gorse is an offline recommender system backend based on collaborative filtering written in Go.

This project is aim to provide a high performance, easy-to-use, programming language irrelevant recommender micro-service based on collaborative filtering. We could build a simple recommender system on it, or set up a more sophisticated recommender system using candidates generated by it. It features:

  • Implements 7 rating based recommenders and 4 ranking based recommenders.
  • Supports data loading, data splitting, model training, model evaluation and model selection.
  • Provides the data import/export tool, model evaluation tool and RESTful recomender server.
  • Accelerates computations by SIMD instructions and multi-threading.


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