community-detection

Python Programming Learning Circle

Nov 22, 2024 · Artificial Intelligence

Introducing the Python "communities" Library for Graph Clustering and Visualization

This article introduces the Python "communities" library, explains its support for multiple graph clustering algorithms such as Louvain and Girvan‑Newman, demonstrates how to import algorithms, build adjacency matrices, visualize communities, create animation of the clustering process, and provides author and resource information.

Graph ClusteringLouvain Algorithmcommunity-detection

0 likes · 7 min read

Introducing the Python "communities" Library for Graph Clustering and Visualization

DataFunSummit

Oct 31, 2024 · Artificial Intelligence

Community Recommendation in Tencent Games: Adaptive K‑Free Community Detection and Constrained Large‑Scale Community Recommendation (ComRec)

This article presents Tencent's research on community recommendation for online games, introducing an adaptive K‑Free community detection algorithm (DAG) to address cold‑start and unknown community count, a constrained large‑scale recommendation method (ComRec), their evaluation metrics, experimental results, and deployment insights.

Graph Neural NetworksRecommendation systemsTencent games

0 likes · 20 min read

Community Recommendation in Tencent Games: Adaptive K‑Free Community Detection and Constrained Large‑Scale Community Recommendation (ComRec)

Python Programming Learning Circle

Jun 28, 2024 · Artificial Intelligence

Python 'communities' Library: Implementing Louvain, Girvan‑Newman, Hierarchical, Spectral, and Bron‑Kerbosch Community Detection Algorithms

This article introduces the open‑source Python library communities, which provides implementations of several community‑detection algorithms—including Louvain, Girvan‑Newman, hierarchical clustering, spectral clustering, and Bron‑Kerbosch—along with installation instructions, usage examples, and visualization tools for network analysis.

Pythoncommunity-detectiongraph algorithms

0 likes · 6 min read

Python 'communities' Library: Implementing Louvain, Girvan‑Newman, Hierarchical, Spectral, and Bron‑Kerbosch Community Detection Algorithms

AntTech

Dec 13, 2023 · Artificial Intelligence

IEEE ICDM 2023 Graph Learning Challenge: Community Detection and Fraud Group Mining

The IEEE ICDM 2023 Graph Learning Challenge, co‑hosted by Ant Group and Zhejiang University, showcased deep graph learning approaches for community detection and fraud‑group mining, highlighting the winning team's Risk‑DCRN method and emphasizing the importance of pretrained models in large‑scale network analysis.

ICDMcommunity-detectiondeep learning

0 likes · 5 min read

IEEE ICDM 2023 Graph Learning Challenge: Community Detection and Fraud Group Mining

JD Tech

Sep 12, 2023 · Fundamentals

Community Detection Algorithms: Concepts, Types, and Classic Methods

This article introduces community detection as a fundamental graph algorithm, explains its basic concepts and types, compares it with clustering, discusses evaluation metrics like modularity, and reviews classic methods such as Louvain, node2vec‑based approaches, and the information‑theoretic Infomap algorithm.

InfomapLouvaincommunity-detection

0 likes · 13 min read

Community Detection Algorithms: Concepts, Types, and Classic Methods

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

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

Baidu Geek Talk

Aug 16, 2022 · Artificial Intelligence

Louvain Algorithm for Community Detection in Anti‑Fraud Systems

The Louvain algorithm, a fast modularity‑maximizing community‑detection method, iteratively merges nodes into hierarchical super‑nodes, enabling anti‑fraud systems to uncover hidden collusive groups in weighted transaction graphs, thereby improving detection of fake orders, coupon abuse, and other illicit behaviors despite its iterative nature and streaming limitations.

