Shaping the future of online commerce with innovative research in cutting-edge disciplines.

Microservices

Groot: eBay’s Event-graph-based Approach for Root Cause Analysis

The framework achieves great coverage and performance across different incident triaging scenarios, and also outperforms other state-of-the-art root cause analysis methodologies.

By: Hanzhang Wang, Applied Researcher
Machine Learning

Mathesis: Elements of Learning and Intelligence

A formal and interdisciplinary theory of learning and intelligence that combines biology, neuroscience, computer science, engineering and various branches of mathematics to provide a unifying framework, direction and a broader horizon for neural network and machine learning research.

By: John (Ioannis) A. Drakopoulos, Principal Applied Researcher
Machine Learning

Building a Product Catalog: eBay's 2nd Annual University Machine Learning Competition

Participating universities will structure listing data to help solve a real-world ecommerce challenge.

By: Senthil Padmanabhan
Cloud

Kubernetes Secrets: A Secure Credential Store for Jenkins

At eBay, we containerized Jenkins to provide a continuous build infrastructure on Kubernetes Clusters to power the ecommerce marketplace experience. Our goal was to leverage the capability of Kubernetes secrets, for managing the Jenkins credentials.

By: Vasumathy Seenuvasan and Ravi Bukka
Knowledge Graphs

Relation Embedding with Dihedral Group in Knowledge Graph

eBay researchers recently published a paper about a method for KG relation embedding using dihedral group. Experimental results on benchmark KGs show that the model outperforms existing bilinear form models and even deep learning methods.

By: Canran Xu and Ruijiang Li
Computer Vision

A Human-centric Approach for Evaluating Visual Search Models

Part of our mission within Core AI at eBay is to develop computer vision models that will power innovative and compelling customer experiences. But how can we compare several visual search models and say which of them works better? This article will describe a method that is tackling this problem directly from the eyes of the users.

By: Michal Romi, Michael Ebin and Chantal Acacio
Service Architecture

eBay’s New Approach to Managing a Vast Service Architecture

Learn how eBay's architecture knowledge graph was developed; the benefits eBay has received from it; and the use cases we see now and in the future for this approach.

By: Hanzhang Wang, Chirag Shah and Sanjeev Katariya

eBay Is Hiring

294 Job Openings Start Your Search

North
America

190 Job Openings

Europe, Middle East
& Africa

71 Job Openings

Asia
Pacific

33 Job Openings
Agile

Towards Agile AI

In this article, we propose a set of better practices, designed by and for eBay ML scientists, for facilitating weaving ML modeling into the cyclical Agile process flow.

By: Jean-David Ruvini
Machine Learning

Building a Product Catalog: eBay's University Machine Learning Competition

Trade has played a critical role in the history of humanity and yet, data from ecommerce, the modern form of trading, has received limited attention from academia. We at eBay want to change that.

By: Senthil Padmanabhan
Machine Translation

Going the Distance — Edit Distance 3

How do you normalize Edit Distance? Some simple ideas to get useful numbers about the changes in your text.

By: Silvio Picinini
Machine Translation

Going the Distance — Edit Distance 2

If you change a sentence, should you see the characters or words that changed? Edit Distance is back to help you figure this out.

By: Silvio Picinini
Machine Translation

Going the Distance — Edit Distance 1

What is Edit Distance? How could it be used to measure quality? Find out the basics about this simple metric used for Machine Translation.

By: Silvio Picinini
Testing

Measuring Success with Experimentation

Tips from eBay's Experimentation Science team on how you can best leverage A/B tests to measure the success and health of your product.

By: Tianlin Duan
Deep Learning

Explainable Reasoning over Knowledge Graphs for Recommendation

Incorporating knowledge graphs into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity between users and items can be discovered as paths, which provide rich and complementary information to user-item interactions. Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user’s interest. However, existing efforts have not fully explored this connectivity to infer user preferences, especially in terms of modeling the sequential dependencies within and holistic semantics of a path. We have developed a new model named Knowledge-aware Path Recurrent Network (KPRN) to exploit knowledge graphs for recommendation.

