guoguibing/librec

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

3257 stars · 1018 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LibRec is a Java library for recommender systems implementing over 70 state-of-the-art recommendation algorithms. It supports the two classic recommendation tasks of rating prediction and item ranking with a modular architecture covering data splitting, conversion, similarity, algorithms, evaluators, and filters.

Use cases

• build a movie recommendation engine in Java
• run collaborative filtering experiments on rating datasets
• compare matrix factorization algorithms for rating prediction
• generate top-N item rankings for users
• benchmark recommender algorithms on sparse datasets
• prototype a custom recommendation algorithm

When to choose

• you need a mature Java library with a wide range of recommendation algorithms
• you want to evaluate and compare recommender models with built-in evaluators
• your stack is JVM-based and you need rating prediction or item ranking

When to avoid

• you need deep learning based recommenders or GPU acceleration
• you want a production recommendation service rather than an algorithm library
• you work primarily in Python and prefer libraries like Surprise or implicit

Facets

library · maturity maintenance

machine-learning data-science search-engine machine-learning data-science jvm cross-platform recommender-systems collaborative-filtering matrix-factorization tensor-factorization rating-prediction item-ranking algorithms

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markdown · JSON · MCP: product_card(name="guoguibing/librec")