D2KLab/entity2rec
entity2rec generates item recommendation using property-specific knowledge graph embeddings
This tool helps e-commerce managers and content curators create personalized recommendations for their users. It takes data about user interactions (like purchases or views) and item characteristics from a knowledge graph, then outputs a ranked list of items tailored to each user. This is perfect for anyone managing a product catalog or content library and wanting to improve user engagement through better suggestions.
183 stars. No commits in the last 6 months.
Use this if you manage a large catalog of items or content and want to generate highly relevant, personalized recommendations for individual users based on their past behavior and item attributes.
Not ideal if you only have basic user interaction data without rich item descriptions or a structured knowledge graph, or if you need real-time recommendations for extremely high-traffic applications.
Stars
183
Forks
43
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 17, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/D2KLab/entity2rec"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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