Today we’re joined by Luna Dong, Sr. Principal Scientist at Amazon.
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In our conversation with Luna, we explore Amazon’s expansive product knowledge graph, and the various roles that machine learning plays throughout it. We also talk through the differences and synergies between the media and retail product knowledge graph use cases and how ML comes into play in search and recommendation use cases. Finally, we explore the similarities to relational databases and efforts to standardize the product knowledge graphs across the company and broadly in the research community.
Connect with Luna!
- Blog: Amazon’s Product Knowledge Graph
- Paper: AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types
- Blog: AutoKnow
- TXtract: Taxonomy-Aware Knowledge Extraction for Thousands of Product Categories
- Octet: Online Catalog Taxonomy Enrichment with Self-Supervision
- Ceres Web Extraction Keynote
- Check out our TWIML Presents: series page!
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- Check out the official TWIMLcon:AI Platform video packages here!
- Download our latest eBook, The Definitive Guide to AI Platforms!
“More On That Later” by Lee Rosevere licensed under CC By 4.0