepts such as nodes, edges, degrees, and graph representations, and explores its algorithms, graph neural networks, and real‑world applications ranging from search engines and social graphs to financial fraud detection and emerging AI technologies.

Artificial Intelligencefraud detectiongraph computing
0 likes · 12 min read
Why Graph Computing Is the Hidden Powerhouse Behind AI and Fraud Detection
DataFunTalk
DataFunTalk
Apr 27, 2023 · Databases

Graph Computation Correctness Verification and Optimization in Ultipa XAI Real‑Time Graph Database

This article presents Ultipa CEO Sun Yuxi’s comprehensive overview of high‑performance real‑time graph database Ultipa XAI, covering graph theory evolution, typical graph computation challenges, error analysis, verification examples, and optimization strategies to ensure accurate and efficient graph algorithm results.

Ultipaalgorithm verificationgraph computing
0 likes · 12 min read
Graph Computation Correctness Verification and Optimization in Ultipa XAI Real‑Time Graph Database
DataFunTalk
DataFunTalk
Oct 28, 2022 · Big Data

Angel Graph: A High‑Performance Distributed Graph Computing Framework for Intelligent Risk Control

Angel Graph is a high‑performance, fault‑tolerant distributed graph computing framework developed by Tencent, featuring scalable node‑metric, community‑detection, and graph‑neural‑network algorithms optimized for billion‑node, trillion‑edge datasets, and demonstrated through practical applications in intelligent financial risk control.

Distributed Systemscommunity-detectiongraph computing
0 likes · 20 min read
Angel Graph: A High‑Performance Distributed Graph Computing Framework for Intelligent Risk Control
Xiaohongshu Tech REDtech
Xiaohongshu Tech REDtech
Sep 22, 2022 · Big Data

Graph Computing Algorithms for E‑commerce Anti‑Fraud and Reselling Bot Detection

The Xiaohongshu anti‑fraud team combats sophisticated same‑group and crowdsourced reselling bots by ingesting real‑time transaction streams into a Nebula Graph, using multi‑hop sub‑graph sampling, label propagation, and modularity‑based community detection to identify suspicious clusters, update risk pools, and enforce personalized purchase‑limit rules.

Big Dataanti-fraudbot detection
0 likes · 9 min read
Graph Computing Algorithms for E‑commerce Anti‑Fraud and Reselling Bot Detection
AntTech
AntTech
Sep 3, 2022 · Artificial Intelligence

Highlights from the 2022 World AI Conference: Graph Computing, Privacy Computing, AI Safety, and New Open Platforms

The 2022 World AI Conference in Shanghai showcased cutting‑edge research on graph computing and privacy computing, announced Ant Group’s new AI safety product “AntJian”, the “YinYu Open Platform” for trusted privacy computing, and the open‑source high‑performance graph database TuGraph, highlighting the push for secure, scalable AI technologies.

AI SafetyAnt GroupOpen Platform
0 likes · 7 min read
Highlights from the 2022 World AI Conference: Graph Computing, Privacy Computing, AI Safety, and New Open Platforms
DataFunSummit
DataFunSummit
Jun 16, 2022 · Artificial Intelligence

Exploring Graph Computing for Credit Fraud Detection: Background, Applications, Risk Graph System, and Performance Optimization

This article presents a comprehensive overview of how graph computing, powered by AI and big‑data techniques, is applied to credit fraud detection, covering background, pre‑mid‑post fraud scenarios, the risk graph architecture, performance tuning methods, and a Q&A with Ant Group experts.

aicredit fraud detectiongraph computing
0 likes · 14 min read
Exploring Graph Computing for Credit Fraud Detection: Background, Applications, Risk Graph System, and Performance Optimization
AntTech
AntTech
Jun 14, 2022 · Big Data

Insights on Graph Computing: Technology, Applications, and Future Directions

Professor Chen Wenguang discusses how graph computing—originating from graph theory—offers a powerful way to model relationships across industries, its rapid development in China, challenges in scaling, integration with AI via graph neural networks, and the collaborative efforts needed between academia and industry to advance the field.

Big DataGraph Processingai
0 likes · 17 min read
Insights on Graph Computing: Technology, Applications, and Future Directions
ITPUB
ITPUB
May 27, 2022 · Databases

How HugeGraph’s Self‑Built Graph Computing Tackles Large‑Scale Graph Challenges

This article explains the fundamentals of graph computing, compares it with traditional processing, outlines industry challenges such as partitioning and load imbalance, and details HugeGraph’s self‑developed architecture, key technical solutions, and how developers can create and deploy graph algorithms.

