Graph Computing

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.

Brain SimulationDigital BrainGraph Computing

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

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.

DSLGraph ComputingTuGraph-Analytics

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Applying TuGraph-Analytics for Graph Computing and Data Warehouse Acceleration

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.

Graph ComputingTuGraphbig data

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Ant TuGraph Computing Engine Architecture and Applications

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 GroupGraph Computing

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

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.

Graph ComputingHot DeploymentXiaohongshu

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

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 TrackingGraph ComputingID-Mapping

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How ID‑Mapping Connects Data Silos Across Industries

AntTech

Sep 7, 2023 · Artificial Intelligence

Ant Group Introduces Large Graph Model (LGM) Integrating Graph Computing and Large Language Models

At the 2023 Bund Conference, Ant Group unveiled the Large Graph Model (LGM), a research effort that merges graph computing with large language models to enhance data representation and insight generation, marking a significant step toward advanced generative AI applications.

Ant GroupGenerative AIGraph Computing

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Ant Group Introduces Large Graph Model (LGM) Integrating Graph Computing and Large Language Models

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 Networksartificial intelligence

0 likes · 12 min read

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

DataFunTalk

Jun 15, 2023 · Big Data

Graph Language and GeaFlow DSL for Integrated Graph‑Table Analytics in Ant Financial

The article presents Ant Financial's practice of graph language and the GeaFlow DSL, covering graph models, query languages, DSL design, architecture, performance optimizations, distributed execution, binary data handling, and future roadmap for unified graph‑table analytics.

DSLGeaFlowGraph Computing

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Graph Language and GeaFlow DSL for Integrated Graph‑Table Analytics in Ant Financial

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.

Graph ComputingGraph Neural Networksartificial intelligence

0 likes · 15 min read

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

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.

Graph ComputingPerformance OptimizationUltipa

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

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.

Graph Computingcommunity-detectiondistributed systems

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

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.

E-commerceGraph Computinganti-fraud

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

AntTech

Sep 21, 2022 · Big Data

2022 China Graph Computing Technology and Application Development Research Report Overview

China’s graph computing landscape is rapidly evolving, with the 2022 CB Insights report detailing the technology’s shift from traditional relational databases to graph databases and engines, highlighting industry growth, academic research surges, major investments, open‑source initiatives, and diverse applications across finance, energy, and AI.

AIGraph ComputingIndustry Analysis

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2022 China Graph Computing Technology and Application Development Research Report Overview

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.

AIAI SafetyAnt Group

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

AntTech

Sep 2, 2022 · Databases

Highlights of the 2022 World AI Conference Graph Intelligence Forum in Shanghai

The September 1, 2022 Graph Intelligence Forum at the World AI Conference in Shanghai gathered leading researchers and industry experts to discuss advances in graph computing, learning, and databases, announced the open‑source TuGraph as the world’s fastest graph database, and emphasized standards, temporal graphs, and industry‑academia collaboration.

AIGraph ComputingLDBC

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Highlights of the 2022 World AI Conference Graph Intelligence Forum in Shanghai

AntTech

Aug 28, 2022 · Databases

Insights from the Beijing Graph Computing Seminar: Industry‑Academia Collaboration and Future Directions

The Beijing seminar co‑hosted by MIT Technology Review China and Ant Group highlighted the rapid rise of graph computing, discussed academic‑industry cooperation models, explored research hotspots such as distributed graph platforms and AI‑driven graph pre‑training, and examined practical challenges and future prospects for graph databases across sectors.

Graph ComputingIndustry-Academia Collaborationartificial intelligence

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Insights from the Beijing Graph Computing Seminar: Industry‑Academia Collaboration and Future Directions

AntTech

Aug 22, 2022 · Information Security

Intelligent Risk Control Enters the 10‑Millisecond Era

In a 2022 IDC China Digital Finance Forum speech, Ant Group's security chief outlines the shift from explicit to implicit online risks, identifies three major challenges for risk control, and presents Ant's AI‑driven IMAGE framework that achieves sub‑10 ms detection across privacy‑preserving, multi‑party, and graph‑based technologies.

AIGraph ComputingMachine Learning

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Intelligent Risk Control Enters the 10‑Millisecond Era

AntTech

Jun 30, 2022 · Big Data

Ant Group's TuGraph Passes Trusted Big Data Evaluation and Becomes First Certified Graph Computing Platform

Ant Group’s large‑scale graph computing system TuGraph recently passed the China Academy of Information and Communications Technology’s Trusted Big Data assessment, becoming one of the first graph platforms certified for basic capabilities, compatibility, management, high availability and scalability, and highlighting its critical role in financial risk control.

Ant GroupGraph ComputingTrusted Data

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Ant Group's TuGraph Passes Trusted Big Data Evaluation and Becomes First Certified Graph Computing Platform

DataFunSummit

Jun 28, 2022 · Big Data

GeaFlow: Ant Group’s Real‑Time Streaming Graph Computing Engine and Its Applications

This article introduces GeaFlow, Ant Group’s self‑developed real‑time streaming graph engine, covering its basic concepts, technical architecture, dynamic and fusion computing capabilities, integrated DSL, and several large‑scale business use cases such as fraud detection and incremental community mining.

Ant GroupGeaFlowGraph Computing

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GeaFlow: Ant Group’s Real‑Time Streaming Graph Computing Engine and Its Applications