Metarank Docs
  • Introduction
    • What is Metarank?
    • Quickstart
    • Performance
  • Guides
    • Search
      • Reranking with cross-encoders
  • Reference
    • Installation
    • Event Format
      • Timestamp formats
    • API
    • Command-line options
    • Configuration
      • Feature extractors
        • Counters
        • Date and Time
        • Generic
        • Relevancy
        • Scalars
        • Text
        • User Profile
        • Diversification
      • Recommendations
        • Trending items
        • Similar items
        • Semantic similarity
      • Models
      • Data Sources
      • Persistence
    • Deployment
      • Standalone
      • Docker
      • Kubernetes
      • Prometheus metrics export
      • Custom logging
      • Warmup
    • Integrations
      • Snowplow
  • How-to
    • Automated ML model retraining
    • Automatic feature engineering
    • Running in production
  • Development
    • Changelog
    • Building from source
  • Doc versions
    • 0.7.9 (stable)
    • master (unstable)
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  1. Reference
  2. Configuration

Recommendations

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Last updated 2 years ago

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Starting from version 0.6.x, Metarank supports three types of recommendations:

  • : popularity-sorted list of items with customized ordering.

  • : matrix-factorization collaborative filtering recommender of items you may also like.

  • : a content-based semantic similarity recommender, based on neural embeddings.

Trending
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