Algorithm DevelopmentData PartitioningGraph Database
0 likes · 14 min read
How HugeGraph’s Self‑Built Graph Computing Tackles Large‑Scale Graph Challenges
DataFunTalk
DataFunTalk
May 11, 2022 · Artificial Intelligence

Graph and AI Accelerate Supply Chain Digital Transformation

This presentation explores how combining graph computing with artificial intelligence can address modern supply chain challenges, improve decision‑making, and enable digital transformation, illustrated by a Jaguar Land Rover case study that demonstrates risk analysis, optimization, and cost reduction.

Digital TransformationSupply ChainTigerGraph
0 likes · 12 min read
Graph and AI Accelerate Supply Chain Digital Transformation
DataFunSummit
DataFunSummit
Apr 16, 2022 · Big Data

Angel Graph: A Scalable Graph Computing Platform – Architecture, Optimizations, and Applications

The article introduces Angel Graph, a large‑scale graph computing platform built on Angel's parameter‑server architecture and Spark, detailing its evolution, framework components (including Spark‑on‑Angel and PyTorch‑on‑Angel), data and model partitioning strategies, communication and computation optimizations, stability mechanisms, usability features, and real‑world applications across recommendation, risk control, social and gaming domains.

Parameter ServerPyTorchSpark
0 likes · 15 min read
Angel Graph: A Scalable Graph Computing Platform – Architecture, Optimizations, and Applications
AntTech
AntTech
Mar 1, 2022 · Big Data

Graph Computing at Ant Group: From Fraud Prevention to Industry‑Wide Impact

The article explains how Ant Group leverages large‑scale graph computing—through its GeaBase and TuGraph platforms and a dedicated research team—to enhance real‑time fraud detection, drive industry standards, and explore future applications across finance, energy, and public services.

Ant GroupBig DataTuGraph
0 likes · 7 min read
Graph Computing at Ant Group: From Fraud Prevention to Industry‑Wide Impact
DataFunTalk
DataFunTalk
Dec 27, 2021 · Databases

Graph Theory, Graph Databases, and the Graph Intelligent Platform: Concepts, Development, and Tencent Use Cases

This article explores the fundamentals and evolution of graph theory, graph databases, and graph computing, discusses Tencent's self‑built graph stack—including EasyGraph, Angel‑Graph, and visualization tools—and demonstrates real‑world applications such as scheduling, financial payment analysis, and fraud detection, highlighting performance gains and future trends.

Graph VisualizationTencentfraud detection
0 likes · 17 min read
Graph Theory, Graph Databases, and the Graph Intelligent Platform: Concepts, Development, and Tencent Use Cases
AntTech
AntTech
Dec 23, 2021 · Databases

Understanding Graph Computing: Fundamentals, Applications, and Future Directions

This article explains graph computing fundamentals, illustrates its use in fraud detection, search ranking, and brain modeling, highlights Ant Group's record‑breaking performance and standards efforts, and outlines future challenges such as standardization, higher performance, and integration with AI.

Artificial IntelligenceBig Datagraph computing
0 likes · 13 min read
Understanding Graph Computing: Fundamentals, Applications, and Future Directions
JD Retail Technology
JD Retail Technology
Dec 20, 2021 · Artificial Intelligence

Large-Scale Graph Technology in JD.com E‑commerce: Practice and AI Computing Directions

The article summarizes JD.com Vice President Bao Yongjun's presentation on applying ultra‑large‑scale graph technology to e‑commerce, covering data foundations, recommendation and fraud detection use cases, technical challenges, the Galileo graph engine, and future AI computing development directions such as chips, auto‑learning, application layers, and privacy protection.

e‑commercefraud detectiongraph computing
0 likes · 7 min read
Large-Scale Graph Technology in JD.com E‑commerce: Practice and AI Computing Directions
DataFunTalk
DataFunTalk
Oct 8, 2021 · Artificial Intelligence

Graph Computing for Financial Credit Risk Control: Architecture, Challenges, and Lessons Learned

This article explores how graph computing is applied to financial credit risk and anti‑fraud, detailing the business background, terminology, stakeholder roles, system requirements, architectural evolution across three phases, practical challenges, and key take‑aways for building stable, timely, accurate, and controllable graph‑based risk models.

aifinancial riskfraud detection
0 likes · 14 min read
Graph Computing for Financial Credit Risk Control: Architecture, Challenges, and Lessons Learned
DataFunSummit
DataFunSummit
Oct 8, 2021 · Artificial Intelligence

