nhtlongcs/e-commerce-product-search

Relevance Prediction in E-commerce Product Search

25
/ 100
Experimental

This project helps e-commerce platforms accurately match customer search queries to products and categories, even if the queries are in multiple languages, mix languages, or use informal terms. It takes customer search terms and product information (like titles or categories) as input, then outputs a relevance score, helping improve search results. This is ideal for e-commerce managers, product catalog specialists, or anyone responsible for search and discovery on a global online store.

No commits in the last 6 months.

Use this if you manage an e-commerce platform and need to improve how search queries from diverse, multilingual customers are matched to your product catalog, especially across different languages.

Not ideal if your e-commerce platform only operates in a single language and already has highly accurate search relevance.

e-commerce-search multilingual-marketing product-discovery online-retail search-relevance
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 7 / 25
Community 11 / 25

How are scores calculated?

Stars

13

Forks

2

Language

Python

License

Last pushed

Sep 27, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/nhtlongcs/e-commerce-product-search"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.