By: Dingxian Wang, Canran Xu, Hua Yang and Xiaoyuan Wu
Computer Vision

Interactive Visual Search

Interactive visual search with user feedback helps buyers find the perfect item and while enjoying the exploratory journey.

By: M. Hadi Kiapour, Shuai (Kyle) Zheng and Robinson Piramuthu
Computer Vision

Seven Tips for Visual Search at Scale

We present seven tips for visual search at scale, based on our KDD 2017 paper titled "Visual Search at eBay."

By: Fan Yang, M. Hadi Kiapour, Robinson Piramuthu and Qiaosong Wang
Computer Vision

Beyond Logos and Patterns: How We’re Training eBay’s AI to Understand Brands

We’re researching how to recognize brands using computer vision by training our AI to look beyond logos and iconic patterns.

By: M. Hadi Kiapour and Robinson Piramuthu
Computer Vision

ModaNet: A Large-scale Street Fashion Dataset with Polygon Annotations

Searching for an ideal dress or pair of shoes sometimes could be challenging, especially when you do not know the best keywords to describe what you are looking for. Luckily, the emerging smart mobile devices provide an efficient and convenient way to capture those products of interest in your photo album. The next natural thing is letting an ecommerce app like eBay figure it out for you.

By: Shuai (Kyle) Zheng, Fan Yang, M. Hadi Kiapour and Robinson Piramuthu
Testing

GUI Testing Powered by Deep Learning

Deep Learning (DL) is revolutionizing the face of many industries these days, such as computer vision, natural language processing, and machine translation, and it penetrates many science-driven products and technological companies, including eBay. These days, DL is taking its first strides in eBay’s Quality Engineering (QE) space, and it has already proven to outperform the best test veteran and industry-grade applications one could find.

By: Yotam Sharan, Honghao Wang and Sovan Rath
Mathematics

The Design of A/B Tests in an Online Marketplace

A/B testing is at the heart of data-driven decision making at eBay when launching product features to our site. However, the tests must be designed to carefully manage the interaction between the test and control groups.

By: Jason (Xiao) Wang
Search Science

Finding Desirable Items in eBay Search by a Deep Dive into Skipped Items

When you search on eBay and there are many matching listings, how does eBay figure out which ones to rank at the top? One key ingredient is to determine how well the listing matches the intent of the query.

By: Ishita Khan
Performance Engineering

Faster E-commerce Search

The search engine plays an essential role in e-Commerce: it connects the user's need with a set of relevant items based on a query. This is not a simple task; millions of queries per second need to be processed over possibly billions of items, and it is expected that every query will be executed in just a few hundred milliseconds using limited resources. In this article, we show how we improved eBay's search engine efficiency by over 25%, inspired by a technique coming from web search.

By: Roberto Konow
Applied Math

A Surprising Pitfall of Human Judgement and How to Correct It

Algorithms based on machine learning, deep learning, and AI are in the news these days.

By: David Goldberg
Machine Translation

The Biggest Dictionary in the World

By now, we are all familiar with the use of machine translation to produce versions of a text in different languages.

By: Jose Sanchez
Machine Translation

Collocations: The Secret Web of Language

Imagine this.

By: Jose Sanchez
Mathematics

Congruent Numbers Part III

Before demonstrating the claims made in Part I and Part II on this topic, let me mention two simple facts about integer solutions to .

By: David Goldberg
Mathematics

Congruent Numbers Part II

The method of my first post is too slow to find the side lengths for a triangle of area , which has many digits:

By: David Goldberg
Mathematics

Congruent Numbers Part I

Usually my posts have a connection to eBay, but this time I’m writing about a recreational math problem that caught my attention.

By: David Goldberg
Machine Learning

Personalized Search at eBay, part II

In the first part of this blog posting, I talked about how to estimate a buyer’s propensity to purchase an auction over a fixed price item.

By: David Goldberg