Graph Computing for Financial Credit Risk Control and Anti‑Fraud: Architecture, Challenges, and Lessons Learned

This article examines how graph computing is applied to financial credit risk management and anti‑fraud, covering business background, key credit terminology, stakeholder roles, graph‑based fraud detection techniques, system architecture evolution across three development stages, practical requirements such as stability, timeliness, accuracy and controllability, and summarizes operational insights.

aianti-fraudgraph computing
0 likes · 16 min read
Graph Computing for Financial Credit Risk Control and Anti‑Fraud: Architecture, Challenges, and Lessons Learned
AntTech
AntTech
Sep 28, 2021 · Databases

GeaGraph: Large-Scale Graph Computing System Wins World Internet Conference Award

The Ant Group and Tsinghua University’s jointly developed large‑scale graph computing system GeaGraph, recognized at the 2021 World Internet Conference, showcases world‑leading performance in trillion‑edge graph queries and exemplifies successful industry‑academia‑research collaboration for advanced database technology.

Big DataGeaGraphIndustry-Academia Collaboration
0 likes · 8 min read
GeaGraph: Large-Scale Graph Computing System Wins World Internet Conference Award
DataFunSummit
DataFunSummit
Sep 19, 2021 · Artificial Intelligence

Graph Computing for Risk Control in WeChat Pay: From Feature Engineering to Network Analysis

This talk explains how WeChat Pay leverages graph algorithms, graph databases, and graph neural networks to combat fraud at massive scale, covering new risk‑control perspectives, the three‑pillar graph computing platform, practical applications, and the team’s innovations in algorithm design and deployment.

Graph DatabaseGraph Neural NetworkWeChat Pay
0 likes · 18 min read
Graph Computing for Risk Control in WeChat Pay: From Feature Engineering to Network Analysis
DataFunTalk
DataFunTalk
Aug 19, 2021 · Artificial Intelligence

Graph Computing for Risk Control in WeChat Pay: Platforms, Algorithms, and Practices

This talk presents how WeChat Pay leverages graph computing, including graph databases, engines, and algorithms such as GNN and PageRank, to combat fraud and money‑laundering by shifting from individual feature engineering to network‑level analysis, highlighting platform choices, practical experiences, and technology‑for‑good outcomes.

GNNGraph DatabaseWeChat Pay
0 likes · 16 min read
Graph Computing for Risk Control in WeChat Pay: Platforms, Algorithms, and Practices
Volcano Engine Developer Services
Volcano Engine Developer Services
May 13, 2021 · Databases

Inside ByteGraph: How ByteDance Built a Scalable Distributed Graph Database

The article offers a comprehensive technical deep‑dive into ByteDance’s home‑grown distributed graph database and graph‑processing engine, ByteGraph, covering its directed‑property graph model, Gremlin query support, multi‑layer architecture, storage strategies for massive data, and real‑world graph‑computing practices.

Big DataByteGraphGraph Database
0 likes · 28 min read
Inside ByteGraph: How ByteDance Built a Scalable Distributed Graph Database
JD Tech
JD Tech
Mar 30, 2021 · Artificial Intelligence

JD Retail's Jiushu Business Analytics Platform: AI‑Driven Solutions for Retail

The article introduces JD Retail's Jiushu Business Analytics Platform, detailing how AI, big‑data, and distributed‑training technologies address fragmented retail scenarios, high deployment barriers, large‑scale application difficulties, and cost concerns through specialized frameworks, fault‑tolerant training, and advanced cluster optimization.

Cluster ManagementDistributed TrainingRetail
0 likes · 12 min read
JD Retail's Jiushu Business Analytics Platform: AI‑Driven Solutions for Retail
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 17, 2020 · Big Data

Why GraphScope is Revolutionizing Large-Scale Graph Computing for AI and Big Data

GraphScope, an open‑source one‑stop platform from Alibaba DAMO Academy, unifies interactive queries, graph analytics, and graph learning on massive, rapidly evolving graphs, offering high‑performance distributed memory management, Gremlin optimization, and seamless Python integration to tackle real‑world AI and big‑data challenges.

