Data Module Introduction¶

RecBole not only implements lots of popular recommender models, but also collects and releases 28 commonly-used publiced datasets. You can freely download these datasets following our docs Dataset Download.

For extensibility and reusability, Recbole has a flexible and extensible data module. Our data module designs an elegant data flow that transforms raw data into the model input. Detailed as Data Flow. In order to characterize most forms of the input data required by different recommendation tasks, RecBole designs an input data format called Atomic Files. All the input data should be converted into Atomic Files format. Besides, we design a data structure called Interaction to provides a unified internal data representation for different recommendation algorithms.

Plus, RecBole supports both explicit feedback (labeled data) scenes and implicit feedback (unlabeled data) scenes. For explicit feedback scenes, users can set the LABEL_FIELD in the config and RecBole will train and test model based on the label. For implicit feedback scenes, RecBole will regard all the observed interactions as positive samples and automatically select the negative samples from the unobserved interactions (which is known as negative sampling). For more information about label setting in RecBole, please read Label of data.

Here are the related docs for data module: