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landing_page/qdrant-landing/content/solutions/recommendation-engine.md
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---
title: Recommendations
icon: advertising
tabid: recommendations
landing_image: /content/images/abstract_cubes_3.svg
image: /content/images/recommendations.png
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.
Qdrant allows you to create a recommendation engine with custom filters and real-time updates.
No need to deploy a MapReduce cluster.
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, user vectors can be updated in real-time, no need to deploy a MapReduce cluster.
Understand user behavior in real time.