eBay | BestHub

DataFunSummit

Jun 4, 2024 · Artificial Intelligence

Multimodal and Graph Neural Network Techniques for eBay Recommendation Systems

This article details eBay's practical experience integrating multimodal data and graph neural networks into its recommendation pipeline, covering pain‑point analysis, a twin‑tower multimodal embedding model with triplet loss and TransH, engineering design, experimental results, and key takeaways for future AI‑driven product development.

GNNMachine LearningMultimodal

0 likes · 19 min read

Multimodal and Graph Neural Network Techniques for eBay Recommendation Systems

DataFunTalk

Aug 5, 2022 · Big Data

Delta Lake Principles, eBay Migration, and Practical Enhancements

This talk by eBay software engineer Zhu Feng explains the fundamentals of Delta Lake and Lakehouse architecture, outlines eBay’s migration from Teradata to a Spark‑based platform, and details the custom enhancements, performance optimizations, and operational improvements implemented to support large‑scale update and delete workloads.

Delta LakeSparkbig data

0 likes · 16 min read

Delta Lake Principles, eBay Migration, and Practical Enhancements

DataFunSummit

Sep 6, 2021 · Artificial Intelligence

Graph Neural Network‑Based Payment Fraud Detection at eBay

This article explains how eBay uses graph neural networks and a heterogeneous‑graph fraud detection framework (xFraud) to improve payment risk assessment, overcome the limitations of traditional machine‑learning models, and effectively identify both individual and organized fraud in a large‑scale e‑commerce environment.

Dynamic GraphGraph Neural NetworksMachine Learning

0 likes · 15 min read

Graph Neural Network‑Based Payment Fraud Detection at eBay

DataFunTalk

Jul 15, 2021 · Artificial Intelligence

Graph Neural Network‑Based Payment Fraud Detection at eBay

The article explains how eBay protects its global payment system using a graph‑neural‑network driven risk management framework called xFraud, which combines heterogeneous graph sampling, node‑type encoding, attention mechanisms and dynamic‑graph extensions to detect and explain both individual and organized fraud patterns in real‑time.

Graph Neural NetworksMachine LearningRisk Management

0 likes · 13 min read

Architects Research Society

Mar 29, 2021 · Operations

eBay’s Scalability Best Practices: Functional Partitioning, Horizontal Sharding, Asynchronous Decoupling, and More

The article outlines eBay’s practical scalability principles—including functional partitioning, horizontal sharding, avoiding distributed transactions, aggressive asynchronous decoupling, moving work to async pipelines, virtualization, and intelligent caching—demonstrating how large‑scale web systems can be designed for linear growth and high availability.

Shardingarchitectureasynchronous

0 likes · 14 min read

eBay’s Scalability Best Practices: Functional Partitioning, Horizontal Sharding, Asynchronous Decoupling, and More

Architect

Jan 5, 2016 · Big Data

Apache Eagle: eBay’s Open‑Source Real‑Time Hadoop Data Security Platform

The article provides a comprehensive technical overview of Apache Eagle, an open‑source, distributed, real‑time security monitoring and alerting platform for Hadoop developed by eBay, covering its motivation, architecture, core components, machine‑learning based detection, typical use cases, and future development directions.

Apache EagleData SecurityHadoop

0 likes · 15 min read

Apache Eagle: eBay’s Open‑Source Real‑Time Hadoop Data Security Platform