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eBay Tech Blog

To support the world’s largest internet marketplace, eBay tackles technical challenges at a scale that few others have. With this blog, we share our experiences working on those challenges with the technical community.


Complementary Item Recommendations at eBay Scale

By: Yuri M. Brovman

Generating relevant complementary item recommendations that drive conversion at eBay is a challenging problem. In this blog post, we describe some of these challenges, and how we incorporated several different signals, including behavior-based (co-purchase, co-view, co-search, popularity) and content-based (title text), to significantly enrich the number and quality of candidate recommendations. This can produce an improved user shopping experience, which can lead to increased transactions between eBay buyers and sellers, and an increase in the number of items bought, which is good for the eBay marketplace as a whole.

Featured Blog Posts

Seven Tips for Visual Search at Scale
ModaNet: A Large-scale Street Fashion Dataset with Polygon Annotations
Event Sourcing in Action with eBay's Continuous Delivery Team (Part 2)
Elasticsearch Performance Tuning Practice at eBay

SRE Case Study: Triaging a Non-Heap JVM Out of Memory Issue

By: Eric Tian

Most Java virtual machine out of memory issues happen on the heap, but this time proved to be a little different.

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Explainable Reasoning over Knowledge Graphs for Recommendation

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

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

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

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


eBay OAuth Client Library

By: Sandeep Dhiman

To make integrations with eBay RESTful APIs easier, eBay provides client libraries in C# and Java to make it simpler to set up authorization and reduce the amount of code application developers have to write to get OAuth Access Tokens.


Sharing Modules Across Experience Services and Multi-Screen Applications

By: Chuck Zheng

By now most eBay core business flows have gone through the journey of implementing Experience Service-based multi-screen application solutions, where web and mobile native app user interfaces are composed of one or more modules, and Experience Services directly returns these modules to clients with content synthesized from backend data sources, localized and formatted, ready for render and user interaction. This article outlines a plan to move more modules to a shared environment.


Providing Metadata Discovery on Large-Volume Data Sets

By: Satbeer Lamba and Sudeep Kumar

Many big data systems collect petabytes of data on a daily basis. Such systems are often designed primarily to query raw data records for a given time range with multiple data filters. However, discovering or identifying unique attributes present in such large datasets can be difficult.

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