Big DataDistributed SystemsPython
0 likes · 21 min read
Why GraphScope is Revolutionizing Large-Scale Graph Computing for AI and Big Data
JD Cloud Developers
JD Cloud Developers
Oct 26, 2020 · Artificial Intelligence

Top Tech Breakthroughs: Open‑Source Graph AI, Moon 4G, Brain‑Inspired Computing

This roundup covers JD's upcoming open‑source graph AI platform, LINE's CBDC talks with Asian central banks, NASA's lunar 4G network plan, Microsoft‑SpaceX cloud rivalry, Nvidia's Ampere GPU supercomputer, Intel‑powered AI satellite, a heterogenous GNN for malware detection, and a brain‑inspired computing architecture advancing AI research.

Blockchainaibrain-inspired computing
0 likes · 8 min read
Top Tech Breakthroughs: Open‑Source Graph AI, Moon 4G, Brain‑Inspired Computing
Tencent Cloud Developer
Tencent Cloud Developer
Jul 8, 2020 · Artificial Intelligence

Graph-Based Chinese Word Embedding (AlphaEmbedding) for Improved Text Matching

AlphaEmbedding builds a weighted graph linking Chinese words, sub‑words, characters and pinyin, then uses random‑walk‑based node2vec training to produce embeddings that capture orthographic and phonetic similarity, markedly improving recall and ranking for homophones, typos and OOV terms in enterprise search.

Chinese NLPgraph computingsemantic similarity
0 likes · 17 min read
Graph-Based Chinese Word Embedding (AlphaEmbedding) for Improved Text Matching
DataFunTalk
DataFunTalk
Feb 26, 2020 · Databases

ByteGraph: ByteDance’s Distributed Graph Database and Graph Computing System – Architecture, Data Model, and Practices

This article presents an in‑depth technical overview of ByteGraph, ByteDance’s self‑built distributed graph database and its accompanying graph‑computing engine, covering graph data characteristics, the directed‑property graph model, API design, three‑tier system architecture, storage strategies using KV stores and B‑Trees, hotspot handling, indexing, and future research directions.

B+TreeByteGraphGraph Database
0 likes · 33 min read
ByteGraph: ByteDance’s Distributed Graph Database and Graph Computing System – Architecture, Data Model, and Practices
WeChat Backend Team
WeChat Backend Team
Nov 26, 2019 · Big Data

Plato: Tencent’s Open‑Source Engine Cutting Billion‑Node Graph Jobs to Minutes

Plato, the newly open‑sourced high‑performance graph computing framework from Tencent’s TGraph project, delivers industry‑leading speed and memory efficiency for billion‑node social network graphs, achieving minute‑level processing with as few as ten servers, and supports a wide range of graph algorithms and learning tasks.

Distributed Systemsgraph computinghigh performance
0 likes · 8 min read
Plato: Tencent’s Open‑Source Engine Cutting Billion‑Node Graph Jobs to Minutes
Tencent Cloud Developer
Tencent Cloud Developer
Nov 14, 2019 · Big Data

Tencent Announces Open‑Source High‑Performance Graph Computing Framework Plato

Tencent has open‑sourced its high‑performance graph computing framework Plato, which can process billion‑node graphs in minutes on as few as ten servers, outpacing Spark GraphX by up to two orders of magnitude, and supports offline computation, representation learning, and integration with Kubernetes/YARN for social, recommendation, and biomedical applications.

Big DataDistributed SystemsPLATO
0 likes · 7 min read
Tencent Announces Open‑Source High‑Performance Graph Computing Framework Plato
Alibaba Cloud Developer
Alibaba Cloud Developer
May 22, 2017 · Artificial Intelligence

AI, Big Data, and Graph Computing Take Center Stage at ACM TURC 2017

The ACM TURC 2017 conference in Shanghai gathered Turing Award laureates, leading Chinese scholars, and Alibaba executives, highlighting breakthroughs in artificial intelligence, big data, streaming and graph computing, and showcasing AI-driven medical imaging diagnostics and collaborative research initiatives between industry and academia.

Artificial Intelligencegraph computingmedical imaging
0 likes · 4 min read
AI, Big Data, and Graph Computing Take Center Stage at ACM TURC 2017
Java High-Performance Architecture
Java High-Performance Architecture
Jun 22, 2016 · Databases

Why Apache TinkerPop Is Becoming a Top Graph Computing Framework

Apache TinkerPop, now a top-level Apache project, offers a powerful graph computing framework with Gremlin, supporting real-time transactional processing and batch analytics across languages, scalable from single machines to massive clusters, making it essential for data mining, analysis, and large‑scale graph applications.

GremlinTinkerPopdata mining
0 likes · 4 min read
Why Apache TinkerPop Is Becoming a Top Graph Computing Framework