Gorse Recommender
Gorse is an open-source recommendation engine written in Go that automatically trains models to generate personalized recommendations by importing items, users, and interaction data, supporting collaborative filtering, AutoML optimization, distributed deployment, and RESTful API interfaces.
## Gorse Recommendation Engine Gorse is an open-source recommendation engine written in Go that automatically trains models to generate personalized recommendations by importing items, users, and interaction data. **Key Features:** - Multi-source recommendations: popular items, latest content, user-based and item-based collaborative filtering - AutoML for automatic model optimization - Distributed prediction with horizontal scaling capability - RESTful APIs for data management and recommendation requests - Online evaluation of recommendation performance - Web dashboard for monitoring and cluster status **Usage Instructions:** 1. After starting the application, access the web dashboard to view system status 2. Default login credentials: username `admin`, password `admin` 3. To change password, edit the configuration file `/lzcapp/var/config/config.toml` 4. Import users, items, and interaction data via RESTful API 5. Use https://github.com/lazycatapps/gorse/blob/main/import-sample-data.sh script to import sample data (modify BASE_URL in the script to your actual access address) 6. After first data import, restart the service to immediately trigger recommendation analysis 7. System automatically trains models and generates recommendations 8. Use API endpoints (port 8087) to retrieve personalized recommendations **Official Website:** https://gorse.io **Upstream Repository:** https://github.com/gorse-io/gorse **Repository:** https://github.com/lazycatapps/gorse.git
