DAReS is a proposed zero-configuration recommender system framework that uses a Dataset Description Language (DsDL) metadata schema to automate feature engineering, model selection, and hyperparameter tuning.
Secon d workshop on information hetero- geneity and fusion in recommender systems (hetrec2011)
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Dataset-Agnostic Recommender Systems
DAReS is a proposed zero-configuration recommender system framework that uses a Dataset Description Language (DsDL) metadata schema to automate feature engineering, model selection, and hyperparameter tuning.