Louvainanti-fraudcommunity-detection

0 likes · 10 min read

Louvain Algorithm for Community Detection in Anti‑Fraud Systems

58 Tech

Dec 14, 2021 · Artificial Intelligence

Unsupervised Community Detection for Black‑Market Identification Using the Louvain Algorithm

This article presents an unsupervised community‑discovery approach based on the Louvain algorithm to identify black‑market accounts, describing the threat landscape, system architecture, algorithmic principles, optimizations, experimental results, and future directions for improving risk detection in large‑scale online services.

Big DataLouvain Algorithmblack market

0 likes · 10 min read

Unsupervised Community Detection for Black‑Market Identification Using the Louvain Algorithm

Baidu Intelligent Testing

Sep 14, 2021 · Information Security

Community Encoding Based Detection of Black and Gray Market Attacks Using Graph Embedding

This article presents a community‑encoding approach that leverages large‑scale graph‑embedding (GraphSAGE) and asynchronous near‑real‑time engineering to identify and measure unknown black‑gray market attacks with higher accuracy and flexibility than traditional graph‑mining methods.

GraphSAGEblack‑gray marketcommunity-detection

0 likes · 15 min read

Community Encoding Based Detection of Black and Gray Market Attacks Using Graph Embedding

Baidu Geek Talk

Jun 23, 2021 · Information Security

Black-Gray Industry Attack Detection Based on Community Encoding Using Graph Embedding

The paper introduces a community‑encoding, GraphSAGE‑based detection framework that embeds whole user‑account, IP, device, and phone‑number graphs—both homogeneous and heterogeneous—to identify previously unseen black‑gray industry attacks, achieving about 95% IP‑risk accuracy via an asynchronous near‑real‑time system, though computational and automation challenges persist.

GraphSAGEblack-gray-industrycommunity-detection

0 likes · 12 min read

Black-Gray Industry Attack Detection Based on Community Encoding Using Graph Embedding

DataFunTalk

Oct 8, 2020 · Artificial Intelligence

Community Detection in Graphs: Granovetter's Theory, Louvain Algorithm, and Overlapping Communities with BigCLAM

This article explains the concept of communities in graphs, illustrates Granovetter's weak tie theory, introduces the Louvain algorithm for modularity‑based community detection, and presents the overlapping‑community detection method BigCLAM built on the Community Affiliation Graph Model.

BigCLAMLouvain Algorithmcommunity-detection

0 likes · 8 min read

Community Detection in Graphs: Granovetter's Theory, Louvain Algorithm, and Overlapping Communities with BigCLAM

360 Tech Engineering

May 30, 2019 · Artificial Intelligence

Louvain Algorithm: Theory, Design, and Implementation

The article explains the Louvain community‑detection algorithm, detailing its modularity‑maximizing objective, two‑step iterative process, efficient graph data structures, practical implementation considerations, and performance results on large‑scale graphs, providing a comprehensive guide for practitioners.

Big DataC ImplementationLouvain

0 likes · 7 min read

Louvain Algorithm: Theory, Design, and Implementation

DataFunTalk

Apr 28, 2019 · Artificial Intelligence

Graph Algorithms for Fraud Detection and Community Detection: Modularity, Louvain, Infomap, node2vec and comE

This article explains how graph‑based algorithms such as centrality measures, modularity optimization, Louvain, Infomap, node2vec and the comE framework can be applied to financial fraud detection and community discovery, detailing their principles, formulas, implementation steps and evaluation metrics.

InfomapLouvaincommunity-detection

0 likes · 14 min read

Graph Algorithms for Fraud Detection and Community Detection: Modularity, Louvain, Infomap, node2vec and comE

Architect

May 22, 2015 · Big Data

Weibo Social Network Analysis: Label Propagation, Similarity Measures, Community Detection, Influence Ranking and Spam User Identification

The article presents a comprehensive overview of algorithms for analyzing Weibo’s social network, covering label propagation, user similarity via LDA, temporal and interaction factors, community detection, influence ranking using PageRank variants, and methods for identifying spam accounts.

LDAcommunity-detectioninfluence ranking

0 likes · 16 min read