Files
landing_page/qdrant-landing/content/solutions/recommendation-engine.md
T

25 lines
904 B
Markdown

---
title: Recommendations
icon: advertising
tabid: recommendations
landing_image: /content/images/recomendations_big.webp
landing_image_png: /content/images/recomendations_big.png
image: /content/images/solutions/recomendations.svg
image_caption: History-based Recommendations
default_link:
default_link_name:
weight: 30
short_description: |
User behavior can be represented as a semantic vector is similar way as text or images.
Vector database allows you to create a real-time recommendation engine.
No MapReduce cluster required.
sitemapExclude: True
---
User behavior can be represented as a semantic vector is similar way as text or images.
This vector can represent user preferences, behavior patterns, or interest in the product.
With Qdrant vector database, user vectors can be updated in real-time, no need to deploy a MapReduce cluster.
Understand user behavior in real time.