DataGenCARS: A generator of synthetic data for the evaluation of context-aware recommendation systems

In this paper, we present DataGenCARS, a complete Java-based synthetic dataset generator that can be used to obtain the required datasets for any type of scenario desired, allowing a high flexibility in the obtention of appropriate data that can be used to evaluate CARS. The generator presents features such as: a flexible definition of user schemas, user profiles, types of items, and types of contexts; a realistic generation of ratings and attributes of items; the possibility to mix real and synthetic datasets; functionalities to analyze existing datasets as a basis for synthetic data generation; and support for the automatic mapping between item schemas and Java classes. Moreover, an experimental evaluation illustrates the interest and the benefits provided by DataGenCARS.