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DataFunTalk

Jan 31, 2021 · Artificial Intelligence

Applying Graph Algorithms and Graph Convolutional Networks for Advertising Anti‑Fraud at 58.com

This article explains how various graph algorithms—including connected components, label propagation, Louvain community detection, and Graph Convolutional Networks—are built on large‑scale user‑behavior graphs using Spark GraphX to detect and mitigate advertising fraud, detailing methodology, implementation, and experimental results.

GCNLouvainSpark GraphX

0 likes · 13 min read

Applying Graph Algorithms and Graph Convolutional Networks for Advertising Anti‑Fraud at 58.com

58 Tech

Nov 18, 2020 · Artificial Intelligence

Applying Graph Algorithms and Graph Convolutional Networks to Advertising Anti‑Fraud

This article describes how graph theory and graph convolutional neural networks are leveraged to model user‑IP relationships, detect fraudulent advertising clusters, and improve detection accuracy and recall through a combination of unsupervised graph algorithms and supervised GCN training in a large‑scale ad‑anti‑fraud system.

GCNGraph Neural NetworksSpark GraphX

0 likes · 14 min read

Applying Graph Algorithms and Graph Convolutional Networks to Advertising Anti‑Fraud

58 Tech

Oct 16, 2020 · Big Data

Social Network Analysis and Graph Database Solution for 58 Community Using JanusGraph and Spark GraphX

This article describes how the 58 community builds a large‑scale social network graph, evaluates graph databases such as Neo4j, JanusGraph and HugeGraph, implements centrality metrics with Spark GraphX, and designs a JanusGraph‑based pipeline for detecting valuable and fraudulent users.

JanusGraphSpark GraphXbig data

0 likes · 16 min read