Research Blog

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.

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

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.

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.

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.

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.

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.

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.

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

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

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

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.

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.

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

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

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

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.