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Project description
Rsdiv: Reranking for Multi-objective Optimized Recommender Systems
rsdiv provides the measurements and improvements for the multi-objective/diversifying tasks.
Some of its features include:
- various implementations of diversifying/ensemble reranking modules.
- various implementations of core recommender algorithms.
- evaluations for recommender systems from a quantitative/visual view.
- easy-to-use benchmarks for comparing and further analysis.
- automated hyperparameter optimization.
Installation
You can simply install the pre-build binaries with:
pip install rsdiv
More installation options can be found here.
Basic Usage
Prepare for a benchmark dataset
Evaluate the results in various aspects
Reranking for diversity improvement
TODO
More diversifying algorithms
-
implement the Bounded Greedy Selection Strategy, BGS diversify algorithm
-
implement the Determinantal Point Process, DPP diversify algorithm
Hyperparameter optimization
- compatible with Optuna.
Ensemble ranking
- support the ensemble ranking modules
For developers
Contributions welcome! Please contact us.
During your development stage, make sure you have pre-commit
installed in your local environment:
pip install pre-commit
pre-commit install
Project details
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